Data top 50

DENT Wireless (CMC: DENT) Tokenizing the Mobile Data Industry!

2017.06.26 02:46 lagaiphone DENT Wireless (CMC: DENT) Tokenizing the Mobile Data Industry!

#Dentcoin subreddit ##DENT Wireless token (Ticker Symbol - DENT) * Dent is a currency for buying and selling mobile data worldwide. It's an ERC20 token, created on the Ethereum blockchain to reduces the effort of designing a decentralized system from scratch, while smart contracts provide a trustworthy, fraud-proof way of defining the mobile data packages as well as the process of buying and selling them.
[link]


2017.01.19 17:52 tetiana_ftv Jelastic Cloud Platform: guides, recommendations, news

Jelastic is a cloud platform for hosting applications that can be deployed on bare metal hardware or any IaaS. Currently, it is running as public, private and hybrid cloud on top of more than 50 data centers worldwide. The platform provides certified containers for Java, PHP, Ruby, Node.js, Python and .NET and the ability to use custom Docker containers.
[link]


2008.08.26 20:25 /r/Rowing

A subreddit for all rowing related news, erging advice and fitness discussion related to the sport.
[link]


2020.10.26 20:14 oscdawg [US-ND][H] Artisans (Alpha Salvador, SUK, Dwarf Factory Terrarium)[W] Paypal / Trades

Timestamp

Hello all,
I have some artisans available for sale/trade. Mainly looking to trade for items on my wishlist or blue artisans but I'm up for any offers. Let me know if you need better pictures of anything. Please comment before PM, whether Discord or Reddit.

Discord @ oscdawg#3700
Imgur Wishlist

Artisan Price Available Details
Wildstory Caps Yu Ama $125 No Ama - Translucent Blue/Purple
Alpha Keycaps Bombay Salvador Trades Yes Salvador Black, Green Eyes, Pink Ears
Alpha Keycaps Showa Salvador Trades Yes Salvador Black, White, and Red
CYSM Classic Blue Ice Cube $90 Yes CYSM Blue/Translucent Ice Cube
GirlDC Roadhog $25 Yes Roadhog - Includes Top and Bottom
SUK Data Weaver Keybuto III $75 Yes Keybuto III - Translucent Dark Blue/ Blue Face
TXD Keycaps Frigid Care Bare $45 Yes Care Bare - White/ Light Blue
Alpha Keycaps Albison – Thundering Herd $35 Yes Albison - Green/Yellow
Dwarf Factory Terrarium SA Profile Fortune Clover $50 Yes Terrarium SA Profile - Magenta base with Green Clovers
submitted by oscdawg to mechmarket [link] [comments]


2020.10.26 19:53 anghelfilon Need advice for starting a career in CS

Hi, people!
Just found this subreddit and it's perfect because I'm thinking about changing my job and trying to do something in CS and I could sure use some advice from people in this line of work. I currently work in the financial asset management industry (Europe) in back-office and for a few years have dabbled with doing some programming through Excel VBA.
I like computers, I'd even say I'm passionate about them. I've build my own computers ever since I was a teenager and have always been the tech support in my family. I've always solved any issue that was solvable and Google is my friend.
I've had 4 years of C++ classes in highschool and for the past 4-5 years at my job I've been doing some work to automate as much as possible for what we do. I've done all sorts of stuff with Excel macros and then building VBA code on top of that, combining code with Excel formulas, conditional formatting to color code stuff depending on our needs. Have done excel macro files that execute code when opened and then close themselves when they're done. Have done excel macro files that move or rename files, make folders, read/write/process .txt, .csv and .xml files (and of course, other excel files). Have done files that send e-mails with attachments (also processed by code). Have done work processing excel files with over 100k rows and processing that data, where normally you'd think to search for every row in the entire list again to get other values and that approach would take hours on a normal desktop machine, I've optimized it with data sorting to run in 60 seconds.
Frequently we ask quotes from software developers to do stuff for us and the cost is high and time to do it is insanely slow. Many many times I've done the same work they'd quote us for weeks or even months to do in a day or two. So I've done what I consider (and my colleagues for that matter) to be some clever stuff and all this work on my part has taken my department from doing a lot of stuff manually (copy/pasteing and sending e-mails) and printing lots of paper and checking on the printed paper to being virtually paperless and constantly working with 50+ of these excel macros that do most of the boring repetetive work, obviously much much faster than we can do it, but also with less operational risk and with more checks along the way to verify that everything is ok.
So I've been thinking of changing my job and trying to do this sort of stuff full time. I currently have two ideas:
1) Learning even more and trying to find a job doing RPA properly for a company like UiPath
2) Going freelance and trying to do exactly this sort of thing for companies that still do things like reports by manually copy/pasteing from one excel file to another

The way I see it, my programming knowledge isn't fantastic. I'm self taught in pretty much all of this, but I know there's loads more to learn. However my experience in the financial services industry and understanding of finance/marketing/business probably gives me an edge as I don't need much explaining to understand what needs to be done. I'd like option two more as I'd have more freedom and I could work for any company on Earth, but I'm not sure how many companies I could actually convince to give me the business.

Can any of you give me any hints, ideas, advice? Are my skills marketable or in demand? Should I focus more on education first and learn even more? If so, learn what? What are your thoughts on my situation?

TL;DR: I've automated stuff in Excel with VBA and want to do more for more money. How?
submitted by anghelfilon to cscareerquestions [link] [comments]


2020.10.26 18:15 dc_gay_man 43.4% Registered NCians Have Voted Make Your Plan + Vote

As of 1 PM, 43.40% NCians Statewide have Voted. In terms of percentage, Henderson County is #3 in NC-11. Mitchell, Buncombe, Henderson, Transylvania, and Yancy are top 5 in that order. All are above 45%.
Mitchell County will be over 50% by tomorrow. Look at FAR RIGHT of link below.
Voter Turnout Statistics NCSBE
submitted by dc_gay_man to MitchellNC [link] [comments]


2020.10.26 17:47 djmuaddib First Marathon, NYC Virtual on Pine Creek Rail Trail, 3:59:10

*Sorry, I am having trouble with the race report generator and don't know how to copy the source here and have it come out formatted properly. I feel like a dunce but whatever, re-formatted manually.

Race information

What? 2020 Virtual NYC Marathon
When? 10/25/2020
How far? 26.2 miles
Where? Jersey Shore, PA
Stats: 36 yo male, 5'7, 142 lbs.
Shoes: Saucony Endorphin Speed
Website: https://www.nyrr.org/tcsnycmarathon
Strava Activity: https://www.strava.com/activities/4243862757
Finish Time: 3:59:10

Goals

Goal Description Completed?
-------------------------------
A Sub-4:00 Yes
B Sub-4:05 Yes
C Don't Bonk Yes
D Finish Strong Yes
E Finish Yes

Pictures:

Strutting around after to cool off.

Splits

Mile Time
------------
1 8:53
2 9:14
3 9:10
4 9:11
5 8:50
6 9:10
7 9:09
8 9:06
9 9:04
10 9:13
11 9:05
12 9:05
13 9:11
14 9:07
15 9:08
16 9:08
17 8:53
18 9:07
19 9:05
20 9:11
21 9:04
22 9:11
23 8:56
24 9:13
25 9:18
26 9:20
27 ~2:00
Training
First a little important background. I am a 36 yo male, 5'7, 142 pounds, RHR ~55, MHR ~200. Since 2017 I've lost about 50 pounds, 32 or so in the past year. I detail that saga here. I first started to get deeply into outdoor running in March of this year when my gym closed due to the pandemic and outdoor running became my only outlet for consistent exercise. Prior to then, I did primarily spin and dumbbell routines at our gym. I started out with not much of a system, but ran my first half in May on a whim (2:08:48). By July I decided that I was ready for a marathon training program, or maybe not ready, but right now is one of the few times in my life I felt like I had the time and drive to make it happen.
I picked what I would regard as kind of a sucky training program, but it ended up working out for me: Runner's World 3:30–4:30 Intermediate Plan. The obvious problem with this plan is the extraordinarily wide range of goal times that theoretically the plan can churn out. If I had been smart I would've picked a plan with a specific goal like sub-4, but as it turns out, I think this sucky plan actually kind of worked for me because of how adaptable it ended up being. I obviously have never done marathon training so being able to kind of go by feel — knowing the plan was already kinda whack — took some of the pressure off of adhering strictly to a plan. After the first few weeks I figured out that two workouts a week were too much strain for me and I dropped to one, typically either fartleks, intervals, or hill repeats (my favorite). I did 2–3 half time trails, too. I peaked at 50 mpw, typically working in a slight recovery week every 3–4 weeks.
I did my training on hilly gravel trails throughout the dog days of summer, beginning at the end of July. I highly recommend this strategy if you're training for a flat fall marathon, because you build up a lot of leg strength, you gain heat acclimation, and you're forced to learn proper hydration/nutrition early or you'll be in real danger. Plus when fall rolled around, everything suddenly felt like a breeze; I really needed that cool off by week 12 to push me through the hardest training weeks.
I had two minor injury episodes — in early August I strained an intercostal muscle and was out of commission for about three days; in late August I bonked severely on a hot 17-mile long run, felt fine the rest of the day, woke up in the middle of the night vomiting my brains out, and felt hungover the whole next day, some kind of combo of dehydration/heat exhaustion? I didn't actually miss any days on this, but the rest of the week was a struggle. Otherwise my number one sore spot was ankles, though by the end of the training plan I had no ankle soreness; I think I successfully strengthened them!
In the few weeks prior to the marathon I did a half time-trial (9:04 pace), a 10k steady/tempo (8:27 pace), and a 10-mi steady (9:03 pace, on the actual race route) in efforts to gauge what was a reasonable finishing marathon pace for me. Based on my Hstrain on these, I thought I could comfortably finish a flat marathon route at a 9:09 pace, especially given that my training route had significantly higher elevation gain. My plan was to maintain that pace at a high Z2/low Z3 effort, which would be consistent with my efforts in the three aforementioned runs. The PROBLEM here is that 1) I'm inconsistent, 2) My race prep was ineffective, and 3) I was really anxious and my HR was sky-high throughout the whole race. So my advice here is build those factors into your expectations when deciding on marathon time, or at least be real with yourself that it's going to be harder than you're anticipating. Your last few training runs at marathon pace are not necessarily super reliable indicators of how hard you can go. There's a lot more to it — more on that below.

Pre-race

I found carb-loading and tapering very confusing and perhaps not helpful and if I was to do this over again, I would try not to overthink it so much. I ate big bowls of cereal most of the week for breakfast, along with big fruit smoothies /w whey protein. Lunches for me are typically light — homemade bread, olive oil, apple, granola bar — but I threw in some almonds, goldfish, and chocolate milk. Friday night I ate Dominos, popcorn, and ice cream. Saturday I went lighter — breakfast sandwich on bagel, smoothie for lunch, sushi for dinner, 8 oz of ipa, applesauce cake, and some goldfish. I ran two miles on Saturday at an easy pace and felt good. Went to bed at 12:00 and had just a bit of trouble sleeping due to nerves, but did ultimately get a full night's sleep.
Woke up at 9:00 on race day, had a fruit smoothie for breakfast with half a scoop of whey protein, 25 oz of water throughout the morning, and half a cup of coffee (wanted to hold back on caffeine because my gels have 40 mg each). We drove to the Pine Creek Rail Trail and I got started around 12:50 (46F/60% humidity, warmed up to 53F by mile 16). I took a 20 oz bottle of Nuun Endurance and 4 Gu gels with me (mile 7, mile 12, mile 17, mile 22). My partner stayed at the trailhead parking lot, the plan being to swap out my empty bottle of Nuun at the 16-mile mark for an 18 oz bottle of plain water, after which he would run the last ten miles with me. I did five minutes of activation drills and took off.

Race

An absolute mess from the very beginning! I started out with no headphones as it was a crisp autumn day and I wanted to enjoy the weather and sounds of the leaves and be in the moment. After about a quarter mile I looked down at my watch to check pace and HR and my HR was a bit high. Figured it was nerves. Looked again at half a mile, still high. Looked again at a mile, still high, already into the 160s. While my A goal was to finish sub-4, I was playing HR very conservatively because I wanted to finish more than anything, so my plan was to stay in mid-to-high HRZ 2 for as long as possible. Based on training runs, I figured this would translate to an avg 160 bpm for the whole race (my MHR is 200, figured out through multiple FTP tests, though I have it as 198 in strava) which would be an 80% effort. I was anticipating having the first ten miles be almost exclusively in the 150s and ending in the 170s. NOPE! Nerves, nerves, nerves, and I think my diet and sleep weren't effective either.
By mile 5 my confidence was shot and I was very frustrated, figuring that sub-4 was out the window and there was little to no guarantee of even finishing. I popped music in to try and improve my mood and vowed not to look at my watch again for at least three miles and go by feel. It was very pretty and crisp fall weather and I tried to enjoy that. When I made the turn back to the parking lot at the 8th mile my HR was still way too high (173, almost 87% of MHR), but it was at this point that I developed what I can only regard as a severe fuck-it attitude that I think worked in my favor. I decided that I no longer cared about the bum start nor my watch and would do as much of the rest of it by feel as I could sticking to the goal marathon pace. If I bonked, whatever. In my experience on long runs where I was not at 100%, backing off pace midway through did not typically help me recover anyway. If I'm having a bad day, it's a bad day. Plus this was race day and I was counting on adrenaline and desire to see me through.
So then it was trudging back to the parking lot, probably one of the worst stretches for confidence because I was already feeling a little stiff. By mile 16 I was definitely feeling the fatigue in my legs and a whiny right quad. I felt my energy reserves dissipating, but getting back to the parking lot and swapping my bottle and having my partner join me was a huge boost in terms of my general attitude. Not only did having someone with me assuage my concerns about potential injury/bonking, but it was a nice distraction to have another runner with me so I wasn't alone in the void with my negative thoughts. Miles 16–21 were arguably the best of the whole race for me and also probably my fastest consistent stretch — part of this had to do with the fact my partner was running a little faster than me and that helped me pace myself without looking at my watch; I tried to keep him at a certain distance ahead of me and it worked, felt much more natural than looking at my watch frequently.
When we turned at mile 21 (which I had been dreading) I nearly stumbled and felt an abrupt shock in my leg, which scared me, but it turned out to be nothing and I got right back on it. My HR at this point was 180 and I stayed right up around 180 for the remainder of the race. Frankly, I couldn't believe I had this much tolerance for threshold pace, that I had spent most of the race in high tempo and low threshold. This was not what I trained for and I was sure I was going to bonk. But I never bonked. Reader: I never bonked!
The last five miles were basically spent in a kind of numb disbelief that I was going to finish and that I didn't feel the world crashing down around me. My legs were concrete, not exactly in true pain anymore, but kind of just like I had two large wooden stumps attached to my hips swinging around underneath me, that I was sitting on top of an uncomfortable machine that was sputtering on. When it became clear at mile 23 (gel #4) or so that I had kept under 9:09 pace and had enough banked to take the last few miles conservatively, it was an immense relief, but I didn't slow down too much because I thought that was a slippery slope to walking/stopping, so I eased down to around 9:20. I kept saying to myself, "Finish strong, finish strong" over and over and skipping through my playlist to get to better songs. I kept being sure that I was going to have a sudden breakdown in the last mile which was scary and I tried to put it out of my head. I went up the last little hill, crossed a roadway with thankfully no traffic, and took the last .5 mile stretch toward the parking lot, looking to the side into the woods or toward the sky in order not to see the finish. When I hit 26.2 I pumped my fist and spiked my empty water bottle on the ground. It was over, 3:59:10.

Post-race

I immediately threw on a jacket and just walked around the parking lot for 10–15 minutes, looking at my data and trying to upload to Strava. I did a little stretching (saved the big stretches for home) and then piled in the car, ate goldfish, saltines, granola bars, almonds, banana, drank water, etc. as much as I could stomach, though I didn't have much of an appetite at all. I took off my shoes and tried to keep my legs moving in the car so they wouldn't lock up, cuz we had a 45 minute drive home. I listened to a podcast to try to get my mind off the discomfort
When we got home I made another 16 oz of Nuun and some chocolate milk with a half scoop of whey protein. I showered, put my legs up on the wall for 15 minutes, stretched, and ordered Chinese food which I could barely eat. I had just a little bit of diarrhea and my HR was steadily at 95 bpm for the rest of the night, just sitting on the couch. Weighed myself and saw that I had basically hydrated appropriately, was only down about 1.5 pounds from the morning. It was hard to get to sleep because I was still full of adrenaline, so I watched Simpsons and played Ghost of Tsushima. Wrote in my journal, read a bit, and got to bed at 1:00.
Today I feel pretty stiff, though not inordinately so, no limping, no severe pains. I'd say the most comparable thing I've done in terms of strain is The Great Saunter about four years ago, when I was considerably less in shape. I feel probably a little worse today than I did then, but I'd also say the Saunter primed me for the kind of leg fatigue I'd feel on a marathon so I recommend something like that as a gateway event.

Final Thoughts:

  1. I spent the race, on average, at about 87% of my MHR. I've read that seasoned elite marathoners do their marathons around 90–93% of MHR. It could be that my watch was messed up and locking onto my cadence, but I don't think I've had problems with that in the past, so my takeaway here is that I need to deemphasize HR as a metric for my sustainable performance and focus more on pace and feel, period. I let HR psych me out early on in this race. The other thing I learned here is that I seem to have a higher lactate threshold — and maybe more sheer fucking psychological willpower — than I ever could have imagined. So, yeah, I think I'm going to maybe phase out HR training.
  2. I have a lot of potential. This was not really a good day — granted, the factor of race day nerves did not occur to me prior — I never felt good, and I still pulled out my A goal, which makes me think I have a lot more potential as a runner than I thought, that maybe I can challenge myself more in the future. On a good day could I have gotten something closer to 3:50? 3:45? I think I could have, which is crazy to me; it was never on my list of things to expect. Maybe in a couple years I can even shoot for BQ.
  3. Overthinking things almost fucked me. I overtapered, reducing mileage too fast over the course of two weeks when it should have been three. I carb-loaded stupidly, taking in too much sugar and fat, when I should've been sticking to healthier lean proteins and rice primarily. I let myself get anxious about the race to the point where my resting HR was at least ten beats too high at the start. And then I obsessed over my watch, pace, HR, etc. throughout the first 8 miles. Long story short: I need to chill out! Chilling out, however I can manage that, will undoubtedly improve my future performances.
I don't know what's next for me, probably few weeks of recovery, then I want to focus on middle distances, probably 10K and 5K, maybe even the mile. I've actually never done a true mile time trial on a track and I'm very curious to get a sense of what my true top pace might be, which I think would be a help in determining what's possible for me at other distances.
Last thing: I got major help for the training on this from running, AdvancedRunning, u/nerdjnerdbird, and Kofuzi, as well as from many friends and I thank you all thoroughly! Hopefully I get to do an IRL marathon by 2022, probably Chicago or NYC. My long-term dreams are Boston and Big Sur. Until then, I'm just going to enjoy running w/o goals for a couple weeks. Hope people found this helpful.
*This post was generated using [the new race-reportr](https://coachview.github.io/race-report), powered by [coachview](https://www.coachview.io), for making organized, easy-to-read, and beautiful race reports.*
submitted by djmuaddib to AdvancedRunning [link] [comments]


2020.10.26 16:54 Cyberrockz What It's Like To Interview For A Coding Job

part 2 is continuing...... if you find it useful please do up vote.

7) How to structure your coding interview timeline
Avoiding exploding offers and burnout while maximizing negotiating leverage and keeping your options open
The exploding offer dilemma
Here’s the situation you wanna avoid: You’ve just started interviewing with a company you're really excited about. Another company you've been talking to for a while sends you an “exploding offer”—an offer that expires in a week or even 24 hours. You have to respond to the exploding offer before your final round of interviews at the first company.
You don’t wanna have to decide between a real offer and a potential offer. Either decision has a big downside:

It's also bad for negotiation. The best way to get negotiating leverage with one company is to have an offer from another company. If your offers aren't open at the same time, you lose that leverage.
Work backwards from a signing date
So you want to do everything you can to ensure your offers come in at the same time. But how do you do that? The key is to work backwards:
Pick a "signing date" and stick to it. This is the date that you plan to make a final decision and sign an offer. This includes some allowed time for negotiating once you have all your offers in hand (more on that later).
Share your chosen signing date with every company as soon as you start talking to them. You may even want to ask them to confirm that they'll be able to work with your timeline. This way a company is much less likely to give you an offer that explodes before that date—they already know your timeline, so if they can't work with it they should tell you up front.
What if a company does give you an offer that explodes before your signing date, even though you told them about it early on? Don't panic. Politely remind them that you've been clear about your timeline from the beginning. Explain that you'd like to make your final decision on the date you've already shared with them.
If they still won't budge, you might be better off passing on that company—if they're comfortable squeezing you this early on in your relationship, that's a bad sign for how they'd treat you as an employee.
Now, some companies have policies about not having open offers for more than X days. So what if you're going through the interview process with one of those companies and it looks like you're moving too fast and the offer would come in too early and explode before the signing date you chose?
No problem. Most companies are happy to "pause" or slow down your interview process so the offer comes in later. This way both parties can get what they want: the company can follow their usual "offers explode after X days" policy, and you can have the offer still open on your pre-planned signing date.
How far out should my signing date be?
It depends. At a high level, you should allow as much time as you can afford to. Most people underestimate how long their job search is going to take. And when you end up in a time crunch at the end, it means less time at the negotiation stage. So allowing an extra week for your job search could literally mean earning tens of thousands of dollars more in your final salary.
If you have a current job or are a full-time student, try to allow more time by starting the process earlier.
Of course, some of us will be in situations where we really need to start our new job as soon as possible. That's fine. Do what works for you.
Keep in mind that you’re shooting for having enough time to practice and get through the whole interview process with multiple companies if you can. Think through how much time you can devote to each of these steps:

One more consideration: if you have the means, consider leaving yourself some time for a vacation before starting your new job. Job hunting is stressful. And that window of time between signing a new offer and starting a new job can be a rare window of low stress and low responsibility in your life.
Many companies are happy to accommodate this by setting your start date a few weeks after your signing date—just ask. Many offers include a signing bonus, which could help offset the cost of this extra time without a salary. But again, this'll depend on your means—not everyone can afford to take this extra time off.
Cast a wide net
Interview with multiple companies. Exactly how many companies depends on your situation, but the point is to avoid putting all your eggs in one basket. You want multiple offers by the end, so you can negotiate the best offer possible.
A good rule of thumb: send out applications to more places than you’re currently planning. If you end up getting too many interviews…well that’s a good problem to have! You can always "pause" or simply cancel the interview process with some companies.
Schedule your favorite companies last. Get interview practice with the places you aren’t as excited about. You’ll be in your prime by the time you interview with your top choices, so long as you don’t burn out.
Jot down your impressions after each interview. You’ll be surprised how much different companies can start to melt together after a couple weeks of interviewing.
Avoid burnout
If you’re casting a wide net and allowing several weeks for your job search, you need to be careful about burnout. The interview process is a marathon, not a sprint.
Space out your onsites. Onsites are draining. Try to keep at least a two day buffer between them—one day to recover after your last onsite, and one day to get ready for the next.
Don’t travel too much. You can quickly burn yourself out bopping across the country. When you have to travel for an interview, try to wait a few days before you travel again.
Batch interviews that are in cities you have to fly to. Try to avoid flying to the same city multiple times—though sometimes traveling to the same place twice is better than trying to cram three or more onsites into a short span of time.
8) Telling Better Stories For Behavioral Programming Interview Questions
Show, don’t tell”
You’ve probably heard this advice before. Maybe it was your 10th grade English teacher. Maybe it was career services in college. “Remember: show, don’t tell.”
And it’s good advice. When it comes to answering behavioral questions (like “Tell me about yourself”) in coding interviews, the difference between a good answer and a great answer comes down to showing rather than telling.
The problem is, people who give you the advice of “Show, don’t tell”… are themselves failing to follow it. They’re telling you to show, but they should be showing you how to show. That’s the hardest part!
So here are three specific tips for showing more and telling less.
1. Sprinkle in specific details
Imagine two responses to the stock interview question “Tell me about yourself.”
First:
I started programming about two years ago with some personal projects. I eventually got a job at a small tech company in my home town, and I’ve been working there about a year and a half. I like my job, but I’m looking for a new challenge, which I think your company could provide.
Then:
I got started programming because I wanted to build a social network for cats. That didn’t take off, but the prototype helped me get a job at a small tech company in my home town.
Last month, I read an awesome article on Hacker News about the social network your company is building. The scaling challenges you face seem like they’ll help me grow faster and stronger than my current role will.
The second response says a lot more about the candidate.
Why? Because of the specific details. An interviewer won’t remember the tenth person to say “I’m looking for a new challenge.” They will remember the person who tried to build a social network for cats and read about their company on Hacker News.
So don’t skimp on the details. Look out for opportunities to use specifics, especially if they’re at all quirky, funny, surprising, or otherwise memorable.
2. Tell a story from your life
Take another common question: “Why do you want to work here?”
People tend to just cross-reference their values with those of the company or team they’re interviewing with:
I’m really interested in technical blogging and open source. So I like that your company has some open-source work and contributes back to the community.
That’s a fine response. But to really wow your interviewer, try adding a specific story around those values:
A couple years ago, when I was still new to programming, I was working on this tricky bug. I found a post on a company blog where an engineer explained how her team solved the issue. She included a code snippet she’d open-sourced. I appreciated that she took the time to write about her team’s experience and share their solution. It helped me!
That’s how I first started getting into open source. I really wanna work with more engineers like that—who write about their work and try to help others in the community. So I was excited to see all the stuff your team shares on your blog and on the company’s Github profile.
The second response just sounds more genuine. It shows a personal connection to open source and technical blogging, instead of just telling it.
Anyone can look up a company’s core values and repeat them during an interview. It’s more meaningful to tell a story from your life that shows how those values benefited you or taught you something.
3. Use someone else’s voice
This one’s a neat trick. Consider one more standard behavioral question: “What’s your biggest strength?”
You might tell the interviewer:
I work well with others. Even under tough circumstances, I make sure my coworkers feel supported.
But a lightly detailed story is better suited to show this strength:
I have a coworker, Ana, who’s been an engineer for almost a decade. We worked together on this really tough, messy project.
Towards the end, she told me, “For such a hellish project, you really made things feel sane.” I think this is my biggest strength—I work well with others, even under tough circumstances.
When you respond with a story, you can refer to what other people have said about your best qualities. In this case, a ten-year tech veteran said you made a project feel less awful. That kind of praise is a lot more credible when it comes from someone else.
Practice, practice, practice
Remember these specific tricks for showing rather than telling:

  1. Use specific, memorable details. “Social network for cats” instead of “a personal project.”
  2. Tell a story from your life. “I was trying to solve a tricky bug…” instead of “I value open source contributions.”
  3. Use someone else’s voice. “’You really made things feel sane‘” instead of "I work well with others."
Try these tactics out on the questions below. Keep in mind, sometimes it’s easiest to start with a “tell” response, then spruce it up to “show.”

9) Common Issues In Coding Interviews
And how to fix them
The biggest, scariest issues
I keep getting lost or stuck in the middle of technical questions.
Getting stuck during a coding interview can be really demoralizing. That is, until you get good at getting un-stuck. That's right, you can get good at getting un-stuck! You just have to learn the steps.
But surprisingly, sometimes you're supposed to get stuck, and sometimes you're supposed to lose your train of thought. To understand why, read up on how the coding interview is like a maze
Of course, with more practice you're less likely to get stuck or lose your train of thought. Check out our practice coding interview questions.
Finally, make sure you're doing everything you can to get yourself into the best possible headspace in the 24 hours before your big interview.
It takes me forever to solve a single problem.
The trick to finishing problems faster is using a specific process and sticking to it:

  1. Brainstorm and design your algorithm by manipulating sample inputs by hand on the whiteboard. Don't start writing code until you know exactly how your algorithm will work.
  2. Code it up as quickly as possible. Don't get caught up in details like, "should this be a '<' or a '<='?"—just make a check mark in the margin and move on. Don't start debugging it until it's all written out.
  3. Finally, walk through your code with a sample input and fix any bugs you find.
The important lesson here is to never skip ahead. Only move on to the next step after finishing the last step. This keeps your thinking more organized, makes it easier for your interviewer to follow what you're doing, helps you avoid mistakes, and ultimately makes you move faster.
This process is explained in more detail in our general coding interview tips article.
I'm practicing, but I'm not getting better.
I don't have a CS degree. I don't understand big O notation and algorithms.
A lot of people struggle with data structures, algorithms, and big O notation. Especially people who don't have a computer science degree.
It's easy to think this stuff is just objectively hard to understand, since it's associated with the "academic" side of software. That makes it seem more technical and difficult.
The truth is this stuff just feels technical and difficult because people are bad at teaching it.
Yes, thinking in algorithms and data structures is a specific skill that's different from general coding. It's a separate thing you have to learn.
But it's very learnable. Check out our Intuitive Guide to Data Structures and Algorithms.
I . . . feel like I'm just not good at this stuff :/
This feeling is very common. The interview process makes us doubt ourselves. It eats away at our confidence. This is called impostor syndrome, and it can be fixed.
The rest of the job search process
How do I get interviews?
But I don't know the latest hip new framework or language.
How long should I allow for my job search?
I got an offer but it expires soon! What do I do?
What about behavioral questions? How do I prepare for those?
Practicing
I know I should practice, but I have trouble finding the time.
For most of us, saying, "I should spend a few hours practicing for coding interviews each week" just doesn't work. Whenever there's a spare hour, it's suddenly really important to send some emails. Or do laundry. Or do some other "productive" bit of procrastination.
The fix is to pick a specific, regular time for your interview practice. Block it off and stick to it.
An hour a day, or a few hours over the weekend. Just pick something you can actually commit to.
Open up your calendar and do it right now.
Couple more tips:

How should I practice?
Not all programming interview practice is made equal. There are a lot of things you can do to make sure you're getting the maximum possible benefit out of your practice sessions. Check out our guide to getting the most out of your coding interview practice.
How long should I spend on each each practice problem?
In general, a coding interview is about 45 minutes of problem solving. Sometimes you'll get a few short technical questions, but usually you'll only dig into one complex algorithmic coding interview question (like the ones in our course).
So, 45 minutes per question is a good rule of thumb. But don’t worry too much if you’re taking longer to finish our practice questions—you’ll get faster with time. Stressing about the clock usually does more harm than good.
Should I do mock interviews? How?
Yes! There are a few great websites that offer mock interviews as a service. Check out:

Or you can grab a buddy and organize some mock interviews yourselves.
For phone interview practice, do it over the computer. Use a shared coding environment tool like CoderPad, and actually talk to each-other over the phone or through Skype (great opportunity to test that your laptop's microphone works!).
For onsite interview practice, whip out some paper and pencils or, better yet, actually get on your feet and write stuff on a whiteboard.
You can even run a mock interview with a nontechnical friend! Try loading up one of our practice questions on a laptop or tablet—the progressive hints and gotchas allow your friend to use the page like a script.
And of course, real interviews are very effective as "mock interviews" :) Reach out to some more companies and try to get some extra interviews.
Onsite Interviews
What should I do the day before an onsite interview?
There's a lot to say about this, and getting yourself into the best possible head space the day before a big onsite can make a huge difference!
Read our full guide on what to do in the 24 hours before a big onsite interview.
And check out our guided meditation for visualizing yourself breezing through a day of onsite interviews.
My whiteboard always gets really messy :/
This is pretty common, and it can actually be a big problem. A messy whiteboard makes it more likely that you or your interviewer will get totally lost trying to understand your code, especially when you come back to it a few minutes later to walk through it with a sample input. Here are some tips:
Start in the very top-left corner of the board. Most people's instinct is to leave some margin on the left and top of the board, so their code comes out "centered." But this just ends up leaving you with less space. And you want all the space you can get.
Leave blank space between each line as you write your code. This makes it much easier to add an extra line later.
Take an extra second to carefully name each variable. Don't rush this part! It might seem like this'll slow you down, but using more descriptive variable names actually ends up saving you time in the end. Few reasons why:

  1. You're less likely to confuse your interviewer, which means you don't have to waste time explaining things.
  2. You're less likely to confuse yourself, especially later on when you go back and walk through your code with a sample input to see if it works.
Miscellaneous
What do I do if I get rejected?
Rejection happens. It’s an ugly reality of the interview process. If you can afford to, take a brief break from your studying so you can come back fresh.
The good news: You’re better at interviewing now. Sure, running practice questions is good preparation, but actually getting out there and failing some interviews is great preparation. Nothing approximates real interviews quite like other real interviews!
Reach out to the company and ask for feedback. Some companies can’t do this for legal reasons, but it never hurts to ask.
Keep in mind that rejection can happen for any number of reasons. There’s definitely an element of randomness. A lot of Google engineers feel there’s only a 50-50 chance they’d get an offer if they went through the interview process again.
Sometimes company priorities change, and they decide they need to slow down hiring. Sometimes you just get unlucky and get the interviewers who like to give low ratings.
There’s lots you can do to prepare, but there’s also lots that you can’t control. The best you can do is keep showing up and slowly getting better!
EDITS are always welcome!
submitted by Cyberrockz to u/Cyberrockz [link] [comments]


2020.10.26 16:39 Cyberrockz First Time Going Through Coding Interviews?

This post draws on my personal experiences and challenges over the past term at school, which I entered with hardly any knowledge of DSA (data structures and algorithms) and problem-solving strategies. As a self-taught programmer, I was a lot more familiar and comfortable with general programming, such as object-oriented programming, than with the problem-solving skills required in DSA questions.
This post reflects my journey throughout the term and the resources I turned to in order to quickly improve for my coding interview.
Here're some common questions and answers
What's the interview process like at a tech company?
Good question. It's actually pretty different from most other companies.

(What It's Like To Interview For A Coding Job

First time interviewing for a tech job? Not sure what to expect? This article is for you.

Here are the usual steps:

  1. First, you’ll do a non-technical phone screen.
  2. Then, you’ll do one or a few technical phone interviews.
  3. Finally, the last step is an onsite interview.
Some companies also throw in a take-home code test—sometimes before the technical phone interviews, sometimes after.
Let’s walk through each of these steps.

The non-technical phone screen

This first step is a quick call with a recruiter—usually just 10–20 minutes. It's very casual.
Don’t expect technical questions. The recruiter probably won’t be a programmer.
The main goal is to gather info about your job search. Stuff like:

  1. Your timeline. Do you need to sign an offer in the next week? Or are you trying to start your new job in three months?
  2. What’s most important to you in your next job. Great team? Flexible hours? Interesting technical challenges? Room to grow into a more senior role?
  3. What stuff you’re most interested in working on. Front end? Back end? Machine learning?
Be honest about all this stuff—that’ll make it easier for the recruiter to get you what you want.
One exception to that rule: If the recruiter asks you about your salary expectations on this call, best not to answer. Just say you’d rather talk about compensation after figuring out if you and the company are a good fit. This’ll put you in a better negotiating position later on.

The technical phone interview(s)

The next step is usually one or more hour-long technical phone interviews.
Your interviewer will call you on the phone or tell you to join them on Skype or Google Hangouts. Make sure you can take the interview in a quiet place with a great internet connection. Consider grabbing a set of headphones with a good microphone or a bluetooth earpiece. Always test your hardware beforehand!
The interviewer will want to watch you code in real time. Usually that means using a web-based code editor like Coderpad or collabedit. Run some practice problems in these tools ahead of time, to get used to them. Some companies will just ask you to share your screen through Google Hangouts or Skype.
Turn off notifications on your computer before you get started—especially if you’re sharing your screen!
Technical phone interviews usually have three parts:

  1. Beginning chitchat (5–10 minutes)
  2. Technical challenges (30–50 minutes)
  3. Your turn to ask questions (5–10 minutes)
The beginning chitchat is half just to help your relax, and half actually part of the interview. The interviewer might ask some open-ended questions like:

  1. Tell me about yourself.
  2. Tell me about something you’ve built that you’re particularly proud of.
  3. I see this project listed on your resume—tell me more about that.
You should be able to talk at length about the major projects listed on your resume. What went well? What didn’t? How would you do things differently now?
Then come the technical challenges—the real meet of the interview. You’ll spend most of the interview on this. You might get one long question, or several shorter ones.
What kind of questions can you expect? It depends.
Startups tend to ask questions aimed towards building or debugging code. (“Write a function that takes two rectangles and figures out if they overlap.”). They’ll care more about progress than perfection.
Larger companies will want to test your general know-how of data structures and algorithms (“Write a function that checks if a binary tree is ‘balanced’ in O(n)O(n) ↴ time.”). They’ll care more about how you solve and optimize a problem.
With these types of questions, the most important thing is to be communicating with your interviewer throughout. You'll want to "think out loud" as you work through the problem. For more info, check out our more detailed step-by-step tips for coding interviews.
If the role requires specific languages or frameworks, some companies will ask trivia-like questions (“In Python, what’s the ‘global interpreter lock’?”).
After the technical questions, your interviewer will open the floor for you to ask them questions. Take some time before the interview to comb through the company’s website. Think of a few specific questions about the company or the role. This can really make you stand out.
When you’re done, they should give you a timeframe on when you’ll hear about next steps. If all went well, you’ll either get asked to do another phone interview, or you’ll be invited to their offices for an onsite.

The onsite interview

An onsite interview happens in person, at the company’s office. If you’re not local, it’s common for companies to pay for a flight and hotel room for you.
The onsite usually consists of 2–6 individual, one-on-one technical interviews (usually in a small conference room). Each interview will be about an hour and have the same basic form as a phone screen—technical questions, bookended by some chitchat at the beginning and a chance for you to ask questions at the end.
The major difference between onsite technical interviews and phone interviews though: you’ll be coding on a whiteboard.
This is awkward at first. No autocomplete, no debugging tools, no delete button…ugh. The good news is, after some practice you get used to it. Before your onsite, practice writing code on a whiteboard (in a pinch, a pencil and paper are fine). Some tips:

  1. Start in the top-most left corner of the whiteboard. This gives you the most room. You’ll need more space than you think.
  2. Leave a blank line between each line as you write your code. Makes it much easier to add things in later.
  3. Take an extra second to decide on your variable names. Don’t rush this part. It might seem like a waste of time, but using more descriptive variable names ultimately saves you time because it makes you less likely to get confused as you write the rest of your code.
If a technical phone interview is a sprint, an onsite is a marathon. The day can get really long. Best to keep it open—don’t make other plans for the afternoon or evening.
When things go well, you’ wrap-up by chatting with the CEO or some other director. This is half an interview, half the company trying to impress you. They may invite you to get drinks with the team after hours.
All told, a long day of onsite interviews could look something like this:

If they let you go after just a couple interviews, it’s usually a sign that they’re going to pass on you. That’s okay—it happens!
There are are a lot of easy things you can do the day before and morning of your interview to put yourself in the best possible mindset. Check out our piece on what to do in the 24 hours before your onsite coding interview.

The take-home code test

Code tests aren’t ubiquitous, but they seem to be gaining in popularity. They’re far more common at startups, or places where your ability to deliver right away is more important than your ability to grow.
You’ll receive a description of an app or service, a rough time constraint for writing your code, and a deadline for when to turn it in. The deadline is usually negotiable.
Here's an example problem:
Write a basic “To-Do” app. Unit test the core functionality. As a bonus, add a “reminders” feature. Try to spend no more than 8 hours on it, and send in what you have by Friday with a small write-up.
Take a crack at the “bonus” features if they include any. At the very least, write up how you would implement it.
If they’re hiring for people with knowledge of a particular framework, they might tell you what tech to use. Otherwise, it’ll be up to you. Use what you’re most comfortable with. You want this code to show you at your best.
Some places will offer to pay you for your time. It's rare, but some places will even invite you to work with them in their office for a few days, as a "trial.")
Do I need to know this "big O" stuff?
Big O notation is the language we use for talking about the efficiency of data structures and algorithms.
Will it come up in your interviews? Well, it depends. There are different types of interviews.
There’s the classic algorithmic coding interview, sometimes called the “Google-style whiteboard interview.” It’s focused on data structures and algorithms (queues and stacks, binary search, etc).
That’s what our full course prepares you for. It's how the big players interview. Google, Facebook, Amazon, Microsoft, Oracle, LinkedIn, etc.
For startups and smaller shops, it’s a mixed bag. Most will ask at least a few algorithmic questions. But they might also include some role-specific stuff, like Java questions or SQL questions for a backend web engineer. They’ll be especially interested in your ability to ship code without much direction. You might end up doing a code test or pair-programming exercise instead of a whiteboarding session.
To make sure you study for the right stuff, you should ask your recruiter what to expect. Send an email with a question like, “Is this interview going to cover data structures and algorithms? Or will it be more focused around coding in X language.” They’ll be happy to tell you.
If you've never learned about data structures and algorithms, or you're feeling a little rusty, check out our Intuitive Guide to Data Structures and Algorithms.
Which programming language should I use?
Companies usually let you choose, in which case you should use your most comfortable language. If you know a bunch of languages, prefer one that lets you express more with fewer characters and fewer lines of code, like Python or Ruby. It keeps your whiteboard cleaner.
Try to stick with the same language for the whole interview, but sometimes you might want to switch languages for a question. E.g., processing a file line by line will be far easier in Python than in C++.
Sometimes, though, your interviewer will do this thing where they have a pet question that’s, for example, C-specific. If you list C on your resume, they’ll ask it.
So keep that in mind! If you’re not confident with a language, make that clear on your resume. Put your less-strong languages under a header like ‘Working Knowledge.’
What should I wear?
A good rule of thumb is to dress a tiny step above what people normally wear to the office. For most west coast tech companies, the standard digs are just jeans and a t-shirt. Ask your recruiter what the office is like if you’re worried about being too casual.
Should I send a thank-you note?
Thank-you notes are nice, but they aren’t really expected. Be casual if you send one. No need for a hand-calligraphed note on fancy stationery. Opt for a short email to your recruiter or the hiring manager. Thank them for helping you through the process, and ask them to relay your thanks to your interviewers.
1) Coding Interview Tips
How to get better at technical interviews without practicing
Chitchat like a pro.
Before diving into code, most interviewers like to chitchat about your background. They're looking for:

You should have at least one:

Nerd out about stuff. Show you're proud of what you've done, you're amped about what they're doing, and you have opinions about languages and workflows.
Communicate.
Once you get into the coding questions, communication is key. A candidate who needed some help along the way but communicated clearly can be even better than a candidate who breezed through the question.
Understand what kind of problem it is. There are two types of problems:

  1. Coding. The interviewer wants to see you write clean, efficient code for a problem.
  2. Chitchat. The interviewer just wants you to talk about something. These questions are often either (1) high-level system design ("How would you build a Twitter clone?") or (2) trivia ("What is hoisting in Javascript?"). Sometimes the trivia is a lead-in for a "real" question e.g., "How quickly can we sort a list of integers? Good, now suppose instead of integers we had . . ."
If you start writing code and the interviewer just wanted a quick chitchat answer before moving on to the "real" question, they'll get frustrated. Just ask, "Should we write code for this?"
Make it feel like you're on a team. The interviewer wants to know what it feels like to work through a problem with you, so make the interview feel collaborative. Use "we" instead of "I," as in, "If we did a breadth-first search we'd get an answer in O(n)O(n) time." If you get to choose between coding on paper and coding on a whiteboard, always choose the whiteboard. That way you'll be situated next to the interviewer, facing the problem (rather than across from her at a table).
Think out loud. Seriously. Say, "Let's try doing it this way—not sure yet if it'll work." If you're stuck, just say what you're thinking. Say what might work. Say what you thought could work and why it doesn't work. This also goes for trivial chitchat questions. When asked to explain Javascript closures, "It's something to do with scope and putting stuff in a function" will probably get you 90% credit.
Say you don't know. If you're touching on a fact (e.g., language-specific trivia, a hairy bit of runtime analysis), don't try to appear to know something you don't. Instead, say "I'm not sure, but I'd guess $thing, because...". The because can involve ruling out other options by showing they have nonsensical implications, or pulling examples from other languages or other problems.
Slow the eff down. Don't confidently blurt out an answer right away. If it's right you'll still have to explain it, and if it's wrong you'll seem reckless. You don't win anything for speed and you're more likely to annoy your interviewer by cutting her off or appearing to jump to conclusions.
Get unstuck.
Sometimes you'll get stuck. Relax. It doesn't mean you've failed. Keep in mind that the interviewer usually cares more about your ability to cleverly poke the problem from a few different angles than your ability to stumble into the correct answer. When hope seems lost, keep poking.
Draw pictures. Don't waste time trying to think in your head—think on the board. Draw a couple different test inputs. Draw how you would get the desired output by hand. Then think about translating your approach into code.
Solve a simpler version of the problem. Not sure how to find the 4th largest item in the set? Think about how to find the 1st largest item and see if you can adapt that approach.
Write a naive, inefficient solution and optimize it later. Use brute force. Do whatever it takes to get some kind of answer.
Think out loud more. Say what you know. Say what you thought might work and why it won't work. You might realize it actually does work, or a modified version does. Or you might get a hint.
Wait for a hint. Don't stare at your interviewer expectantly, but do take a brief second to "think"—your interviewer might have already decided to give you a hint and is just waiting to avoid interrupting.
Think about the bounds on space and runtime. If you're not sure if you can optimize your solution, think about it out loud. For example:

Get your thoughts down.
It's easy to trip over yourself. Focus on getting your thoughts down first and worry about the details at the end.
Call a helper function and keep moving. If you can't immediately think of how to implement some part of your algorithm, big or small, just skip over it. Write a call to a reasonably-named helper function, say "this will do X" and keep going. If the helper function is trivial, you might even get away with never implementing it.
Don't worry about syntax. Just breeze through it. Revert to English if you have to. Just say you'll get back to it.
Leave yourself plenty of room. You may need to add code or notes in between lines later. Start at the top of the board and leave a blank line between each line.
Save off-by-one checking for the end. Don't worry about whether your for loop should have "<<" or "<=<=." Write a checkmark to remind yourself to check it at the end. Just get the general algorithm down.
Use descriptive variable names. This will take time, but it will prevent you from losing track of what your code is doing. Use names_to_phone_numbers instead of nums. Imply the type in the name. Functions returning booleans should start with "is_*". Vars that hold a list should end with "s." Choose standards that make sense to you and stick with them.
Clean up when you're done.
Walk through your solution by hand, out loud, with an example input. Actually write down what values the variables hold as the program is running—you don't win any brownie points for doing it in your head. This'll help you find bugs and clear up confusion your interviewer might have about what you're doing.
Look for off-by-one errors. Should your for loop use a "<=<=" instead of a "<<"?
Test edge cases. These might include empty sets, single-item sets, or negative numbers. Bonus: mention unit tests!
Don't be boring. Some interviewers won't care about these cleanup steps. If you're unsure, say something like, "Then I'd usually check the code against some edge cases—should we do that next?"
Practice.
In the end, there's no substitute for running practice questions.
Actually write code with pen and paper. Be honest with yourself. It'll probably feel awkward at first. Good. You want to get over that awkwardness now so you're not fumbling when it's time for the real interview.

2) Tricks For Getting Unstuck During a Coding Interview
Getting stuck during a coding interview is rough.
If you weren’t in an interview, you might take a break or ask Google for help. But the clock is ticking, and you don’t have Google.
You just have an empty whiteboard, a smelly marker, and an interviewer who’s looking at you expectantly. And all you can think about is how stuck you are.
You need a lifeline for these moments—like a little box that says “In Case of Emergency, Break Glass.”
Inside that glass box? A list of tricks for getting unstuck. Here’s that list of tricks.
When you’re stuck on getting started
1) Write a sample input on the whiteboard and turn it into the correct output "by hand." Notice the process you use. Look for patterns, and think about how to implement your process in code.
Trying to reverse a string? Write “hello” on the board. Reverse it “by hand”—draw arrows from each character’s current position to its desired position.
Notice the pattern: it looks like we’re swapping pairs of characters, starting from the outside and moving in. Now we’re halfway to an algorithm.
2) Solve a simpler version of the problem. Remove or simplify one of the requirements of the problem. Once you have a solution, see if you can adapt that approach for the original question.
Trying to find the k-largest element in a set? Walk through finding the largest element, then the second largest, then the third largest. Generalizing from there to find the k-largest isn’t so bad.
3) Start with an inefficient solution. Even if it feels stupidly inefficient, it’s often helpful to start with something that’ll return the right answer. From there, you just have to optimize your solution. Explain to your interviewer that this is only your first idea, and that you suspect there are faster solutions.
Suppose you were given two lists of sorted numbers and asked to find the median of both lists combined. It’s messy, but you could simply:

  1. Concatenate the arrays together into a new array.
  2. Sort the new array.
  3. Return the value at the middle index.
Notice that you could’ve also arrived at this algorithm by using trick (2): Solve a simpler version of the problem. “How would I find the median of one sorted list of numbers? Just grab the item at the middle index. Now, can I adapt that approach for getting the median of two sorted lists?”
When you’re stuck on finding optimizations
1) Look for repeat work. If your current solution goes through the same data multiple times, you’re doing unnecessary repeat work. See if you can save time by looking through the data just once.
Say that inside one of your loops, there’s a brute-force operation to find an element in an array. You’re repeatedly looking through items that you don’t have to. Instead, you could convert the array to a lookup table to dramatically improve your runtime.
2) Look for hints in the specifics of the problem. Is the input array sorted? Is the binary tree balanced? Details like this can carry huge hints about the solution. If it didn’t matter, your interviewer wouldn’t have brought it up. It’s a strong sign that the best solution to the problem exploits it.
Suppose you’re asked to find the first occurrence of a number in a sorted array. The fact that the array is sorted is a strong hint—take advantage of that fact by using a binary search.

Sometimes interviewers leave the question deliberately vague because they want you to ask questions to unearth these important tidbits of context. So ask some questions at the beginning of the problem.
3) Throw some data structures at the problem. Can you save time by using the fast lookups of a hash table? Can you express the relationships between data points as a graph? Look at the requirements of the problem and ask yourself if there’s a data structure that has those properties.
4) Establish bounds on space and runtime. Think out loud about the parameters of the problem. Try to get a sense for how fast your algorithm could possibly be:

When All Else Fails
1) Make it clear where you are. State what you know, what you’re trying to do, and highlight the gap between the two. The clearer you are in expressing exactly where you’re stuck, the easier it is for your interviewer to help you.
2) Pay attention to your interviewer. If she asks a question about something you just said, there’s probably a hint buried in there. Don’t worry about losing your train of thought—drop what you’re doing and dig into her question.
Relax. You’re supposed to get stuck.
Interviewers choose hard problems on purpose. They want to see how you poke at a problem you don’t immediately know how to solve.
Seriously. If you don’t get stuck and just breeze through the problem, your interviewer’s evaluation might just say “Didn’t get a good read on candidate’s problem-solving process—maybe she’d already seen this interview question before?”
On the other hand, if you do get stuck, use one of these tricks to get unstuck, and communicate clearly with your interviewer throughout...that’s how you get an evaluation like, “Great problem-solving skills. Hire.”

3) Fixing Impostor Syndrome in Coding Interviews
“It's a fluke that I got this job interview...”
“I studied for weeks, but I’m still not prepared...”
“I’m not actually good at this. They’re going to see right through me...”
If any of these thoughts resonate with you, you're not alone. They are so common they have a name: impostor syndrome.
It’s that feeling like you’re on the verge of being exposed for what you really are—an impostor. A fraud.
Impostor syndrome is like kryptonite to coding interviews. It makes you give up and go silent.
You might stop asking clarifying questions because you’re afraid they’ll sound too basic. Or you might neglect to think out loud at the whiteboard, fearing you’ll say something wrong and sound incompetent.
You know you should speak up, but the fear of looking like an impostor makes that really, really hard.
Here’s the good news: you’re not an impostor. You just feel like an impostor because of some common cognitive biases about learning and knowledge.
Once you understand these cognitive biases—where they come from and how they work—you can slowly fix them. You can quiet your worries about being an impostor and keep those negative thoughts from affecting your interviews.

Everything you could know

Here’s how impostor syndrome works.
Software engineering is a massive field. There’s a huge universe of things you could know. Huge.
In comparison to the vast world of things you could know, the stuff you actually know is just a tiny sliver:
That’s the first problem. It feels like you don’t really know that much, because you only know a tiny sliver of all the stuff there is to know.

The expanding universe

It gets worse: counterintuitively, as you learn more, your sliver of knowledge feels like it's shrinking.
That's because you brush up against more and more things you don’t know yet. Whole disciplines like machine learning, theory of computation, and embedded systems. Things you can't just pick up in an afternoon. Heavy bodies of knowledge that take months to understand.
So the universe of things you could know seems to keep expanding faster and faster—much faster than your tiny sliver of knowledge is growing. It feels like you'll never be able to keep up.

What everyone else knows

Here's another common cognitive bias: we assume that because something is easy for us, it must be easy for everyone else. So when we look at our own skills, we assume they're not unique. But when we look at other people's skills, we notice the skills they have that we don't have.
The result? We think everyone’s knowledge is a superset of our own:
This makes us feel like everyone else is ahead of us. Like we're always a step behind.
But the truth is more like this:
There's a whole area of stuff you know that neither Aysha nor Bruno knows. An area you're probably blind to, because you're so focused on the stuff you don't know.

We’ve all had flashes of realizing this. For me, it was seeing the back end code wizard on my team—the one that always made me feel like an impostor—spend an hour trying to center an image on a webpage.

It's a problem of focus

Focusing on what you don't know causes you to underestimate what you do know. And that's what causes impostor syndrome.
By looking at the vast (and expanding) universe of things you could know, you feel like you hardly know anything.
And by looking at what Aysha and Bruno know that you don't know, you feel like you're a step behind.
And interviews make you really focus on what you don't know. You focus on what could go wrong. The knowledge gaps your interviewers might find. The questions you might not know how to answer.
But remember:
Just because Aysha and Bruno know some things you don't know, doesn't mean you don't also know things Aysha and Bruno don't know.
And more importantly, everyone's body of knowledge is just a teeny-tiny sliver of everything they could learn. We all have gaps in our knowledge. We all have interview questions we won't be able to answer.
You're not a step behind. You just have a lot of stuff you don't know yet. Just like everyone else.

4) The 24 Hours Before Your Interview

Feeling anxious? That’s normal. Your body is telling you you’re about to do something that matters.

The twenty-four hours before your onsite are about finding ways to maximize your performance. Ideally, you wanna be having one of those days, where elegant code flows effortlessly from your fingertips, and bugs dare not speak your name for fear you'll squash them.
You need to get your mind and body in The Zone™ before you interview, and we've got some simple suggestions to help.
5) Why You're Hitting Dead Ends In Whiteboard Interviews

The coding interview is like a maze

Listening vs. holding your train of thought

Finally! After a while of shooting in the dark and frantically fiddling with sample inputs on the whiteboard, you've came up with an algorithm for solving the coding question your interviewer gave you.
Whew. Such a relief to have a clear path forward. To not be flailing anymore.
Now you're cruising, getting ready to code up your solution.
When suddenly, your interviewer throws you a curve ball.
"What if we thought of the problem this way?"
You feel a tension we've all felt during the coding interview:
"Try to listen to what they're saying...but don't lose your train of thought...ugh, I can't do both!"
This is a make-or-break moment in the coding interview. And so many people get it wrong.
Most candidates end up only half understanding what their interviewer is saying. Because they're only half listening. Because they're desperately clinging to their train of thought.
And it's easy to see why. For many of us, completely losing track of what we're doing is one of our biggest coding interview fears. So we devote half of our mental energy to clinging to our train of thought.
To understand why that's so wrong, we need to understand the difference between what we see during the coding interview and what our interviewer sees.

The programming interview maze

Working on a coding interview question is like walking through a giant maze.
You don't know anything about the shape of the maze until you start wandering around it. You might know vaguely where the solution is, but you don't know how to get there.
As you wander through the maze, you might find a promising path (an approach, a way to break down the problem). You might follow that path for a bit.
Suddenly, your interviewer suggests a different path:
But from what you can see so far of the maze, your approach has already gotten you halfway there! Losing your place on your current path would mean a huge step backwards. Or so it seems.
That's why people hold onto their train of thought instead of listening to their interviewer. Because from what they can see, it looks like they're getting somewhere!
But here's the thing: your interviewer knows the whole maze. They've asked this question 100 times.

I'm not exaggerating: if you interview candidates for a year, you can easily end up asking the same question over 100 times.
So if your interviewer is suggesting a certain path, you can bet it leads to an answer.
And your seemingly great path? There's probably a dead end just ahead that you haven't seen yet:
Or it could just be a much longer route to a solution than you think it is. That actually happens pretty often—there's an answer there, but it's more complicated than you think.

Hitting a dead end is okay. Failing to listen is not.

Your interviewer probably won't fault you for going down the wrong path at first. They've seen really smart engineers do the same thing. They understand it's because you only have a partial view of the maze.
They might have let you go down the wrong path for a bit to see if you could keep your thinking organized without help. But now they want to rush you through the part where you discover the dead end and double back. Not because they don't believe you can manage it yourself. But because they want to make sure you have enough time to finish the question.
But here's something they will fault you for: failing to listen to them. Nobody wants to work with an engineer who doesn't listen.
So when you find yourself in that crucial coding interview moment, when you're torn between holding your train of thought and considering the idea your interviewer is suggesting...remember this:
Listening to your interviewer is the most important thing.
Take what they're saying and run with it. Think of the next steps that follow from what they're saying.
Even if it means completely leaving behind the path you were on. Trust the route your interviewer is pointing you down.
Because they can see the whole maze.
6) How To Get The Most Out Of Your Coding Interview Practice Sessions
When you start practicing for coding interviews, there’s a lot to cover. You’ll naturally wanna brush up on technical questions. But how you practice those questions will make a big difference in how well you’re prepared.
Here’re a few tips to make sure you get the most out of your practice sessions.
Track your weak spots
One of the hardest parts of practicing is knowing what to practice. Tracking what you struggle with helps answer that question.
So grab a fresh notebook. After each question, look back and ask yourself, “What did I get wrong about this problem at first?” Take the time to write down one or two things you got stuck on, and what helped you figure them out. Compare these notes to our tips for getting unstuck.
After each full practice session, read through your entire running list. Read it at the beginning of each practice session too. This’ll add a nice layer of rigor to your practice, so you’re really internalizing the lessons you’re learning.
Use an actual whiteboard
Coding on a whiteboard is awkward at first. You have to write out every single character, and you can’t easily insert or delete blocks of code.
Use your practice sessions to iron out that awkwardness. Run a few problems on a piece of paper or, if you can, a real whiteboard. A few helpful tips for handwriting code:

Set a timer
Get a feel for the time pressure of an actual interview. You should be able to finish a problem in 30–45 minutes, including debugging your code at the end.
If you’re just starting out and the timer adds too much stress, put this technique on the shelf. Add it in later as you start to get more comfortable with solving problems.
Think out loud
Like writing code on a whiteboard, this is an acquired skill. It feels awkward at first. But your interviewer will expect you to think out loud during the interview, so you gotta power through that awkwardness.
A good trick to get used to talking out loud: Grab a buddy. Another engineer would be great, but you can also do this with a non-technical friend.
Have your buddy sit in while you talk through a problem. Better yet—try loading up one of our questions on an iPad and giving that to your buddy to use as a script!
Set aside a specific time of day to practice.
Give yourself an hour each day to practice. Commit to practicing around the same time, like after you eat dinner. This helps you form a stickier habit of practicing.
Prefer small, daily doses of practice to doing big cram sessions every once in a while. Distributing your practice sessions helps you learn more with less time and effort in the long run.
part -2 will be upcoming in another post !
submitted by Cyberrockz to u/Cyberrockz [link] [comments]


2020.10.26 15:29 hilomrm Maritime Risk Management services Greece

We Are: HiLo is the only data-driven risk management company in the world helping the shipping industry predict and prevent catastrophes. The company was founded by Shell Shipping, Maritime Maersk Tankers A/S, and Lloyd’s Register Consulting in April 2018. At HiLo, we devise concrete solutions to mitigate the risks involved in shipping by using day-to-day data collected internally by shipping companies. Our risk analytics use predictive modelling to identify which low-level incidents need immediate attention to safeguard shipping companies from potential high impact disasters.
HiLo uses a data-based statistical model to deliver security to seafarers through its Maritime Industry Knowledge Centre. The database was created by Maritime experts and developed by HSSE professionals by analysing every cause and effect relationship to ensure the events line up with existing shipping experience. The system works to build a network of interconnected events—from daily warning signals to high impact incidents.
We have analysed risks for approximately 4800 ships and 150,000 events from 2016 to 2020. Our basic agenda is to aid the shipping industry in preventing high impact, low-frequency events, avoiding fatalities, shielding assets, and saving cost.
Vision:- HiLo’s vision is to create the best quality information to reduce accidents for taking away the element of shock from the shipping industry.
Mission:- HiLo’s mission is to connect the whole maritime industry through data, from industry bodies to P&I Clubs and from manufacturers to the end-users - ship managers; and ensure mariners have the best guidance, the best equipment, and the best protection from hazardous situations.
Customer:- “HiLo is taking a leading role in using risk prediction to improve safety. It has our full support.", Peter Livanos, Chairman of GasLog
Functioning:- HiLo’s Maritime Industry Knowledge Centre provides well-analysed safety and security solutions that deliver step-by-step guides to avoid high impact events. The companies have access to the most accurate Maritime Safety Big Data Analytics by holding the predictive modelling tool on a secure portal.
The portal has an in-built feature to collect, compile, and standardise all the relevant data directly from the client’s system files. Upon analysis, the portal applies the industry-leading risk analysis program to highlight the highest risk incidents for a particular company, along with the complete HiLo Fleet.
HiLo is different:- Since HiLo is a unique service industry, there are no competitors yet.Hilo enjoys a monopoly as a risk predictive and prevention management company for the shipping industry in the world. The internal safety data is collected daily from the shipping companies for analysis. Our core strength is secured client data anonymity while enhancing maritime safety. Our data library focuses on every part of the industry, from micro to macro, leaving no information untouched.
Our wide range of data collection and predictive analysis is what makes us unique in this domain - currently 3500 ships (2200 tankers, 800 bulk carriers, and 500 container ships).
Feat:- The industry-leading predictive modelling has assisted in minimising the risk elements of the Maritime industry right from daily warning signals to undesired potentially fatal situations. The risk of lifeboat incidents has dropped by 72%, engine room fires by 65%, and bunker spill by 25% in the year 2017-18, making HiLo the go-to safety statistical model for the top 50 shipping companies in the world. The model works on investigating every aspect of safety for mariners - from incident reports to audits. While collecting the data leading to a more comprehensive solution, the risk factors involved are also taken into consideration without fail.
We have strengthened the safety process of seafarers with our data collection library - 20x more near-miss data, 5x more collision data, 3x more grounding data, 5x more lifeboat incident data, 30x more mooring equipment data, and 8x more flooding data.
Details for Greece are: Philip Nielsen Oriani House, 13 Papathanasiou str., Athens 190 02 Mobile: +30 6944 5717 00 Office: +30 211 118 1369 Email: p[email protected] Website- https://hilomrm.com/our-services/
submitted by hilomrm to u/hilomrm [link] [comments]


2020.10.26 12:09 InsiderMemeBot LEADERBOARD: Mon, Oct 26, 2020: 07:09 AM EDT

TOP TRADERS

##Overall Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score :------::-----:----- :------::-----:----- :------::-----:----- :------::-----:----- :------::-----:----- 1  u/Gasenos 225142 11 u/mistermuesli 38664 21 u/NovaAge 17100 31 u/Regis_Casillas 11815 41 u/multipurposeflame 8210 2 u/sponge_hitler 153590 12 u/Mugiwara_AF 38137 22 u/PosterQ 16599 32 u/CodyGriffin 11394 42 u/JetZflare25 7690 3 u/rad302 86964 13 u/BlitzTaco 37379 23 u/SubsubatomicGuy 16407 33 u/Zombiepixlz-gamr 10842 43 u/MemeCalendar 7448 4 u/chaosgiantmemes 82414 14 u/razhagever 30124 24 u/matuhx 15414 34 u/Olipop999 10430 44 u/FoxTrotPlays 6656 5 u/iamscythed 64008 15 u/Hangzhounike 26045 25 u/KushPatil 15164 35 u/2D_DoS 10252 45 u/aemanthefox 6397 6 u/3D_Guernsey 51861 16 u/CritzD 23428 26 u/dhtikna 14947 36 u/Allonsy_11 9493 46 u/ibwitmypigeons 6343 7 u/Useless_Archives 48050 17 u/Umber0010 23149 27 u/acidcomplex_ 14002 37 u/CyberDalek6401 9211 47 u/Zeetelli 6323 8 u/Doses_of_Happiness 46608 18 u/MyNameSpaghette 22185 28 u/ncroney12 13654 38 u/GnelforGnoblin 9175 48 u/myownwildthoughts 5846 9 u/pineapple_overlord 41846 19 u/rosesan 19065 29 u/occultmoon 13130 39 u/Plastic_Pinocchio 8824 49 u/Sonorational 5585

10 u/Ralle1998 40209 20 u/blaZikeN_257 17184 30 u/Kermit_Ur_Life 11992 40 u/NervigerWutbuerger 8689 50 u/Oxigenate 5327

Top Crafters

Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score
1  u/Gasenos 63474 11 u/Ralle1998 8085 21 u/GinjaNinjaYT 4706 31 u/NovaAge 3852 41 u/MrEpicXD 2803
2 u/rad302 25634 12 u/BlitzTaco 7525 22 u/CritzD 4700 32 u/Hammerman305 3529 42 u/MarioThePumer 2740
3 u/chaosgiantmemes 19480 13 u/MemeCalendar 7448 23 u/FoxTrotPlays 4619 33 u/superstonks 3513 43 u/ncroney12 2736
4 u/sponge_hitler 17624 14 u/mistermuesli 5901 24 u/rosesan 4473 34 u/c0mp0op3r 3495 44 u/Neoquem45_Yt 2734
5 u/pineapple_overlord 17501 15 u/Useless_Archives 5709 25 u/KushPatil 4284 35 u/PosterQ 3328 45 u/occultmoon 2690
6 u/iamscythed 14686 16 u/Sonorational 5502 26 u/blaZikeN_257 4252 36 u/CyberDalek6401 3314 46 u/Azuridus 2673
7 u/3D_Guernsey 11334 17 u/Umber0010 5498 27 u/matuhx 4170 37 u/Thecloud420 3175 47 u/KlerWatchCo 2657
8 u/Doses_of_Happiness 10636 18 u/Zombiepixlz-gamr 5425 28 u/_Open_Your_Mind_ 4148 38 u/MyNameSpaghette 3145 48 u/CrispyRoastedDuck 2501
9 u/Mugiwara_AF 9464 19 u/Hangzhounike 5211 29 u/JetZflare25 4041 39 u/dhtikna 3002 49 u/Delicious_Peters_III 2448
10 u/Allonsy_11 9141 20 u/acidcomplex_ 4752 30 u/CaesarWalinguini 3949 40 u/666thSuprisedPikachu 2828 50 u/Kermit_Ur_Life 2414

Top Distributors

Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score
1  u/Gasenos 161668 11 u/razhagever 30124 21 u/PosterQ 13271 31 u/Regis_Casillas 9430 41 u/myownwildthoughts 5846
2 u/sponge_hitler 135966 12 u/BlitzTaco 29854 22 u/NovaAge 13248 32 u/acidcomplex_ 9250 42 u/Zombiepixlz-gamr 5417
3 u/chaosgiantmemes 62934 13 u/Mugiwara_AF 28673 23 u/blaZikeN_257 12932 33 u/CodyGriffin 9097 43 u/anal__penetration 4824
4 u/rad302 61330 14 u/pineapple_overlord 24345 24 u/dhtikna 11945 34 u/Plastic_Pinocchio 8777 44 u/ibwitmypigeons 4590
5 u/iamscythed 49322 15 u/Hangzhounike 20834 25 u/matuhx 11244 35 u/2D_DoS 8172 45 u/Zeetelli 4512
6 u/Useless_Archives 42341 16 u/MyNameSpaghette 19040 26 u/ncroney12 10918 36 u/GnelforGnoblin 7325 46 u/Oxigenate 4261
7 u/3D_Guernsey 40527 17 u/CritzD 18728 27 u/KushPatil 10880 37 u/multipurposeflame 6604 47 u/CourierMTF 4032
8 u/Doses_of_Happiness 35972 18 u/Umber0010 17651 28 u/occultmoon 10440 38 u/aemanthefox 6396 48 u/Th3AlphaPooch 4007
9 u/mistermuesli 32763 19 u/SubsubatomicGuy 16407 29 u/Olipop999 10430 39 u/NervigerWutbuerger 6370 49 u/JetZflare25 3649
10 u/Ralle1998 32124 20 u/rosesan 14592 30 u/Kermit_Ur_Life 9578 40 u/CyberDalek6401 5897 50 u/Some_dumb_mexican 3512

TOP POSTS

Templates Examples
Yesterday
1: Make this a meme 1: [No Data](No Data)
    Author: u/DPussyDestroyer     Author: u/No Data
    Score: 362     Score: 0
2: [No Data](No Data) 2: [No Data](No Data)
    Author: u/No Data     Author: u/No Data
    Score: 0     Score: 0
3: [No Data](No Data) 3: [No Data](No Data)
    Author: u/No Data     Author: u/No Data
    Score: 0     Score: 0
 
This week
1: Smirking cat template(pls use) 1: Found a possible good template
    Author: u/TriPpycheesE__     Author: u/Mugiwara_AF
    Score: 805     Score: 29363
2: I found this image and saw potential. 2: You can't hide from buff bird.
    Author: u/DrJimMBear     Author: u/Darthvegan66
    Score: 726     Score: 50
3: Playing tumble tower (Jenga) 3: We love you even if you are stupid
    Author: u/Mugiwara_AF     Author: u/og-lollercopter
    Score: 723     Score: 43
 
This month
1: Negative thoughts corrected by a friend 1: Found a possible good template
    Author: u/KlerWatchCo     Author: u/Mugiwara_AF
    Score: 1070     Score: 29363
2: Steve in smash 2: Authorised Dealers describing your place on a waitlist
    Author: u/FeedTheMii     Author: u/KlerWatchCo
    Score: 1065     Score: 280
3: Apple watch from TechSupport saying "Fuck" 3: Please get a room that is not the one I’m in
    Author: u/deadface008     Author: u/JD_Justice
    Score: 974     Score: 134
 
This Year
1: New Sonic movie template 1: Let's spend some time together
    Author: u/Spudtastic-Spastic     Author: u/rad302
    Score: 1616     Score: 92780
2: An Upgrade 2: Lord of the rings
    Author: u/0Markus0     Author: u/rad302
    Score: 1533     Score: 60488
3: For singular tastes 3: Some told me to do it
    Author: u/African_Watersports     Author: u/Ralle1998
    Score: 1459     Score: 40154
 
All Time
1: New Sonic movie template 1: The gif that started it all
    Author: u/Spudtastic-Spastic     Author: u/Whymanwhy12
    Score: 1616     Score: 99404
2: Credit to u/mallow_dip 2: I once called Hulk Shrek.
    Author: u/Yemris     Author: u/Shiteingann
    Score: 1614     Score: 97200
3: An Upgrade 3: Let's spend some time together
    Author: u/0Markus0     Author: u/rad302
    Score: 1533     Score: 92780
submitted by InsiderMemeBot to InsiderMemeTrading [link] [comments]


2020.10.26 12:06 estoyloca43 Teams that overperformed or underperformed their xG by the largest margins in 19/20

*big five leagues only, data from FBref

Top 10 teams that outperformed their xG per game
  1. Dortmund: 2.47 (actual goals) vs. 1.74 (expected goals) per game
  2. Bayern Munich: 2.94 vs. 2.42 per game
  3. Barcelona: 2.26 vs. 1.75 per game
  4. Atalanta: 2.58 vs. 2.16 per game
  5. Tottenham: 1.61 vs. 1.21 per game
  6. Bordeaux: 1.43 vs. 1.06 per game
  7. Liverpool: 2.24 vs. 1.88 per game
  8. Sassuolo: 1.82 vs. 1.47 per game
  9. RB Leipzig: 2.38 vs. 2.08 per game
  10. Lazio: 2.08 vs. 1.79 per game

Top 10 teams that outperformed their xGA per game
  1. Freiburg: 1.38 (actual goals conceded) vs. 1.78 per game (expected goals conceded)
  2. Sheffield Utd: 1.03 vs. 1.26 per game
  3. Arsenal: 1.26 vs. 1.49 per game
  4. Athletic Club: 1.00 vs. 1.22 per game
  5. Dijon: 1.32 vs. 1.54 per game
  6. Levante: 1.39 vs. 1.60 per game
  7. Lazio: 1.11 vs. 1.30 per game
  8. Reims: 0.75 vs. 0.94 per game
  9. Rennes: 0.86 vs. 1.04 per game
  10. Liverpool: 0.87 vs. 1.05 per game

Top 10 teams that outperformed their xGDiff per game
  1. Dortmund: 1.26 (actual GDs) vs. 0.58 (expected GDs) per game
  2. Bayern Munich: 2.00 vs. 1.41 per game
  3. Freiburg: 0.03 vs. -0.56 per game
  4. Liverpool: 1.37 vs. 0.83 per game
  5. Tottenham: 0.37 vs. -0.16 per game
  6. Lazio: 0.97 vs. 0.49 per game
  7. Barcelona: 1.26 vs. 0.80 per game
  8. Arsenal: 0.21 vs. -0.19 per game
  9. Sassuolo: 0.16 vs. -0.22 per game 10. Parma: -0.03 vs. -0.41 per game
  10. Parma: -0.03 vs. -0.41 per game

Top 10 teams that underperformed their xG per game
  1. SPAL: 0.71 (actual goals) vs. 1.03 (expected goals) per game
  2. Norwich City: 0.68 vs. 1.00 per game
  3. Toulouse: 0.79 vs. 1.08 per game
  4. Watford: 0.95 vs. 1.19 per game
  5. Brescia: 0.92 vs. 1.12 per game
  6. Leganés: 0.79 vs. 0.98 per game
  7. Lille: 1.25 vs. 1.41 per game
  8. Espanyol: 0.71 vs. 0.87 per game
  9. Monaco: 1.57 vs. 1.71 per game
  10. Everton: 1.16 vs. 1.30 per game

Top 10 teams that underperformed their xGA per game
  1. Werder Bremen: 2.03 (actual goals conceded) vs. 1.41 (expected goals conceded) per game
  2. Amiens: 1.79 vs. 1.27 per game
  3. Köln: 2.03 vs. 1.51 per game
  4. Toulouse: 2.07 vs. 1.58 per game
  5. Chelsea: 1.42 vs. 1.00 per game
  6. Genoa: 1.92 vs. 1.57 per game
  7. Espanyol: 1.53 vs. 1.18 per game
  8. Saint-Étienne: 1.61 vs. 1.26 per game
  9. Norwich City: 1.97 vs. 1.63 per game
  10. Düsseldorf: 1.97 vs. 1.65 per game

Top 10 teams that underperformed their xGDiff per game
  1. Toulouse: -1.29 vs. -0.50 per game
  2. Norwich City: -1.29 vs. -0.63 per game
  3. Werder Bremen: -0.79 vs. -0.19 per game
  4. SPAL: -1.32 vs. -0.74 per game
  5. Espanyol: -0.82 vs. -0.31 per game
  6. Leganés: -0.55 vs. -0.05 per game
  7. Watford: -0.74 vs. -0.32 per game
  8. Köln: -0.53 vs. -0.13 per game
  9. Sampdoria: -0.45 vs. -0.06 per game
  10. Amiens: -0.68 vs. -0.31 per game
submitted by estoyloca43 to soccer [link] [comments]


2020.10.26 12:00 InsiderMemeBot-dev LEADERBOARD: Mon, Oct 26, 2020: 07:00 AM EDT

TOP TRADERS

##Overall Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score :------::-----:----- :------::-----:----- :------::-----:----- :------::-----:----- :------::-----:----- 1  u/sponge_hitler 82426 11 u/Morchel03 34883 21 u/Neyo708 19802 31 u/djnewton123 13762 41 u/Britisheagl 8869 2 u/Mussu007 81891 12 u/SiomarTehBeefalo 30445 22 u/Ryanrdc 15822 32 u/Edmenz 12027 42 u/BanditSlayer42 7755 3 u/TheSpookiestUser 73519 13 u/Jaredrap 28749 23 u/DankPinnaple 15205 33 u/AKushWarrior 11516 43 u/rad302 7618 4 u/InterracialMemeJob 67675 14 u/RoseBladePhantom 28442 24 u/mix_soup 15200 34 u/depressed_young_lad 11339 44 u/LimeGreenIndustries 7292 5 u/Saintrph 61613 15 u/Dawaitniggi 24331 25 u/Nathaniel__Bacon 15099 35 u/Tehwipez 11311 45 u/GnelforGnoblin 6669 6 u/SeaOdeEEE 52699 16 u/Svenwill 23536 26 u/HmanSupreme 15098 36 u/oroxoss 11164 46 u/Gorloftheinsatiable 6396 7 u/poopgoose1 50002 17 u/Kirk880 23200 27 u/Dane_Saint 15095 37 u/CaptainRadLad 9815 47 u/juanjocasamitjana 5655 8 u/HusseinRazak 46976 18 u/darthkers 22841 28 u/PokemonLegacy6 15053 38 u/Xyeeyx 9652 48 u/ninjabellybutt 5397 9 u/Useless_Archives 42986 19 u/Mono_KS 21194 29 u/quincepetchforth 14909 39 u/Holy_Hobo_ 9621 49 u/zJermando 5384

10 u/dingus_foringus 40851 20 u/jorgisgis 20431 30 u/A_BroadHumor 14541 40 u/Whymanwhy12 9045 50 u/Fleeling 5209

Top Crafters

Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score
1  u/Morchel03 30318 11 u/Dane_Saint 6426 21 u/Xyeeyx 4019 31 u/rad302 2949 41 u/Loopy_beetle 2215
2 u/Saintrph 26818 12 u/Jaredrap 6184 22 u/Neyo708 4013 32 u/ManHuntingMuffalo 2846 42 u/Whymanwhy12 1929
3 u/poopgoose1 25002 13 u/SiomarTehBeefalo 6094 23 u/zJermando 3619 33 u/TockLoxx 2787 43 u/Efficient_Half 1918
4 u/InterracialMemeJob 20977 14 u/RoseBladePhantom 5454 24 u/dingus_foringus 3462 34 u/djnewton123 2778 44 u/aValid_Username 1852
5 u/Mussu007 15605 15 u/Kirk880 4918 25 u/detroit_yeet 3328 35 u/zibbon50cal2 2648 45 u/istarxh 1849
6 u/TheSpookiestUser 13369 16 u/Dawaitniggi 4869 26 u/yeezus40 3219 36 u/fconyt 2547 46 u/Britisheagl 1847
7 u/Useless_Archives 10541 17 u/SeaOdeEEE 4842 27 u/Eze10gun 3086 37 u/Tehwipez 2541 47 u/Ryanrdc 1751
8 u/HusseinRazak 9397 18 u/PokemonLegacy6 4360 28 u/HmanSupreme 3030 38 u/Edmenz 2479 48 u/alice_right_foot-esq 1616
9 u/sponge_hitler 8592 19 u/Mono_KS 4249 29 u/quincepetchforth 2984 39 u/oroxoss 2470 49 u/BanditSlayer42 1554
10 u/Svenwill 6555 20 u/jorgisgis 4145 30 u/CaptainRadLad 2960 40 u/depressed_young_lad 2402 50 u/TomtheMemeKing 1535

Top Distributors

Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score
1  u/sponge_hitler 73834 11 u/SiomarTehBeefalo 24351 21 u/Nathaniel__Bacon 15099 31 u/Holy_Hobo_ 9608 41 u/LimeGreenIndustries 5759
2 u/Mussu007 66286 12 u/RoseBladePhantom 22988 22 u/mix_soup 14241 32 u/Edmenz 9548 42 u/Xyeeyx 5633
3 u/TheSpookiestUser 60150 13 u/darthkers 22841 23 u/DankPinnaple 14200 33 u/depressed_young_lad 8937 43 u/GnelforGnoblin 5330
4 u/SeaOdeEEE 47857 14 u/Jaredrap 22565 24 u/Ryanrdc 14071 34 u/Tehwipez 8770 44 u/Gorloftheinsatiable 5094
5 u/InterracialMemeJob 46698 15 u/Dawaitniggi 19462 25 u/A_BroadHumor 13268 35 u/oroxoss 8694 45 u/rad302 4669
6 u/HusseinRazak 37579 16 u/Kirk880 18282 26 u/HmanSupreme 12068 36 u/Dane_Saint 8669 46 u/Morchel03 4565
7 u/dingus_foringus 37389 17 u/Svenwill 16981 27 u/quincepetchforth 11925 37 u/Whymanwhy12 7116 47 u/ninjabellybutt 4284
8 u/Saintrph 34795 18 u/Mono_KS 16945 28 u/djnewton123 10984 38 u/Britisheagl 7022 48 u/juanjocasamitjana 4257
9 u/Useless_Archives 32445 19 u/jorgisgis 16286 29 u/AKushWarrior 10889 39 u/CaptainRadLad 6855 49 u/Fleeling 3852
10 u/poopgoose1 25000 20 u/Neyo708 15789 30 u/PokemonLegacy6 10693 40 u/BanditSlayer42 6201 50 u/SquishyR0b0 3800

TOP POSTS

Templates Examples
Yesterday
1: Example 1: [No Data](No Data)
    Author: u/Lil_KleinStein2     Author: u/No Data
    Score: 1     Score: 0
2: [No Data](No Data) 2: [No Data](No Data)
    Author: u/No Data     Author: u/No Data
    Score: 0     Score: 0
3: [No Data](No Data) 3: [No Data](No Data)
    Author: u/No Data     Author: u/No Data
    Score: 0     Score: 0
 
This week
1: Example 1: [No Data](No Data)
    Author: u/Lil_KleinStein2     Author: u/No Data
    Score: 1     Score: 0
2: [No Data](No Data) 2: [No Data](No Data)
    Author: u/No Data     Author: u/No Data
    Score: 0     Score: 0
3: [No Data](No Data) 3: [No Data](No Data)
    Author: u/No Data     Author: u/No Data
    Score: 0     Score: 0
 
This month
1: Example 1: [No Data](No Data)
    Author: u/Lil_KleinStein2     Author: u/No Data
    Score: 1     Score: 0
2: [No Data](No Data) 2: [No Data](No Data)
    Author: u/No Data     Author: u/No Data
    Score: 0     Score: 0
3: [No Data](No Data) 3: [No Data](No Data)
    Author: u/No Data     Author: u/No Data
    Score: 0     Score: 0
 
This Year
1: Here’s a Grinch facing the truth template 1: Effort is good
    Author: u/flameboy915     Author: u/Whymanwhy12
    Score: 812     Score: 99404
2: It knows what I want Gravity Falls template 2: Masturbation sense tingling
    Author: u/CaptainRadLad     Author: u/Saintrph
    Score: 724     Score: 58905
3: Spray painted Spongebob meme 3: Always be prepared
    Author: u/Morchel03     Author: u/TheSpookiestUser
    Score: 666     Score: 57919
 
All Time
1: Here’s a Grinch facing the truth template 1: Effort is good
    Author: u/flameboy915     Author: u/Whymanwhy12
    Score: 812     Score: 99404
2: It knows what I want Gravity Falls template 2: Masturbation sense tingling
    Author: u/CaptainRadLad     Author: u/Saintrph
    Score: 724     Score: 58905
3: Spray painted Spongebob meme 3: Always be prepared
    Author: u/Morchel03     Author: u/TheSpookiestUser
    Score: 666     Score: 57919
submitted by InsiderMemeBot-dev to InsiderMemeBot_Test [link] [comments]


2020.10.26 11:34 Reesj Battleground hero stats

HS replay is great place to get stas about battleground heroes. But unfortunetly, most of the data are behind a paywall subsciption. Even the hereos stats are only available for top 50% of player base only.
IS there any other site which give battle ground hero stats ? If not can some one post hero ranking for top 5% and top 20% please?
submitted by Reesj to hearthstone [link] [comments]


2020.10.26 08:23 Cicero1982 The Best and Most Profitable Information You will Ever Likely Receive in this Forum.

The Best and Most Profitable Information You will Ever Likely Receive in this Forum.
Warning: If you are not a reader you will not like this thread. But I promise you that you can profit from it!
———————————
I have been known to invest in a penny stock or two but my primary investment strategy is number 9 HERE. This strategy works because it accounts for the ebbs and flows of the market. So as long as you find a consistently profitable security that routinely beats earnings, is trading at a discount, has the potential for future growth, it generally works. I say “generally” simply to account for the economic conditions that have the tendency to ruin the party.
No matter what chart you look at they all rise and fall, rise and fall, and so on. This rise is created when you have more people buying a security than selling it. I say “people” but in reality the institutions control roughly 90% of the market and their algorithms control roughly 70-80% of the same market. However securities fall when you have more selling than buying. Certainly short interest plays a roll as well. If you get enough folks short selling into the red at massive quantities, it will drive the security down.
But let’s say for a moment that a security is trading slightly above book value per share (BVPS is the total value of the company decided by outstanding shares), it has had three consecutive quarters of good earnings, increasing overall revenue, a relatively low PE as compared to other companies in the sector, a debt to asset ratio of 0-75% (it is not necessarily bad to be higher pending the company is profiting from their debt driven investments), about 60% or more institutional investment, and the economic conditions are favorable (Note: you will rarely find the perfect company). If you’ve met these conditions you have likely found a security worth investing in. And if you see this as a good bet, chances are that institutions are tracking the same numbers. No matter what future earnings will bring you, chances are institutions will bet on future solid quarterly earnings. Please note that they often don’t bet just for the quarter, but for many quarters out.
These institutions cannot simply pump millions of $$ into a security. If they did they would pump it well beyond it’s fair value. And there are usually more than one institution in a stock. Institutions cater to customers and attempt to get the stock at the price their customers demand. These guys are in the profit business and they aren’t afraid to manipulate prices up and down. They’re called “market makers,” or “MM’s” for a reason! They make markets at a certain price. They are overwhelmingly responsible for the ebbs and flows of the market.
This is why when quarterly news is released that some of the more popular institutions are betting on a stock, the securities pump. The same can be said when securities fall after institutions minimize or exit a position.
So let’s say earnings have arrived and they’re great! Everyone is looking at a little known stock that meets all the aforementioned criteria. The stock pumps but after a while the buzz fades and the security drops. Indeed sometimes earnings are priced in and they drop immediately no matter how well they did. While you might move on and attempt to find something else, this is when I begin to take notice. Volume is low, the price is decreasing, but the fundamentals are strong! So while you’re out hunting for volume and chasing pumpers, I’m slowly averaging down on oversold but reliable losing stocks.
The market makers who control the security likely did a combination of two things. They either sold some calls and sold a part of their position driving the price down while profiting from the calls, or they opened a short position and drove the price down ... perhaps also after selling calls. Part of being a market maker is to keep the market stable. Market makers hate over pumped over valued securities. They like stability and consistency that they can profit off of time and time again.
You as a retail trader probably aren’t looking at the situation this way. You’re probably asking “What the hell!!?? Why isn’t this stock skyrocketing!!??” Well the answer is because they don’t want it to skyrocket.
So the stock dives and volume dries up until, in terms of valuation, the stock is at an irresistible entry point. This is market makers playing chicken with each other. Some will enter before the stock bottoms out. This may prevent the stock from fully bottoming out. Sometimes the stock gets so low below historical support that you begin to get uneasy. You shouldn’t pay any heed to this. If the fundamentals are strong, you will at least break even with patience. But if the stock looks irresistible after consistent earnings beats, a good relative BVPS, a low PE, and solid institutional investment, you can bet it will be irresistible to institutions as well.
Dealing with the massive amounts of money they are, institutions are slowly accumulating as the stock is diving. At the bottom they will accumulate more still. They’re in it for the long haul and they aren’t afraid to take a temporary loss. They know to accumulate shares they need to incentivize selling pressure and, as is said so often, “shake the weak hands.” It’s at this low volume moment you will notice that short interest that was high around 50-60% is drying up. This is them closing out their short position. This is where they judge the security so discounted that the risk of diving it further is not worth the reward. They cover and accumulate shares. They may even sell some puts as they do so. They know the stock is due for a reversal.
They not only know the stock is due for a reversal because it is relatively undervalued, but also because it is relatively oversold. The algorithms too will take note when a security is trading too far below the moving averages. The stock reverses, slow at first, and then others take note and rush in. Volume picks up. Perhaps a ratings agency upgraded the security or perhaps dividends are due soon. Perhaps good economic data comes out favorable to the sector. For whatever reason the market makers are no longer going to risk shorting the security. It rises.
The stock sometimes rises until it has reached a point where you have a few whales taking profit.... but not all. There may be a temporary lull in the pump but often it pumps further until the market makers or the algorithms understand the security to be outside the norms of the moving averages. In short the stock becomes overbought. The customers of the institutions or market makers like the stock, but they don’t like the price. It’s time to make a new market. They repeat this process.
This cycle is why you have sell offs a month before earnings, after earnings, and in between earnings. This cycle is also why you have pumps slightly before earnings, in between earnings and sometimes after earnings. Sure there are things that can screw up the cycle but for the most part the cycle always picks up where it left off. So as long as earnings aren’t devastating or insanely awesome, a stock might realize a small gap up or down, depending on the earnings, at best.
By understanding this cycle you as a retail trader can benefit much better than they can. You just need to know how to read the financials and the cycles. After all, they need to profit with millions of not billions. You need to profit with just thousands in your account.
So how do you take advantage of this cycle? Well first you find securities that are reliably profitable, have consistently good earnings, a relatively low P/E for their sector, decent BVPS for their sector, a solid EPS, and a bit of institutional investment. I use Webull’s and Yahoo finance’s financial data/statistics to determine this.
Next you need to set your alerts for when the security crosses a value of which it becomes attractive to you. Seriously, go to town! You’ll be surprised how many alerts you’ll get throughout the week. When you receive the alerts you should check to see that there isn’t any bad news and assure yourself that the market AND economic conditions are still favorable for the sector or industry.
Third you shouldn’t ever go all in at once. You should make a starter position and average down slowly every 1.5-3% the security drops. You should be excited the stock is selling for a cheaper price. Not anxious that you’re losing money.
Fourth, when the stock turns around you shouldn’t try to find the top. Neither should you try to nail the bottom. You would be surprised how far below support some market makers can tank a security. So as long as your analysis is sound you’ll profit ... and that should be enough. There is nothing wrong with 5-15%!!
You might additionally want to do what I do. If you judge your analysis to be sound and yet you’re experiencing a larger than expected sell off, notify others in this forum. Trust me they will thank you for it after they’ve realized a 10-15% gain. I’ve helped my buddies make thousands this way! I usually notify folks of such securities on twitter here: https://mobile.twitter.com/tradinganalysi2
Either way there are plenty of scanners resources and screeners that will help you find these securities.
The great part about this strategy is that you won’t mind bag holding because the security is reliable, at a value, and has a propensity for growth. The chances that you will at least break even is very high.
Nevertheless this advice is the difference between folks that lose money chasing hot securities and those that are consistently profitable. This may or may not work on your typical cheaply traded penny or micro-cap stock (More likely not) as they operate by a whole different set of rules and, well let’s face it, they aren’t profitable companies yet. But if you want penny stock-like gains with a fraction of the risk, this is the way to go! A little patience, resilience, and discipline can go a long way to your financial independence!
For more great stuff like this please feel free to enhance your education HERE
God Bless and Safe Trading!
Remember to always do your own DD and this investment strategy is not for everyone. I am not a certified nor licensed financial advisor but an amateur retail trader and investor just like most of you.
My record of picking stocks: HERE . HERE . HERE . HERE
AND HERE https://mobile.twitter.com/tradinganalysi2
TL;DR: I HIGHLY recommend you read it 🤣
submitted by Cicero1982 to pennystocks [link] [comments]


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submitted by kaylabelvyah to u/kaylabelvyah [link] [comments]


2020.10.26 02:17 Naitor295 Investing In Clean Energy ETFs - FAN, TAN, LIT

I made a small little post a few days ago on Clean Energy Index Funds. This one will focus on Specific Clean Energy ETFs. I hope this post helps people who are interested in this topic.
Before we go in, I'd like to share some potential Megatrends on Clean Energy:
  1. 50% of the world’s energy is predicted to come from solar and wind by 2050, 7x the percentage in 2015.
  2. $2T is the total investment needed by 2030 to implement government renewable energy targets.
  3. Renewables are set to represent ¾ of the $12T the world invests in new power technology through 2040.
(Source: https://www.ishares.com/us/literature/product-brief/ishares-megatrends-global-clean-energy-etf-product-brief-en-us.pdf)
The current general thesis for Clean Energy plays heavily with the concepts stated above along with others.
One note to address before we go in is that these funds are non-diversified: when you invest in these funds, you are SOLELY investing in Clean Energy. Do not confuse this with global diversification, these funds are very focused investments and they all have under 100 holdings
____________________________________________________________________________________________________________
The ETFs
First Trust Global Wind NRG ETF (FAN) - This one has the lowest ER out of three standing at 0.62%. FAN contains about 30 holdings, the top 10 holdings account for about 54.09%. This ETF is very globally diversified, the top 3 countries are Denmark (19.23%), Canada (18.05%), and Spain (14.40%) standing. The US comes in 4th place standing at 10.40% for anyone interested. This ETF tracks the ISE Clean Edge Global Wind Energy Index which is Market-Cap Weighted. The ETFs weighting consists of 66.67% 'Pure-Plays' (companies that provide goods and services exclusively to the wind energy industry) and 40% 'Diversified Category' (companies that are determined to be significant participants in the wind energy industry despite not being exclusive to such industry). Overall, this ETF focuses on the CORE components of Wind Energy.
Fact Sheet: https://www.ftportfolios.com/Common/ContentFileLoader.aspx?ContentGUID=7ed74027-1285-4def-88ac-2ac152007d7b
Invesco Solar ETF (TAN) - This one has the 2nd lowest ER out of the three standing at 0.71%. TAN contains about 27 holdings, the top 10 holdings account for about 63.62%. This ETF is globally diversified, the top 3 countries are The US (57.87%), Hong Kong (14.26%), and China (7.12%) This ETF tracks the MAC Global Solar NRG Index which is Market-Cap Weighted. Similar to FAN, this ETF also weighs itself through the concepts of 'Pure-Plays' (companies that provide goods and services exclusively to the solar energy industry) and 'Diversified Category' (companies that are determined to be significant participants in the solar energy industry despite not being exclusive to such industry), boosting weight for 'Pure-Plays' and underweighting 'Diversified Category.' Overall, this ETF focuses on the CORE components of Solar Energy.
Fact Sheet: https://www.invesco.com/us-rest/contentdetail contentId=025d7c23dbd92610VgnVCM1000006e36b50aRCRD&dnsName=us
Global X Lithium & Battery Tech ETF (LIT) - This one has the highest ER out of the three standing at 0.75%. LIT contains about 43 holdings, the top 10 holdings account for about 59.91%. This ETF is globally diversified, the top 3 countries are, similar to TAN, China (30.94%), The US (24.12%), and Hong Kong (13.22%). A lot of Chinese weight, please research this carefully. China is still considered an Emerging Market so this is a very unique weighting situation. Anyways, this ETF tracks the Solactive Global Lithium Index which is Market-Cap Weighted. This ETF is unique because it focuses on the Full Lithium Cycle which means it offers exposure to the Metal/Mining, Lithium Refining, and Battery Production Segments. This ETF is similar in some ways to Commodity Metal ETFs, keep this in mind if you plan on going further with this.
Fact Sheet: https://www.globalxetfs.com/content/files/LIT-factsheet.pdf (This Fact Sheet is 3 months old, it's outdated. Seek out a website such as ETF.Com for up to date information)
____________________________________________________________________________________________________________
What I provided is very brief. If you're serious about Clean Energy, you must read each ETFs fact sheet along with the prospectuses. This will educate you on the field more and provide more crucial data for each fund.
The main difference between each of these ETFs really comes down to the underlying holdings, sector allocations, and global diversification. Analyze your Risk Tolerance and Circle Of Competence in terms of holding/sectoglobality for each fund before making a decision.
Disclaimer: I am NOT a financial expert. You MUST do your own diligence -- this is ONLY for educational purposes.
- Naitor295
submitted by Naitor295 to StockMarket [link] [comments]


2020.10.26 02:17 Naitor295 Investing In Specific Clean Energy ETFs - FAN, TAN, LIT

I made a small little post a few days ago on Clean Energy Index Funds. This one will focus on Specific Clean Energy ETFs. I hope this post helps people who are interested in this topic.
Before we go in, I'd like to share some potential Megatrends on Clean Energy:
  1. 50% of the world’s energy is predicted to come from solar and wind by 2050, 7x the percentage in 2015.
  2. $2T is the total investment needed by 2030 to implement government renewable energy targets.
  3. Renewables are set to represent ¾ of the $12T the world invests in new power technology through 2040.
(Source: https://www.ishares.com/us/literature/product-brief/ishares-megatrends-global-clean-energy-etf-product-brief-en-us.pdf)
The current general thesis for Clean Energy plays heavily with the concepts stated above along with others.
One note to address before we go in is that these funds are non-diversified: when you invest in these funds, you are SOLELY investing in Clean Energy. Do not confuse this with global diversification, these funds are very focused investments and they all have under 100 holdings
____________________________________________________________________________________________________________
The ETFs
First Trust Global Wind NRG ETF (FAN) - This one has the lowest ER out of three standing at 0.62%. FAN contains about 30 holdings, the top 10 holdings account for about 54.09%. This ETF is very globally diversified, the top 3 countries are Denmark (19.23%), Canada (18.05%), and Spain (14.40%) standing. The US comes in 4th place standing at 10.40% for anyone interested. This ETF tracks the ISE Clean Edge Global Wind Energy Index which is Market-Cap Weighted. The ETFs weighting consists of 66.67% 'Pure-Plays' (companies that provide goods and services exclusively to the wind energy industry) and 40% 'Diversified Category' (companies that are determined to be significant participants in the wind energy industry despite not being exclusive to such industry). Overall, this ETF focuses on the CORE components of Wind Energy.
Fact Sheet: https://www.ftportfolios.com/Common/ContentFileLoader.aspx?ContentGUID=7ed74027-1285-4def-88ac-2ac152007d7b
Invesco Solar ETF (TAN) - This one has the 2nd lowest ER out of the three standing at 0.71%. TAN contains about 27 holdings, the top 10 holdings account for about 63.62%. This ETF is globally diversified, the top 3 countries are The US (57.87%), Hong Kong (14.26%), and China (7.12%) This ETF tracks the MAC Global Solar NRG Index which is Market-Cap Weighted. Similar to FAN, this ETF also weighs itself through the concepts of 'Pure-Plays' (companies that provide goods and services exclusively to the solar energy industry) and 'Diversified Category' (companies that are determined to be significant participants in the solar energy industry despite not being exclusive to such industry), boosting weight for 'Pure-Plays' and underweighting 'Diversified Category.' Overall, this ETF focuses on the CORE components of Solar Energy.
Fact Sheet: https://www.invesco.com/us-rest/contentdetail contentId=025d7c23dbd92610VgnVCM1000006e36b50aRCRD&dnsName=us
Global X Lithium & Battery Tech ETF (LIT) - This one has the highest ER out of the three standing at 0.75%. LIT contains about 43 holdings, the top 10 holdings account for about 59.91%. This ETF is globally diversified, the top 3 countries are, similar to TAN, China (30.94%), The US (24.12%), and Hong Kong (13.22%). A lot of Chinese weight, please research this carefully. China is still considered an Emerging Market so this is a very unique weighting situation. Anyways, this ETF tracks the Solactive Global Lithium Index which is Market-Cap Weighted. This ETF is unique because it focuses on the Full Lithium Cycle which means it offers exposure to the Metal/Mining, Lithium Refining, and Battery Production Segments. This ETF is similar in some ways to Commodity Metal ETFs, keep this in mind if you plan on going further with this.
Fact Sheet: https://www.globalxetfs.com/content/files/LIT-factsheet.pdf (This Fact Sheet is 3 months old, it's outdated. Seek out a website such as ETF.Com for up to date information)
____________________________________________________________________________________________________________
What I provided is very brief. If you're serious about Clean Energy, you must read each ETFs fact sheet along with the prospectuses. This will educate you on the field more and provide more crucial data for each fund.
The main difference between each of these ETFs really comes down to the underlying holdings, sector allocations, and global diversification. Analyze your Risk Tolerance and Circle Of Competence in terms of holding/sectoglobality for each fund before making a decision.
Disclaimer: I am NOT a financial expert. You MUST do your own diligence -- this is ONLY for educational purposes.
- Naitor295
submitted by Naitor295 to stocks [link] [comments]


2020.10.26 02:16 Naitor295 Investing In Specific Clean Energy ETFs - FAN, TAN, LIT

I made a small little post a few days ago on Clean Energy Index Funds. This one will focus on Specific Clean Energy ETFs. I hope this post helps people who are interested in this topic.
Before we go in, I'd like to share some potential Megatrends on Clean Energy:
  1. 50% of the world’s energy is predicted to come from solar and wind by 2050, 7x the percentage in 2015.
  2. $2T is the total investment needed by 2030 to implement government renewable energy targets.
  3. Renewables are set to represent ¾ of the $12T the world invests in new power technology through 2040.
(Source: https://www.ishares.com/us/literature/product-brief/ishares-megatrends-global-clean-energy-etf-product-brief-en-us.pdf)
The current general thesis for Clean Energy plays heavily with the concepts stated above along with others.
One note to address before we go in is that these funds are non-diversified: when you invest in these funds, you are SOLELY investing in Clean Energy. Do not confuse this with global diversification, these funds are very focused investments and they all have under 100 holdings
____________________________________________________________________________________________________________
The ETFs
First Trust Global Wind NRG ETF (FAN) - This one has the lowest ER out of three standing at 0.62%. FAN contains about 30 holdings, the top 10 holdings account for about 54.09%. This ETF is very globally diversified, the top 3 countries are Denmark (19.23%), Canada (18.05%), and Spain (14.40%) standing. The US comes in 4th place standing at 10.40% for anyone interested. This ETF tracks the ISE Clean Edge Global Wind Energy Index which is Market-Cap Weighted. The ETFs weighting consists of 66.67% 'Pure-Plays' (companies that provide goods and services exclusively to the wind energy industry) and 40% 'Diversified Category' (companies that are determined to be significant participants in the wind energy industry despite not being exclusive to such industry). Overall, this ETF focuses on the CORE components of Wind Energy.
Fact Sheet: https://www.ftportfolios.com/Common/ContentFileLoader.aspx?ContentGUID=7ed74027-1285-4def-88ac-2ac152007d7b
Invesco Solar ETF (TAN) - This one has the 2nd lowest ER out of the three standing at 0.71%. TAN contains about 27 holdings, the top 10 holdings account for about 63.62%. This ETF is globally diversified, the top 3 countries are The US (57.87%), Hong Kong (14.26%), and China (7.12%) This ETF tracks the MAC Global Solar NRG Index which is Market-Cap Weighted. Similar to FAN, this ETF also weighs itself through the concepts of 'Pure-Plays' (companies that provide goods and services exclusively to the solar energy industry) and 'Diversified Category' (companies that are determined to be significant participants in the solar energy industry despite not being exclusive to such industry), boosting weight for 'Pure-Plays' and underweighting 'Diversified Category.' Overall, this ETF focuses on the CORE components of Solar Energy.
Fact Sheet: https://www.invesco.com/us-rest/contentdetail contentId=025d7c23dbd92610VgnVCM1000006e36b50aRCRD&dnsName=us
Global X Lithium & Battery Tech ETF (LIT) - This one has the highest ER out of the three standing at 0.75%. LIT contains about 43 holdings, the top 10 holdings account for about 59.91%. This ETF is globally diversified, the top 3 countries are, similar to TAN, China (30.94%), The US (24.12%), and Hong Kong (13.22%). A lot of Chinese weight, please research this carefully. China is still considered an Emerging Market so this is a very unique weighting situation. Anyways, this ETF tracks the Solactive Global Lithium Index which is Market-Cap Weighted. This ETF is unique because it focuses on the Full Lithium Cycle which means it offers exposure to the Metal/Mining, Lithium Refining, and Battery Production Segments. This ETF is similar in some ways to Commodity Metal ETFs, keep this in mind if you plan on going further with this.
Fact Sheet: https://www.globalxetfs.com/content/files/LIT-factsheet.pdf (This Fact Sheet is 3 months old, it's outdated. Seek out a website such as ETF.Com for up to date information)
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What I provided is very brief. If you're serious about Clean Energy, you must read each ETFs fact sheet along with the prospectuses. This will educate you on the field more and provide more crucial data for each fund.
The main difference between each of these ETFs really comes down to the underlying holdings, sector allocations, and global diversification. Analyze your Risk Tolerance and Circle Of Competence in terms of holding/sectoglobality for each fund before making a decision.
Disclaimer: I am NOT a financial expert. You MUST do your own diligence -- this is ONLY for educational purposes.
- Naitor295
submitted by Naitor295 to investing [link] [comments]


2020.10.26 02:04 wasabimcdouble I took the Top 10 players in MVP voting and tried to find the difference each player made for their teams, and how they’ impacted their teams in the clutch since the beginning of the year. Here are my findings.

Hello everybody. After an Adderall and a cup of coffee I decided to spend 8 hours collecting stats to find how impactful the Top 10 MVP candidates have been to their team since the beginning of the year. I am not making any conclusions from my stats, but the findings are nonetheless interesting, and I implore you to use them however you please. The stats sorted in this thread are meant to tell you about the difference a player makes in certain times for their team
Important notes for these stats: The ‘standard’ stats collected are from games since January 1st, and regular season only. The reason I did this was because I wanted to be conducive of more recent play, as well as account for the more recent bubble performances. The games held in November and December of 2019 are so far away at this point that I felt my selection would be more accurate to how a player is playing now. These stats are from regular season only. This is just a personal test run for stat collection so don’t be too bothered with the methodology. You will notice some players don’t pop off the screen like you expect them to, namely LeBron, so it’s important to keep in mind that they had a secured position relatively early to other teams. Basically, winning to LeBron was not as important to the fringe playoff contenders, or teams that were gunning for preferred seeding. In addition, because this is Top 10 MVP candidates, Jimmy Butler is missing. Sorry Jimmy. I’m not too upset about this, as he had a smaller sample size relative to the others due to injury. During this process, I realized that clutch stats weren’t actually being collected from January 1st but rather the beginning of the season. This was an issue with NBA’s website, as I double checked that I had entered the right functions. All stats were collected from NBA’s website. So, standard stats are traced from January 1st. Clutch stats are traced from November 2019.
Clutch Stats: These are stats from the regular season where a players team had a 5-point difference or less, either ahead or behind, within the last 5 minutes of a game.
Real Ranking: This is a players real rank in unsorted categories. As mentioned, the stats sorted in this thread are meant to tell you about the difference a player makes in certain times for their team, but not too much about their skill in most categories. For example, Chris Paul’s Net Rating does not really change much with Clutch vs his Standard Net Rating. But that is not because he is a bad player or does not positively affect his team. Rather, it is a sign that he is always excellent. This is what you should be looking for in Real Ranking. Players who are always great, or poor, regardless of clutch or not.
Chart One - Players Ordered by Offensive Net Rating Difference in the Clutch: First, I wanted to look at the offensive difference a player had in the clutch compared to their normal performance. Offensive rating calculates an individual players efficiency at producing points for the offense. I took a players Clutch OffRTG and subtracted their Standard OffRTG. The stats below show which MVP candidates came alive in the clutch:
Players Ordered by Offensive Net Rating Difference in the Clutch Difference Clutch Offensive Net Rating (Real Ranking) Offensive Rating (Real Ranking)
1. Pascal Siakam +11.5 123.4 (1) 111.9 (7)
2. James Harden +5.3 117.7 (5) 112.4 (6)
3. Chris Paul +4.8 122.2 (2) 117.4 (3)
T4. Nikola Jokic +1.2 115.6 (6) 114.4 (5)
T4. Giannis Antetokounmpo +1.2 112.8 (7) 111.6 (T9)
6. Damian Lillard +0.6 119.9 (3) 119.3 (2)
7. Kawhi Leonard -0.9 119.4 (4) 120.3 (1)
8. Anthony Davis -3.8 107.8 (8) 111.6 (T9)
9. LeBron James -5.0 106.3 (9) 111.3 (10)
10. Luka Doncic -15.7 100.4 (10) 116.1 (4)
Takeaways: Pascal Siakam and the Raptors came alive in the clutch big time last year. Later in this thread, you’ll see how much of that is actually his own work, having the biggest TS% jump of any player in this thread, with the second highest Clutch TS% overall.
Chris Paul led his team to the third highest Offensive Rating mentioned, and somehow made them better in do or die situations.
Dame and Kawhi don’t make the same dramatic jumps, but maintain the dominant offensive consistency needed during crunch time to still be amongst the best in the league.
Giannis and the Bucks, though, are slightly middling during both the Clutch and Standard Offensive situations.
Luka Doncic has by far and away the worst Offensive Rating in the Clutch, with a -15.7 drop, 10 less than LeBron who’s second to last ahead of him. We’ll explore this more later in the thread.
Chart Two - Players Ordered by Defensive Net Rating Difference in the Clutch: Conversely, I wanted to take a similar look at which players came alive defensively in the clutch. Defensive ratings used here are meant to measure an individual players efficiency at preventing the other team from scoring points. The lower rating the better, so these ranks are sorted by who made the most drastic defensive jump in the clutch. A negative number is good.
Players Ordered by Defensive Net Rating Difference in the Clutch Difference Clutch Defensive Net Rating (Real Ranking) Defensive Net Rating (Real Ranking)
1. Nikola Jokic -15.6 97.5 (5) 113.1 (8)
2. James Harden -12.8 96.6 (2) 109.4 (7)
T3. Giannis Antetokoumpo -10.6 85.7 (1) 96.6 (1)
T3. Anthony Davis -10.6 97.6 (6) 108.2 (5)
5. Chris Paul -10.4 96.9 (3) 107.3 (4)
6. Luka Doncic -7.2 106.3 (9) 113.2 (9)
7. Kawhi Leonard -6.7 101.8 (T7) 108.2 (6)
8. Damian Lillard -3.3 115.0 (10) 118.3 (10)
9. LeBron James -2.4 101.8 (T7) 104.2 (3)
10. Pascal Siakam +1.1 104.5 (8) 103.4 (2)
Takeaways: Pascal Siakam with the Raptors have the second-best standard defensive rating with him on the floor but are the only team that didn’t elevate their defensive game in the clutch. This is unfortunate because they were able to do dramatically better on offense. To be fair to Siakam, the 104.5-103.4 range is not horrible, but it does say something about the Raptors and Siakam’s inability to elevate their defense when they needed it most.
Dame and the Blazers are nuclear on offense, but Chernobyl on defense. By far the worst defensive stats here.
On the flip side, Giannis apparently is a defensive god with the Bucks, leading in both clutch Defensive Net Rating and Defensive Net Rating.
Harden and the Rockets small ball somehow come away with second best Clutch Defensive Rating, further destroying the narrative that Harden is a bad defender.
Speaking of going against narratives, the Nuggets and Jokic make this massive crunch time jump from one of the worst in the league to one of the best. It's interesting to compare how moderate Kawhi's Clippers change was. From that WCF Semi-Finals series, these drastic changes and crunch time lockdowns are what swung the series back to Denver when their backs were against the wall.
Once again, Chris Paul takes a great game, and makes it better, but this time on the defensive end.
Finally, it is important not to be distracted by LeBron’s low rated differential here. 104.2 to 101.8 are both excellent defensive ratings.
Chart Three Players Ordered by On/Off Net Rating Difference: This chart here is the only one that is devoid of any clutch factor. This is a players teams’ Net Rating with them on the floor subtracted by their team’s performance off the floor. From this, we can infer how much of an impact each player had for their squad. The Real Rankings for Net Rating-Off are ordered backwards. The worse a team looks with them off the court, the better a player looks.
Players Ordered by On/Off Net Rating Difference On/Off Net Rating Difference Net Rating-On (Real Ranking) Net Rating-Off (Real Ranking)
1. Chris Paul +18.7 +10.1 (3) -8.6 (1)
2. Giannis Antetokounmpo +17.3 +15.0 (1) -2.3 (4)
3. Kawhi Leonard +13.6 +11.8 (2) -1.8 (5)
4. LeBron James +8.6 +7.0 (4) -1.6 (6)
5. Damian Lillard +5.8 +1.0 (10) -4.8 (2)
6. James Harden +5.6 +3.0 (7) -2.6 (3)
7. Pascal Siakam +4.5 +8.5 (4) +4.0 (9)
8. Nikola Jokic +2.5 +1.2 (9) -1.3 (7)
9. Luka Doncic -0.3 +2.9 (8) +3.2 (8)
10. Anthony Davis -2.2 +3.4 (6) +5.6 (10)
Takeaways: Chris Paul meant everything to the Thunder. They are nothing without him. It has been known that the depth of that team was a problem, but they probably should have considered playing Paul 48 minutes a game. They should have considered cloning Chris Paul. They should have signed Cliff Paul.
The Blazers probably should have done the same 48 minutes a game strategy with Dame if they wanted even a chance to win a game. That pitiful Blazers Net Rating-Off is not a surprise to anyone who’s familiar with the Blazers injury woes. Sadly for Dame, +1.0 Net Rating-On is the worst of any player here, barely managing to scrape by. This isn’t too shocking considering the Blazers had the worst record of any team discussed here at 35-39. Without Lillard, the Blazers plummet. It turns out that having Mario Hezonja as your sixth man translates to losing basketball.
Next, Giannis shows that he means everything to the Bucks. It’s somewhat surprising in retrospect, just looking these stats, that the only game the Heat were able to take from them was the one Giannis went out with an injury. Obviously, as an avid Heat watcher throughout the regular season, these stats don’t give you the heads up to the fact that no team in the NBA was better equipped to stop him than the Heat. But Giannis’ impact for the Bucks is undeniable. He has the defense. He needs to lock in and conquer the offensive side of the game.
Both Kawhi and LeBron, paired with star teammates, show that they are the alpha dogs in town. For anybody curious, Paul George has a difference of +7.0, but the Clippers don’t fall into the negative like they do when Kawhi is sitting.
Pascal Siakam’s +4.0 Net Rating-Off speaks heavily to the Raptors depth, but they still improve the teams quality when he’s on the floor very well, all the way to the 4th highest Net Rating-On when he’s checked in.
Poor Anthony Davis, who has a solid +3.4 when he’s on the floor, sees the Lakers jump to a +5.6 when he’s off. I suppose this is a side effect of having LeBron as a teammate, who skews his stats through dominant leadership. I don’t feel too bad for Davis. Having great teammates is a good problem to have. And he is still decidedly positive.
Finally, Luka Doncic off the court gives the Mavericks a better Net Rating. When he’s on the bench, the Mavs have a slightly worse offense, but better defense, and that’s what does it for Luka’s negative skewing. To me, this speaks heavily to the Mavericks depth combined with Rick Carslile’s coaching. Since January 1st in 42 games where Luka spent some time off the court, the Mavs without Luka had a 115.2 offensive rating. This would be the highest in the NBA of all teams over the same time. Kristaps Porzingis, Seth Curry, Jalen Brunson, Maxi Kleber, THJ, Dorian Finney-Smith, Dwight Powell, Trey Burke, J.J. Barea, Boban, and Delon Wright might very well be the best offensive depth in the league when healthy. Interestingly, during the mentioned time frame, Kristaps Porzingis has an excellent +6.9 On/Off differential compared to Luka’s -0.3, and the Mavericks Off Court Net Rating for Kristaps nearly breaks even at +0.1. Kristaps really unlocked his game after a rocky post-injury start to the season, but he is still trending towards stardom if his health allows him.
Chart Four - Players Ordered by Clutch Net Rating Difference subtracted by Net Rating On/Off Difference: This chart takes a players Net Rating in the Clutch and the previously analyzed Standard Net Rating of Players. The players who come alive in the clutch relative to their usual self rise in these rankings, while those that faulter fall.
Players Ordered by Clutch Net Rating Difference subtracted by Net Rating On/Off Difference Difference Clutch Net Rating Difference (Real Rank) Net Rating Difference (Real Rank)
1. Nikola Jokic +15.7 +18.2 (5) +2.5 (8)
2. James Harden +15.5 +21.1 (3) +5.6 (6)
3. Pascal Siakam +14.4 +18.9 (4) +4.5 (7)
4. Anthony Davis +12.4 +10.2 (7) -2.2 (10)
5. Giannis Antetokounmpo +9.8 +27.1 (1) +17.3 (2)
6. Chris Paul +6.6 +25.3 (2) +18.7 (1)
7. Kawhi Leonard +4.0 +17.6 (6) +13.6 (3)
8. Damian Lillard -1.0 +4.8 (8) +5.8 (8)
9. LeBron James -4.1 +4.5 (9) +8.6 (4)
10. Luka Doncic -6.2 -5.9 (10) -0.3 (9)
Takeaways: It’s no secret that Jokic and the Nuggets are clutch, and as we’ve reviewed, it’s because they get better on defense when they need to, while maintaining the solid offensive consistency that the big man is known for.
Harden takes a huge jump in the clutch, improving both offense and defense dramatically when needed, being second in differential in both categories.
Pascal takes a jump, but unlike those ahead of him, he does it exclusively through offensive dominance, while being the only player to take a (slight) step back on defense. Siakam more than doubled second place offensive differential player James Harden and it shows its impact here.
Anthony Davis, who heavily trailed LeBron in On/Off net rating, seemingly takes the reign from LeBron in crunch time, elevating his game defensively.
A reoccurring theme in this thread is that Giannis and Chris Paul seemingly mean everything to their teams, and it is glaringly obvious here. Though only 5th and 6th in differential respectively, they are first and second in real Clutch Net Rating, after being second and first in Standard Net Rating. It is hard to elevate your game when you are already a god.
Kawhi doesn’t drastically improve his game compared to others, but going upwards from a +13.6 to a +17.6 Clutch Net Rating deserves applause.
Both Dame and LeBron are negative relative to their Standard Net Rating, but are both positives on the floor regardless.
Doncic, however, takes a negative Standard Net Rating and makes it worse, with an appalling -5.9 Clutch Net Rating, the only player on this list with a negative in the category, and it isn’t even close. Remember, this year the Mavericks had the most efficient offense in NBA history, owning an incredible offensive rating of 115.8. Yet in clutch situations, their offensive rating falls to 93.9, the second worst in the league this season. This issue will be examined below.
Chart Five - Players Ordered by True Shooting % Difference in the Clutch: The chart below takes a players TS% in the Clutch and subtracts their Standard TS%. While the previous charts say much about a players team and how they impact them, this is chart highlights one of the most personal stats possible. In the clutch, can this player get a bucket?
Players Ordered by True Shooting % Difference in the Clutch TS% Differential Clutch TS% (Real Rank) Standard TS% (Real Rank)
1. Pascal Siakam +8.0% 63.3% (2) 55.3% (10)
2. Chris Paul +5.2% 67.0% (1) 61.8% (4)
3. James Harden -1.6% 59.2% (4) 60.8% (7)
4. Nikola Jokic -2.0% 60.5% (3) 62.7% (2)
5. Giannis Antetokounmpo -2.7% 58.7% (5) 61.4% (5)
6. Anthony Davis -5.7% 56.5% (6) 62.2% (3)
7. Kawhi Leonard -6.3% 54.6% (8) 60.9% (6)
8. Damian Lillard -8.6% 55.8% (7) 64.4% (1)
9. Luka Doncic -11.6% 45.0% (9) 56.6% (9)
10. LeBron James -14.3% 44.3% (10) 58.6% (8)
Takeaways: Pascal Siakam takes a dramatic jump, going from the worst Standard TS% in the pool to the second best, with a scorching 63.3% Clutch TS%. I said earlier that his offensive jump seen in the first chart was due to nobody but himself, and this jump proves it. He becomes an offensive torch for the Raptors.
Chris Paul, though, somehow ascends from a phenomenal 61.8% to an even better 67.0% in the Clutch. Throughout collecting these stats, I was questioning whether the Thunders poor depth was creating a statistical domino effect that made CP3 look better than he really is. No. CP3 is better than you think he is.
Harden and Jokic maintain great consistency in the clutch, barely slumping in do-or-die situations, with Jokic specifically impressing by staying in plus-60% TS% range.
Giannis takes a dip here, one of the first times we see a break from the paralleled seasons of him and CP3, but this 58.7% shouldn’t be too shocking. While he and the Bucks were one of the few to have a positive offensive differential from Standard to Clutch, his Standard Offensive Rating of 111.6 and Clutch Offensive Rating of 112.8 are both average relative to the league, and below average to the others compared here. In any case, his TS% remains above the league average of 56.3%.
AD, who I have somewhat identified as the Lakers closer, also stays above this threshold.
Kawhi however takes a major hit, going from 60.9% to 54.6%. This is the first time Kawhi has looked bad in any of these charts, despite a slight dip mentioned earlier, his Offensive Rating in the Clutch was 4th best of any of the players here, at an awesome 119.4. This -6.3% is surprising but may have more to do with the relatively small sample size of his, as only 22 games for Kawhi went into the clutch this season.
Dame Time takes a huge hit here, going from an MVP candidate best 64.4% to a sub-league average 55.8% during the clutch. This isn’t too shocking necessarily, as having the reputation for being one of the league’s most clutch players, on a team without much other active talent, meant Dame often got unpunishably doubled at the logo during close games. Still it is strange to see this regression from Dame Time.
Finally, unlike the magical Siakam, Doncic and LeBron take roughly average TS% and make them way worse. Both are remarkably poor FT shooters, but that doesn’t explain the disappearance of their shots. How does this effect their teams? We certainly know that LeBron is likely the best player in basketball, and Luka finished fourth in MVP voting – behind only Giannis, James, and Harden, ahead of everybody else in this thread. So are these guys elevating their teams in other ways? Are they still winning games when their shot has disappeared?
Chart Six - Players Ordered by Clutch Win Percentage: This chart is probably the most important one here when it comes to the clutch. Offensive, Defensive, Net Ratings, and True Shooting Percentages are very helpful stats, but they fall short of telling you the most important thing about basketball. They say nothing about winning a basketball game. Games listed are those in which players took part in, which explains why the Lakers duo have different records.
Players Ordered by Clutch Win Percentage Clutch Win Percentage Clutch Wins/Losses/Games Played
1. Giannis Antetokounmpo 76.2% 16-5 (21)
2. Anthony Davis 70.4% 19-8 (27)
3. Pascal Siakam 70.0% 21-9 (30)
T4. Nikola Jokic 67.4% 29-14 (43)
T4. Chris Paul 67.4% 29-14 (43)
6. LeBron James 66.7% 20-10 (30)
7. Kawhi Leonard 63.6% 14-8 (22)
8. James Harden 63.3% 19-11 (30)
9. Damian Lillard 60.0% 21-14 (35)
10. Luka Doncic 45.2% 14-17 (31)
Takeaways: Giannis and the Bucks were great at closing, as well as everybody within the top six.
CP3 led his team to winning over 2 out of 3 games that went into the clutch. The Joker had the exact same games played as CP3, and same record, highlighting how much better he and the Nuggets got in the clutch. Both Jokic and CP3 led in clutch games played at 43.
Pascal, through his offensive explosions at the end of the game, had a third best winning percentage, winning 70% in 30 clutch games.
As it turns out, LeBron’s TS% was never an issue when it mattered most. Affecting the game in other ways, both he and Davis both went over the finish line first in 2 out of 3 games that went into the clutch.
Kawhi’s drop is interesting. 63.6% is winning basketball, but barely, and he only had 22 clutch time appearances on the season. The single player here to have less appearances in the clutch? Giannis. Both would end up being second round bounces. Compared to LeBron’s 30 appearances, or Jokic’s 43, does this say something about the necessity to get more crunch time reps during the regular season?
James Harden, despite his impressive individual performance and convincing On/Off and Clutch Stats, only walked away with 63.3% of games that went into the crunch time. This, to me, says a lot about the players that surround him.
Dame, despite the Blazers best efforts of losing games while he takes a breather, still manages to walk away with 60.0%.
A 16.2% difference separates first place from ninth place, but the difference between Luka and ninth place is a massive 14.8% difference. The only player to finish negative in crunch time games on the season. Unlike LeBron, the poor crunch time TS% seeps through to these numbers, big time.
Final Takeaways: The way Chris Paul elevated the Thunder when on the court, and then his own game during the clutch, cannot be understated. Leading in Clutch TS%, Net Rating On/Off Differential, and finishing Top 5 in every mentioned stat category in this thread except for Clutch Net Rating to Net Rating On/Off Differential where he finished 6th with a +6.6, Paul showed that he was both clutch and that the Thunder lived through him. I never understood why he finished so high in MVP voting with the low 18/5/7 volume, but the impact is indisputable.
Giannis, from these stats, solidifies his case as the best defensive player in basketball. Elevating his team similarly to how Chris Paul does, only somewhat middling offense holds him back, as he does not really raise his offensive game in the clutch.
The opposite to Giannis is fellow African, Toronto Raptor Pascal Siakam. Siakam seemingly went nuclear during crunch time offensive situations, leading in Clutch Offensive Rating, Offensive Rating Differential, and TS% differential. But oddly, he and the Raptors were the only team to not make their defense better during crunch time. When I said opposite to Giannis, I meant it. Pascal takes great offense and makes it better, while Giannis takes great defense and makes it better. Both could still elevate the other end though, defensively for Siakam, and offensively for Giannis. I think Pascal can reach it, already holding the 2nd highest Standard Defensive Rating of any player mentioned here. In any case, I never realized Pascal was this clutch. Spicy P was red hot late in close games.
The absolute craziest thing about Pascal: if you read the important notes at the start of the tread you will know that the stats calculated are Post-January 1st Standard Stats over Clutch Stats from the entire regular season, due to a glitch in the NBA's website. So this means that Pascal's Standard Stats are from the points in the season where he actually regressed - as the unaccounted for months of October, November, and December were all season highs for him in efficiency and points, notably regressing after a groin injury on December 19th. Knowing he was not as good Post-January, you would think the reason Pascal looks so great here is because I am accounting for all clutch performances over the regular season, meaning there might be a severe skew from the clutch games that includes his prime months of October, November, and December, right? Wrong. Post-January, Siakam was actually radically better in the clutch. Taking into account this parameter, Siakam takes the leading 123.4 Clutch Offensive Rating from this thread to an untouchable 133.3 Clutch Offensive Rating, and bringing the second leading Clutch TS% of 63.3% to a would-be leading 68.0% Clutch TS%, while increasing the amount of FGA's he took in the clutch per game. Purely unstoppable. Defensively however, we see a major drop in the questionable Clutch Defensive Ratings going from a stout 97.1 to a measly 109.3. So was this a fair trade? Absolutely. The Pre-January Clutch Net Rating for Siakam was +8.7 to a dominant +24.1, trailing only Giannis and Chris Paul. And how did it translate to the teams record? Pre-January the Raptors had 13 games go into the clutch, going a poor 7-6 (54%) in those contests. Post-January, when Siakam hit his clutch stride: the Raptors played 17 games that went down to the wire. They won 14 of those. 14-3 (82%) would be the only game to break the 80% threshold. To me this shows that he has a switch that he can still flip on when he needs to. The groin injury, combined with him literally not practicing at all during the suspended season, did Pascal no favors. If he can recuperate though going into next season... The East might be in trouble. Siakam is special.
For the Lakers duo, the stats are sightly obscured for a few reasons. One, they were in a comfortable position for a lot of the year. Two, having two superstars on the same team affects each other’s stats heavily. That said, we can see through their Real Rankings, solid Offensive and Defensive Ratings, Clutch Win%, and positive On/Off impacts, that the duo were still dominant even in times where they were comfortably placed in the standings.
Jokic and Harden with the Nuggets and Rockets both displayed consistent offense that got better when needed, and the ability to dramatically elevate their defensive play from the norm. They finish 1st and 2nd respectfully in Clutch Net Rating to Net Rating On/Off Differential, and both show that their teams need them on the court to stay positive.
Kawhi displayed much of the consistency seen with CP3 and Giannis, leading in Standard Offensive Rating, and going for a solid -6.7 Defensive Rating Differential. He also maintained the 3rd highest Net Rating On/Off Differential behind CP3 and Giannis, and the 2nd Net Rating-On behind Giannis. He also had the 2nd least amount of crunch time games played with 22 to Giannis’ 21. Could this have affected both the Bucks and Clippers playoff runs? Do teams benefit form these crunch time experiences? The data implies it. Still, an excellent and impactful season from Kawhi.
Next, Damian Lillard was an unsurprising offensive torch, with his 119.3 Standard Offensive Rating and 119.9 Clutch Offensive Rating finishing 2nd and 3rd in their respective categories. Highest amongst Standard TS% with 64.4%, things get a little iffy for Lillard when you see that his shooting dropped off to around league average in crunch time. In addition, he with the Blazers defense was dramatically the worst one talked about in this thread, being dead last in Clutch Defensive Rating and Standard Defensive Rating. His group low Net Rating-On of +1.0 makes sense with him and the Blazers having the by far the worst record on the season of any team discussed here at 35-39, the only team below 50% on the season. Still, this Net Rating-On is much better than the injury plagued Blazers second worst -4.8 Net Rating-Off when he was getting a breather.
Luka Doncic, in many ways, was the anti-Chris Paul. Luka finished above 5th in only a single stat mentioned in this thread. He, with the Mavericks, were the worst in the following categories: Clutch Net Rating, Net Rating Differential, Clutch Win Percentage, Clutch Offensive Rating, and Offensive Rating Differential. He finished second to last in the following categories: Net Rating On/Off Differential, Standard TS%, Clutch TS%, Clutch Defensive Rating, and Standard Defensive Rating. He was the only mentioned player to have a negative Clutch Net Rating and Clutch Win Percentage, and one of only two players whose teams had higher Net Ratings while he was sitting on the bench. The redeeming parts of this stat collection for Luka is the 4th best Standard Offensive Rating, behind only Kawhi, CP3, and Dame. Another positive takeaway was that 6th place -7.2 Defensive Rating Differential, which means he and the Mavericks do improve in the clutch defensively. However, going to a 106.3 Clutch Defensive Rating from a 113.3 Standard Defensive Rating is still 9th of the candidates mentioned, ahead of only Damian Lillard’s Blazers. This was one of the more surprising takeaways for me. Doncic finished ahead of Kawhi Leonard, Anthony Davis, Chris Paul, Damian Lillard, Nikola Jokic, and Pascal Siakam in MVP voting, and snubbed all of these players but AD for a spot on the NBA first team. He only had a 7th seed playoff team, and seemingly is not playing a winning brand of basketball relative to what his contemporaries are doing. The well-rounded near triple-double statlines on the season, as well as being young, carried him to those season end accolades. The Mavericks, as seen in this thread, have some of the best depth in the league, and Doncic has a brilliant Coach in Rick Carlisle to help him develop his game. If the young Doncic wants to be a winner in the NBA, he needs to be the leader he his, and become a better closer for his team. We saw it in Game 4 against the Clippers. It was fantastic. But we need it on a more consistent basis.
submitted by wasabimcdouble to nba [link] [comments]


2020.10.26 01:46 merely-unlikely Light S3 Review

Light S3 Review

https://preview.redd.it/4gjtspb56cv51.jpg?width=4032&format=pjpg&auto=webp&s=0d91bd193da24e214d4129e14143357801596d69
First Impressions
Hi Vanmoofers - my Light S3 finally arrived on Friday and I thought I’d share my first impressions.

Some Context:
The S3 is the only electric bike I’ve ever ridden. I own a carbon fiber road bike (Specialized Roubaix) that I’ve put a few thousand miles on.
I ordered the S3 back on May 16 with an original deliver date of August 16. Back in August support told me (after I pressed them) my bike was at a warehouse in New Jersey (I live in NYC) but was delayed due to “quality checks.” The bike would be delayed five more times, each due to “quality checks” no one could explain in any detail.
The bike finally shipped from across the country in Washington (state). The original bike in NJ must have had an issue forcing Vanmoof to ship a new bike. Shipping took about a week and the UPS tracking number didn’t get any progress updates until it was in NY. Once in NY it arrived the next day.

Cost
VanMoof S3 Light
Peace of Mind: Theft + Maintenance
Shipping costs
Total: $2,830.65

Assembly
The box came pretty beat up, but now I understand why - the box was huge. There is no way one person could lift it, less due to weight and more due to the box’s length. One end of the box was ripped open and hanging on only by a couple strands of tape. I didn’t bother keeping the box, I would not trust it to survive another round of shipping if I ever needed to use it again.
The bike itself was in perfect condition. No scratches, dents, or any of the other issues people have reported. It was securely packaged and wrapped in foam.
Putting the bike together was fairly straightforward and the instructions were easy to follow. The only part that gave me trouble was connecting the motor cable - and oh boy did it give me trouble. I spent about four hours putting the bike together (which I imagine is on the high side of what it took most people). One of those hours was spent just on getting the motor cable to sit where it is supposed to in the fork. Another of the hours was spent trying to fish the bike end of the motor cable out from inside the fork after I accidentally pushed it all the way inside.
Someone else on this sub had suggested turning the bike upside when connecting the motor cable and that helped to a degree. As did angling the cable on a slant when pushing it inside. But in the end it took a lot more force than I am typically comfortable exerting on mechanical parts to push it into place and force the cover on.
This brings me to my first complaint about the bike - some of the pieces should have been better designed to just snap together in an obvious way. Vanmoof made a big deal about using all custom parts and designs, but then have awkward things like the motor cable connection. I also got a basket and had to thread the cable for the light through plastic pieces - imo the cable should have been fixed and the connection should have snapped in place when you snap the pieces together. It’s like the bike was designed to be put together by a professional/at the store but instead was shipped directly to customers.
A couple other pieces needed to be realigned - the front wheel was a bit off and the back fender wasn’t centered. But this took only a couple minutes to loosen the screws and adjust. No big deal.
Overall, assembling was pretty easy but imo a poor experience for a bike that costs almost $3k all in. Considering how close I live to the store, I really think shipping to the store and having them assembly it should have been an option. It concerns me that other people have had screws come loose and I don’t fully trust myself to have done and checked everything properly.

The Ride
I’ve ridden about 15 miles so far. I’d give you exact stats but I just opened the app and it says, “Damn! There’s a problem loading your data.”
It’s fun. And it’s scary.
20 mph might not sound that fast but getting there almost instantly after takeoff makes it feel incredibly fast. It’s not unusual for me to hit 20 mph on my road bike but on the S3 I was going that speed in areas I would not have on the road bike. The acceleration is fantastic. I frequently found myself holding on for dear life on the first ride. On the second ride I felt more comfortable with it and I imagine you get used to it pretty quickly.
The big tires also absorb a lot. I still felt the bumps but I was confident riding in places I would never take my road bike. Cobble stone streets down in Dumbo, no problem. I found myself no longer paying as much attention to going over potholes and manhole covers where I would be extremely vigilant on the road bike. This makes sense given how massive these tires are.
My original plan was to not use a helmet and the bike was indeed very stable. However, for the second ride I opted for a helmet as I fear falling on this thing. I never felt like I was going to lose balance or anything like that, but I did worry about going over bumps too quickly - I worried at times that I might bounce off the bike. In reality that means I should have slowed down, but also made me want a helmet.
I found myself worrying what might happen if I ran into someone in a way I never worried on my road bike. I’ve done a full flip on my road bike, landing on my head, but I was 100% fine once the surprise wore off. The S3 is incredibly heavy. I would not want to have it land on me if I fell. And worse, I think that hitting a pedestrian while going at top speed would have a high likelihood of killing them. Have I ever actually hit a pedestrian, no - I try to bike as safely as reasonable. But I worry on this thing.
The boost button is a ton of fun. I found myself using it on almost every acceleration and holding it most of the way on bridges. Once I hit 20mph there was a noticeably sudden stop in acceleration but that’s fine. Boost is definitely one of the big highlights of this bike.
The electric shifter is just as bad as everyone says. It is a bit inaccurate (shifts at weird times), grinds constantly, and I found it failed to downshift if I braked into a stop without pedaling. However, while I consider it a negative, it isn’t something that would turn me off the bike. It’s just a nuisance, not a big deal.
Battery - I’m down to 50% after about 15 miles. But I was on level 4 the whole time and made heavy use of the boost button. I don’t think the battery will be a concern on a daily basis but definitely expect to charge it every night with my riding style.

Walking the Bike
The weight and size of the bike become really apparent as soon as you try to walk it. The bike is really heavy, large, and unwieldy. It dwarfs my road bike by a significant margin. It is much longer, a little bit taller, and (obviously) many times heavier. The wheels are also quite fat and large. I didn’t really think too much about this during my test ride but it’s now the biggest con for me by far. Just standing with the bike it feels like it is trying to fall down. Navigating doorways and elevators is a big pain. If you have to carry it up any amount of stairs, this is probably not the bike for you.

The Basket
I have a basket on the front. It’s pretty well made. The metal cage is excellent. The base is plastic and could be nicer, but plenty sturdy. The mount that connects it to the bike is pretty bad. It too is plastic and I would not trust it with any real weight. Carrying some light groceries, fine. But try to sit on it like I’ve seen people do with the Citi Bikes and it will snap right off. Obviously it isn’t designed for that kind of weight but it stands in stark contrast to how sturdy the rest of the bike is. I wouldn’t even want to carry a lock in it on a regular basis for fear of it bending over time. That said, I wanted it mainly to carry take out orders and for that it seems more than capable.

Overall Impression
As an ebike, the S3 is incredible. It’s well made (apart from a few plastic parts) and the design looks fantastic. I love the light blue color. The speed and acceleration are a ton of fun. If I were to buy a second ebike, I would stick with Vanmoof (maybe get an X3). I’m somewhat tall at 6’1” so the height of the bike is comfortable for me but its length and overall size are a bit large for my taste. Anyone shorter than 6’ will likely have a bit of trouble.
While the S3 is a great ebike, mostly it just made me miss my road bike. This is the only ebike I’ve ever ridden but I think ebikes may not be for me. I miss the nimbleness and lightness of my road bike. But more than that, I miss actually biking. I like putting in the effort and feeling it in my legs. Part of the purpose behind buying this was to not get sweaty on the bridges around NYC but I’m not convinced that is enough. I don’t know exactly why, but riding the S3 just didn’t feel as fun as when I’m on my road bike. This is definitely a personal thing as most of the reviews of ebikes I see online are glowing about how fun they are.

I’m probably going to return it
For the reason I just stated - I simply didn’t find it as fun as pedaling manually. I might get a steel framed road bike with some fenders to use as my city bike. Yes, I will get sweaty on the bridges. But I will try to force myself to slow down and not make everything a race all the time. I wouldn’t let this point discourage you from buying the S3 - if you want an ebike I think it is fantastic. Just maybe not for me.

TLDR
It’s a great ebike and I’d recommend it to anyone in the market. It arrived completely undamaged as far as I can tell so far. But I’m thinking of going back to a traditional, manual bike as I like having to work for it a bit.
submitted by merely-unlikely to vanmoofbicycle [link] [comments]


2020.10.26 01:00 DuncnIdahosBandurria IPO DAY: Converge goes live @ 9:30am (Monday, Oct 26)

Happy Monday, Barkada --

The PSE closed up 139 points (!!) to 6484 ▲2.2%.

Happy IPO day! Converge joins the big board today with the 2nd biggest IPO ever in PSE history, in terms of value. Let's see how it does in terms of performance. Shout-out to tekwani99 for reminding me that my "IPO Calendar" still had the wrong date listed for the IPO. It's today! IT'S TODAY.
This is a very big IPO. I don't expect this to be a "ceiling play" like MerryMart. Be careful. Regardless of whether you bought stock during the offer period, or plan to trade the IPO, or just plan to watch: be careful. If you make trades on IPO day, have a plan. Don't start the day as a trader, but end up as an investor. Put in your stops.

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COVID Update

WW: 42918240 PH: 367805 

Top 3 MB indices:

 Fast Food ▲4.52% 2019 IPOs ▲3.51% 2020 IPOs ▲2.94% 

Bottom 3 MB indices:

 Logistics ▼0.80% MiddleClass ▼0.58% Cement ▼0.39% 

Main stories covered:

  • [UPDATE] Converge [CNVRG 16.80] IPO is TODAY... the 2nd biggest IPO in PSE history is set to go off this morning. We’ve talked a lot about Converge in this space, but all that matters (at least initially) is what the traders think when the bell rings to start the buying and selling. Those that bought the IPO will be “protected” to a limited extent by CNVRG’s stabilization agent, UBS AG Singapore, which will have authorization to buy up to around 255m shares over the stock’s first 30 days of life to help “prevent or minimize” a reduction in market price.
    • MB: Moment of truth for CNVRG. The market has been ripping as of late (that’s good), we’re up over 11% in the past month, but still the question comes down to one of value. Is CNVRG worth P16.80/share? Can the “Other Dennis” translate a cash bump into market growth to justify the price? Tune in to find out. :)
  • [NEWS] AREIT [AREIT 25.65 ▼0.19%] acquires another property from papa... the real estate investment trust, that IPO’d just a few months ago, has purchased another property from its parent company, Ayala Land [ALI 33.95 ▲1.34%]. AREIT purchased “The 30th” in Pasig from ALI for P5.1bn. The building is commercial hub/shopping mall. The deal only transfers the ownership of the building and the long-term leases within the building to AREIT, however, as the ownership of the land remains with ALI.
    • MB: AREIT is just starting to stretch its legs. News hit around the same time that AREIT would be raising P6.4bn through a bond sale, and opening up a P12bn credit facility with banks to enable additional acquisitions. All of these are positive moves for shareholders; debt is cheap, and provided the properties are of good quality and lease at attractive rates, adding to the portfolio adds to the quarterly dividend.
  • [UPDATE] POGO flight in progress?... Rappler is reporting that the Subic Bay Metropolitan Authority’s stats show that the POGOs (Philippine Offshore Gaming Organizations) have reduced their staffing levels by 85%. Less than 500 Chinese staff remain inside the SBMA’s jurisdiction, from a high-water mark of over 1,500 during the initial stages of the lockdown. This lines up loosely with the projections of property analyst David Leechiu, who predicted that up to 17% of total office space would be vacant by year-end due to POGO workers leaving, and up to 20-30% of office space vacant in 2021 due to the same.
    • MB: Very little is known about the owners of the POGO firms, so it’s difficult to say why anything happens in particular. We always hear about what POGOs are “thinking” from property analysts like Leechiu, who only looks at trailing data like empty office space, or from politicians or bureaucrats at PAGCOR who have obvious conflicts. This we do know: COVID crippled earnings, movement restrictions hampered operations, and the new taxes levied by the government make the environment less friendly (at least on paper; it’s not like the government ever collects any of those taxes). My personal contacts in the POGO space have maintained that POGO employers are happy and willing to scale up and down without much notice, and appear to be scaling down to skeleton levels in order to ride out the pandemic, but also what they consider to be the temporary crack-down by China. No matter what, property developers that jumped on the “recurring revenue” commercial lease train like Megaworld [MEG 3.14 ▲1.95%], DoubleDragon [DD 14.50 ▼0.68%], Ayala Land [ALI 33.95 ▲1.34%], and DM Wenceslao [DMW 5.53 ▲2.79%] may have an uphill battle to rearrange all those eggs in the basket.
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submitted by DuncnIdahosBandurria to phinvest [link] [comments]


2020.10.26 00:26 Notnotanerd Virtual NYC Marathon - Setting a PR by 11 minutes

### Race information
* **What?** NYC Virtual Marathon
* **When?** October 24, 2020
* **How far?** 26.2 miles
* **Where?** Norwood, MA
* **Strava activity:** [https://www.strava.com/activities/4237559550](https://www.strava.com/activities/4237559550)
* **Finish time:** 3:09:59

### Goals
Goal Description Completed?
-------------------------------
A Set a new PR *Yes*
B < 3:15 *Yes*
C < 3:10 *Yes to me but see below for explanation*


### Splits
Mile Time
------------
1 7:43.9
2 7:42.0
3 7:18.5
4 7:14.2
5 7:20.8
6 7:23.2
7 7:18.2
8 7:15.7
9 7:15.1
10 7:07.3
11 7:11.5
12 7:06.1
13 7:15.6
14 7:08.0
15 7:20.5
16 7:08.1
17 7:17.1
18 7:15.8
19 7:10.5
20 6:58.0
21 7:19.3
22 7:19.6
23 6:59.7
24 7:07.9
25 7:15.5
26 7:15.3
27 1:11.6

### Note on Finishing Time
As you can see my top goal was to break 3:10. When I stopped my watch at 26.2, I was at 3:09:59. When my Garmin activity updated to Strava, Strava added two seconds and put my time as 3:10:01. On the leaderboard for the Virtual NYC Marathon, Strava ahs my time as 3:10:07 as their data had the run just shy of 26.2 (despite what my Garmin had) and stretched it a few seconds on the leaderboard. Whatever, thats the issue with doing virtual races this way, but I'll go with the 3:09:59 because I can!
Also, I'm of the attitude that it has to be an official race for a PR to count, but we're in different times right right now when you beat your PR by more than 11 minutes, I think it still safe to say I've beat my personal record!

### Prior Race Experience
This was my third marathon. Last September I ran my first at the New England Green River Marathon. That course was a downhill course with a net elevation loss of -1400 and I finished at 3:21:09. I then ran the Millinocket Marathon last December, had a terrible time and finished at 4:09:23.

### Training
I got into NYC through the lottery and was planned to be my big race of the year. I had however signed up for far too many other races that were on my slate (the Seven Sisters Trail Race, a really tough 12 mile trail race in Western Massachusetts, the BAA Distance Medley, a 20 miler, and the Mount Washington Road Race), but those were all obviously were cancelled. The last to be cancelled was NYC, and while I knew it would be cancelled, I kept base training until I got the final word, that didn't come until about 17 or 18 weeks before NYC, so it was right before my planned 16 week training was set to start.
For the base training, I had started to work with a coach to help me focus my training, determine my paces, and to force me to run slower more often. During base I got up to a little over 50 mpw. At the peak of training, I hit 59 mpw.
When NYC was cancelled, I had already made up my mind that I would still train and run a marathon anyways. Luckily, my run club decided they would organize a club event with a marathon, half and 10K for members to run. It was planned for this weekend and it worked out that I could also use it for the Virtual NYC Marathon.
Having a coach was incredibly helpful for me. My training leading up to this race was the most consistent training I've had leading up to any race. While my coach was always the first one to say take a day off if something was ailing me, just having someone to keep you accountable helped force me to get out there every day. The biggest thing that helped was having someone who knows what they're doing tell me to take more recovery days. In the later part of the training schedule I found myself looking at my schedule and getting mad about another recovery day because I felt strong, but in hindsight, I needed to not go out and give extra effort to make sure I had the energy for my harder workouts. My 20 milers (I think I did 5 of them) went really well, especially those were there was more marathon pace running mixed in. I would run my 20s and feel strong after them and not dead the day after.
At the end of my training, I was training at a pace of a 3:01 marathon, however I knew the course was going to be hilly and tough, my coach and I figured 3:10-3:15 would be a reasonable goal.

### Course
Route was one loop and the only aid stops was my wife meeting me about every five miles. I carried water for the first 15 miles then dropped my water pack and had my wife hand me a bottle at mile 20. Also only had four of us running the marathon all together. The other three marathoners were planning on running about a four hour marathon so I started 30 minutes after them which allowed me to pass them around mile 18.
Route had a total of 1,164 of elevation gain according to Strava, but the route on Garmin connect had it as 1,387. Route starts with some uphills the first three miles, followed by a flatter four mile section, then four miles of up an downs, four miles of flatter and then the toughest section hits you from 15 to about 17.5 with almost 300 feet of elevation gain during that stretch. The remaining portion of the course is generally downhill, with a few small hills here and there.

### Race Strategy
Miles 1-3: 7:20 to 7:25 (Heart rate around 158)
Miles 4-13: 7:15 (HR ~165)
Miles 14-22: 7:10 to 7:15 (HR ~167)
Final 4.2: As fast as you can.

### Pre-race
A few good and bad things here. First, one thing I did a little differently from my first two marathons was eating a lot more before the run. Most of my long runs I would have half an English muffin with Nutella, 30-40 minutes ahead of the run, but before this run, I had my breakfast two hours before so I could eat more. I had a whole bagel, a whole English muffin with Nutella and a banana and I think that really helped. Didn’t feel full or bloated on the run because I ate it early enough and I think the extra carbs in my system helped prevent me from hitting the wall towards the end of the race.
For the bad here, I needed to give myself more time at the starting location. I think I did my warm up too close to the start, gave myself less than 10 minutes from when I finished the warm up jog and I started my run. This was just poor time management on my part but it didn’t give me enough time to get myself relaxed before starting the race. I also had a few technical issues that were causing me stress. On my warm up run, my heart rate monitor wasn’t working and my watch was telling me my HR was in zone 4 running at a 10:00/mile pace. Once I got back to the starting point, I was having to restart my watch to get the heart rate monitor to reconnect. After that, my headphones stopped connecting, requiring me to restart my watch again. Just added unnecessary stress right before starting.
I remember looking at my heart rate before I started and it was already in the 90s. Some of that was stress and some of it was nerves. I remember looking at my heart rate at the start line of my first marathon and it was similarly in the 90s and I couldn’t get it to come done just do to nerves.
Weather was pretty solid. Temps were in the 50s and early on it was pretty cloudy. Was expecting it to be cloudy most of the morning but in the middle of the run, the sun did come out for a decent amount of time, which made things feel a bit warmer, but never too bad.

### Miles 1 to 3
As was the case with most of the race, my HR was a higher than what I was aiming for. Some of this was due to the high HR to start and the nerves I think I had, and another part on this section was due to the early elevation gains. The goal here was to be between 7:20 and 7:25, but I scaled this back as for the first two miles just to try and keep my heart rate in check. I averaged a 162 HR for these two miles and was around a 7:43 pace for both miles and those were my slowest two miles the entire day. Mile 3 I started to settle in a bit more as the early hills were past me.

### Miles 4 to 13
I was pretty consistent during this section with sticking to the 7:15/mile pace. A few miles were slower, a few faster but I think I was pretty close to averaging these miles out to the 7:15 pace. HR was about 3-4 bpm higher than the target of 165 for most of this, but I felt given some of the additional hills in this area this wasn’t too crazy. I really felt I started to hit my stride a bit more around mile 10 as this was when I was past the early hills and had a fairly flat four mile section before hitting the toughest miles around mile 15. I had been carrying my water pack for this first half of the race, and early on my plan was to ditch it at mile 20, however, at the mile 10 marker I made the decision that I would ditch the pack at 15 right before the toughest section.

### Miles 14 to 22
I remember feeling right after 13 miles, that I was comfortable and that my heart rate was more in check and where I wanted it to be as was my pace. I was hoping to run 7:10’s for mile 14 and 15 and then 7:15’s for the next two as I hit all the hills. I was a bit slow on mile 15, but surprisingly was able to hit the paces for the next few mile as I went over the hills. My HR definitely shot up here into the 170s, which I think was to be expected. It definitely helped to drop my pack and not have the extra weight around mile 15.5. Once I got over the hills, I tried to let mile 18 be a bit of a recovery mile. I was hoping to run miles 19-22 around a 7:10. I was there for 19 and 20 and actually hit my first of two sub seven minute miles on mile 20 due to some of the downhill, but I remember feeling my legs getting tired at this point. I was a bit afraid that the higher heart rates early on were going to cause me to hit the wall. I was able to have my wife ready with a small bottle of wategatorade around mile 20 which came in handy. Was a little slower on 21 and 22, but the extra fluids helped and I took my last bit of fuel at this point. I knew I had some serious downhill for the lat 4.2 so I just made sure to get through those two miles without losing any momentum. I did have one point during this section where there was cop stopping traffic due to a dump truck and a small bulldozer that was tearing up a driveway. He was holding up his hands and telling me to stop and I just ran around the small bulldozer and past his stop sign. He kept yelling at me to stop and I just yelled back that I as running a marathon and blew past him! He would have cost me my sub 3:10 so not upset with my decision!

### Miles 23-26.2
I was hoping to be able to go a bit faster during this section, but I think the fact I ran them all at 7:15 or lower, it shows the overall pacing was pretty spot on. I started to feel in mile 23 my right calf wanting to cramp as well as some tightness in my left groin. Wasn’t anything too bad at that point, but they were definitely barking at me more the last two miles. At that point, I knew I was just in the "gut it out territory" and pushed myself. There was a hill right before I got back to the parking lot that I started at and I pushed myself through that, but I knew looking at my distances I was going to need to do a few loops in the parking lot to get to 26.2. But at this point I also took a look at my overall time and saw myself right around 3:08 with about a quarter of a mile to go. I did quick math in my head and knew 3:10 was within my grasp with a last push. The last .2 was at a 5:50 pace and just snuck in under that 3:10!

### Post-race
For what was mostly a solo marathon, it was awesome to have the other runners who were running the half marathon and 10K that my run club organized there. Start times were staggered so everyone finished roughly around the same time, so we had a decent crowd at the end to cheer everyone on.
I have to admit that I had doubts on if I could still get 3:10 early on in the race due to the high heart rate. I was afraid I had expended a bit too much effort early with the hills, that it was going to cause me to hit the wall. I knew I had been a bit slower then intended so if I could at least avoid the wall, I could still do 3:15 and set a PR, but if i hit the wall even that would have been in jeopardy. Luckily, I think due to my consistent training and extra fuel in the morning, I was able to avoid hitting the wall, and keep myself right on target and just sneak in under 3:10.
Despite being pretty sore today, I'm still riding pretty high today! I put roughly seven months in of consistent training and to see that payoff with the result I was going for is incredibly gratifying!

### What's next?
Continuing to push towards a Boston Qualifier. As a 32/m my qualifying time is 3:00 but realistically I need to aim for a 2:55 to hit any additional cutoff they add each year. This race gave me a lot of confidence that I'm a lot closer to this then I think. On a flatter course, today's run would have been closer to 3:00 so with a few more training cycles under my belt, I think that BQ is in my future!
submitted by Notnotanerd to running [link] [comments]


2020.10.26 00:09 InsiderMemeBot LEADERBOARD: Sun, Oct 25, 2020: 07:09 PM EDT

TOP TRADERS

##Overall Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score :------::-----:----- :------::-----:----- :------::-----:----- :------::-----:----- :------::-----:----- 1  u/Gasenos 225142 11 u/mistermuesli 38664 21 u/NovaAge 17100 31 u/Regis_Casillas 11815 41 u/multipurposeflame 8210 2 u/sponge_hitler 153590 12 u/Mugiwara_AF 38137 22 u/PosterQ 16599 32 u/CodyGriffin 11394 42 u/JetZflare25 7690 3 u/rad302 86964 13 u/BlitzTaco 37379 23 u/SubsubatomicGuy 16407 33 u/Zombiepixlz-gamr 10842 43 u/MemeCalendar 7448 4 u/chaosgiantmemes 82414 14 u/razhagever 30124 24 u/matuhx 15414 34 u/Olipop999 10430 44 u/FoxTrotPlays 6656 5 u/iamscythed 64008 15 u/Hangzhounike 26045 25 u/KushPatil 15164 35 u/2D_DoS 10252 45 u/aemanthefox 6397 6 u/3D_Guernsey 51861 16 u/CritzD 23428 26 u/dhtikna 14947 36 u/Allonsy_11 9493 46 u/ibwitmypigeons 6343 7 u/Useless_Archives 48050 17 u/Umber0010 23149 27 u/acidcomplex_ 14002 37 u/CyberDalek6401 9211 47 u/Zeetelli 6323 8 u/Doses_of_Happiness 46608 18 u/MyNameSpaghette 22185 28 u/ncroney12 13654 38 u/GnelforGnoblin 9175 48 u/myownwildthoughts 5846 9 u/pineapple_overlord 41846 19 u/rosesan 19065 29 u/occultmoon 13130 39 u/Plastic_Pinocchio 8824 49 u/Sonorational 5585

10 u/Ralle1998 40209 20 u/blaZikeN_257 17184 30 u/Kermit_Ur_Life 11992 40 u/NervigerWutbuerger 8689 50 u/Oxigenate 5327

Top Crafters

Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score
1  u/Gasenos 63474 11 u/Ralle1998 8085 21 u/GinjaNinjaYT 4706 31 u/NovaAge 3852 41 u/MrEpicXD 2803
2 u/rad302 25634 12 u/BlitzTaco 7525 22 u/CritzD 4700 32 u/Hammerman305 3529 42 u/MarioThePumer 2740
3 u/chaosgiantmemes 19480 13 u/MemeCalendar 7448 23 u/FoxTrotPlays 4619 33 u/superstonks 3513 43 u/ncroney12 2736
4 u/sponge_hitler 17624 14 u/mistermuesli 5901 24 u/rosesan 4473 34 u/c0mp0op3r 3495 44 u/Neoquem45_Yt 2734
5 u/pineapple_overlord 17501 15 u/Useless_Archives 5709 25 u/KushPatil 4284 35 u/PosterQ 3328 45 u/occultmoon 2690
6 u/iamscythed 14686 16 u/Sonorational 5502 26 u/blaZikeN_257 4252 36 u/CyberDalek6401 3314 46 u/Azuridus 2673
7 u/3D_Guernsey 11334 17 u/Umber0010 5498 27 u/matuhx 4170 37 u/Thecloud420 3175 47 u/KlerWatchCo 2657
8 u/Doses_of_Happiness 10636 18 u/Zombiepixlz-gamr 5425 28 u/_Open_Your_Mind_ 4148 38 u/MyNameSpaghette 3145 48 u/CrispyRoastedDuck 2501
9 u/Mugiwara_AF 9464 19 u/Hangzhounike 5211 29 u/JetZflare25 4041 39 u/dhtikna 3002 49 u/Delicious_Peters_III 2448
10 u/Allonsy_11 9141 20 u/acidcomplex_ 4752 30 u/CaesarWalinguini 3949 40 u/666thSuprisedPikachu 2828 50 u/Kermit_Ur_Life 2414

Top Distributors

Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score
1  u/Gasenos 161668 11 u/razhagever 30124 21 u/PosterQ 13271 31 u/Regis_Casillas 9430 41 u/myownwildthoughts 5846
2 u/sponge_hitler 135966 12 u/BlitzTaco 29854 22 u/NovaAge 13248 32 u/acidcomplex_ 9250 42 u/Zombiepixlz-gamr 5417
3 u/chaosgiantmemes 62934 13 u/Mugiwara_AF 28673 23 u/blaZikeN_257 12932 33 u/CodyGriffin 9097 43 u/anal__penetration 4824
4 u/rad302 61330 14 u/pineapple_overlord 24345 24 u/dhtikna 11945 34 u/Plastic_Pinocchio 8777 44 u/ibwitmypigeons 4590
5 u/iamscythed 49322 15 u/Hangzhounike 20834 25 u/matuhx 11244 35 u/2D_DoS 8172 45 u/Zeetelli 4512
6 u/Useless_Archives 42341 16 u/MyNameSpaghette 19040 26 u/ncroney12 10918 36 u/GnelforGnoblin 7325 46 u/Oxigenate 4261
7 u/3D_Guernsey 40527 17 u/CritzD 18728 27 u/KushPatil 10880 37 u/multipurposeflame 6604 47 u/CourierMTF 4032
8 u/Doses_of_Happiness 35972 18 u/Umber0010 17651 28 u/occultmoon 10440 38 u/aemanthefox 6396 48 u/Th3AlphaPooch 4007
9 u/mistermuesli 32763 19 u/SubsubatomicGuy 16407 29 u/Olipop999 10430 39 u/NervigerWutbuerger 6370 49 u/JetZflare25 3649
10 u/Ralle1998 32124 20 u/rosesan 14592 30 u/Kermit_Ur_Life 9578 40 u/CyberDalek6401 5897 50 u/Some_dumb_mexican 3512

TOP POSTS

Templates Examples
Yesterday
1: I found this image and saw potential. 1: Catcaughtyouslippin
    Author: u/DrJimMBear     Author: u/TriPpycheesE__
    Score: 726     Score: 26
2: This meme is so true. 2: [No Data](No Data)
    Author: u/Pep_Gaming_YT     Author: u/No Data
    Score: 9     Score: 0
3: Total Drama meme format that I think has potential. I called it "dusgusted Heather and happy Chris" (First time posting here, hope I done it right) 3: [No Data](No Data)
    Author: u/Elia1799     Author: u/No Data
    Score: 8     Score: 0
 
This week
1: Smirking cat template(pls use) 1: Found a possible good template
    Author: u/TriPpycheesE__     Author: u/Mugiwara_AF
    Score: 805     Score: 29363
2: Innuendo meets reality 2: World: we just can’t stop watching even though we know we’ll be f*cked next...
    Author: u/KlerWatchCo     Author: u/FooFooFox
    Score: 756     Score: 83
3: I found this image and saw potential. 3: You can't hide from buff bird.
    Author: u/DrJimMBear     Author: u/Darthvegan66
    Score: 726     Score: 50
 
This month
1: Negative thoughts corrected by a friend 1: Found a possible good template
    Author: u/KlerWatchCo     Author: u/Mugiwara_AF
    Score: 1070     Score: 29363
2: Steve in smash 2: should be illegal
    Author: u/FeedTheMii     Author: u/sponge_hitler
    Score: 1065     Score: 458
3: Spongebob VS Freezer template 3: Authorised Dealers describing your place on a waitlist
    Author: u/sponge_hitler     Author: u/KlerWatchCo
    Score: 977     Score: 280
 
This Year
1: New Sonic movie template 1: Let's spend some time together
    Author: u/Spudtastic-Spastic     Author: u/rad302
    Score: 1616     Score: 92780
2: An Upgrade 2: Lord of the rings
    Author: u/0Markus0     Author: u/rad302
    Score: 1533     Score: 60488
3: For singular tastes 3: Some told me to do it
    Author: u/African_Watersports     Author: u/Ralle1998
    Score: 1459     Score: 40154
 
All Time
1: New Sonic movie template 1: The gif that started it all
    Author: u/Spudtastic-Spastic     Author: u/Whymanwhy12
    Score: 1616     Score: 99404
2: Credit to u/mallow_dip 2: I once called Hulk Shrek.
    Author: u/Yemris     Author: u/Shiteingann
    Score: 1614     Score: 97200
3: An Upgrade 3: Let's spend some time together
    Author: u/0Markus0     Author: u/rad302
    Score: 1533     Score: 92780
submitted by InsiderMemeBot to InsiderMemeTrading [link] [comments]


2020.10.26 00:00 InsiderMemeBot-dev LEADERBOARD: Sun, Oct 25, 2020: 07:00 PM EDT

TOP TRADERS

##Overall Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score :------::-----:----- :------::-----:----- :------::-----:----- :------::-----:----- :------::-----:----- 1  u/sponge_hitler 82426 11 u/Morchel03 34883 21 u/Neyo708 19802 31 u/djnewton123 13762 41 u/Britisheagl 8869 2 u/Mussu007 81891 12 u/SiomarTehBeefalo 30445 22 u/Ryanrdc 15822 32 u/Edmenz 12027 42 u/BanditSlayer42 7755 3 u/TheSpookiestUser 73519 13 u/Jaredrap 28749 23 u/DankPinnaple 15205 33 u/AKushWarrior 11516 43 u/rad302 7618 4 u/InterracialMemeJob 67675 14 u/RoseBladePhantom 28442 24 u/mix_soup 15200 34 u/depressed_young_lad 11339 44 u/LimeGreenIndustries 7292 5 u/Saintrph 61613 15 u/Dawaitniggi 24331 25 u/Nathaniel__Bacon 15099 35 u/Tehwipez 11311 45 u/GnelforGnoblin 6669 6 u/SeaOdeEEE 52699 16 u/Svenwill 23536 26 u/HmanSupreme 15098 36 u/oroxoss 11164 46 u/Gorloftheinsatiable 6396 7 u/poopgoose1 50002 17 u/Kirk880 23200 27 u/Dane_Saint 15095 37 u/CaptainRadLad 9815 47 u/juanjocasamitjana 5655 8 u/HusseinRazak 46976 18 u/darthkers 22841 28 u/PokemonLegacy6 15053 38 u/Xyeeyx 9652 48 u/ninjabellybutt 5397 9 u/Useless_Archives 42986 19 u/Mono_KS 21194 29 u/quincepetchforth 14909 39 u/Holy_Hobo_ 9621 49 u/zJermando 5384

10 u/dingus_foringus 40851 20 u/jorgisgis 20431 30 u/A_BroadHumor 14541 40 u/Whymanwhy12 9045 50 u/Fleeling 5209

Top Crafters

Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score
1  u/Morchel03 30318 11 u/Dane_Saint 6426 21 u/Xyeeyx 4019 31 u/rad302 2949 41 u/Loopy_beetle 2215
2 u/Saintrph 26818 12 u/Jaredrap 6184 22 u/Neyo708 4013 32 u/ManHuntingMuffalo 2846 42 u/Whymanwhy12 1929
3 u/poopgoose1 25002 13 u/SiomarTehBeefalo 6094 23 u/zJermando 3619 33 u/TockLoxx 2787 43 u/Efficient_Half 1918
4 u/InterracialMemeJob 20977 14 u/RoseBladePhantom 5454 24 u/dingus_foringus 3462 34 u/djnewton123 2778 44 u/aValid_Username 1852
5 u/Mussu007 15605 15 u/Kirk880 4918 25 u/detroit_yeet 3328 35 u/zibbon50cal2 2648 45 u/istarxh 1849
6 u/TheSpookiestUser 13369 16 u/Dawaitniggi 4869 26 u/yeezus40 3219 36 u/fconyt 2547 46 u/Britisheagl 1847
7 u/Useless_Archives 10541 17 u/SeaOdeEEE 4842 27 u/Eze10gun 3086 37 u/Tehwipez 2541 47 u/Ryanrdc 1751
8 u/HusseinRazak 9397 18 u/PokemonLegacy6 4360 28 u/HmanSupreme 3030 38 u/Edmenz 2479 48 u/alice_right_foot-esq 1616
9 u/sponge_hitler 8592 19 u/Mono_KS 4249 29 u/quincepetchforth 2984 39 u/oroxoss 2470 49 u/BanditSlayer42 1554
10 u/Svenwill 6555 20 u/jorgisgis 4145 30 u/CaptainRadLad 2960 40 u/depressed_young_lad 2402 50 u/TomtheMemeKing 1535

Top Distributors

Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score Ranking Name Score
1  u/sponge_hitler 73834 11 u/SiomarTehBeefalo 24351 21 u/Nathaniel__Bacon 15099 31 u/Holy_Hobo_ 9608 41 u/LimeGreenIndustries 5759
2 u/Mussu007 66286 12 u/RoseBladePhantom 22988 22 u/mix_soup 14241 32 u/Edmenz 9548 42 u/Xyeeyx 5633
3 u/TheSpookiestUser 60150 13 u/darthkers 22841 23 u/DankPinnaple 14200 33 u/depressed_young_lad 8937 43 u/GnelforGnoblin 5330
4 u/SeaOdeEEE 47857 14 u/Jaredrap 22565 24 u/Ryanrdc 14071 34 u/Tehwipez 8770 44 u/Gorloftheinsatiable 5094
5 u/InterracialMemeJob 46698 15 u/Dawaitniggi 19462 25 u/A_BroadHumor 13268 35 u/oroxoss 8694 45 u/rad302 4669
6 u/HusseinRazak 37579 16 u/Kirk880 18282 26 u/HmanSupreme 12068 36 u/Dane_Saint 8669 46 u/Morchel03 4565
7 u/dingus_foringus 37389 17 u/Svenwill 16981 27 u/quincepetchforth 11925 37 u/Whymanwhy12 7116 47 u/ninjabellybutt 4284
8 u/Saintrph 34795 18 u/Mono_KS 16945 28 u/djnewton123 10984 38 u/Britisheagl 7022 48 u/juanjocasamitjana 4257
9 u/Useless_Archives 32445 19 u/jorgisgis 16286 29 u/AKushWarrior 10889 39 u/CaptainRadLad 6855 49 u/Fleeling 3852
10 u/poopgoose1 25000 20 u/Neyo708 15789 30 u/PokemonLegacy6 10693 40 u/BanditSlayer42 6201 50 u/SquishyR0b0 3800

TOP POSTS

Templates Examples
Yesterday
1: Example 1: [No Data](No Data)
    Author: u/Lil_KleinStein2     Author: u/No Data
    Score: 1     Score: 0
2: [No Data](No Data) 2: [No Data](No Data)
    Author: u/No Data     Author: u/No Data
    Score: 0     Score: 0
3: [No Data](No Data) 3: [No Data](No Data)
    Author: u/No Data     Author: u/No Data
    Score: 0     Score: 0
 
This week
1: Example 1: [No Data](No Data)
    Author: u/Lil_KleinStein2     Author: u/No Data
    Score: 1     Score: 0
2: [No Data](No Data) 2: [No Data](No Data)
    Author: u/No Data     Author: u/No Data
    Score: 0     Score: 0
3: [No Data](No Data) 3: [No Data](No Data)
    Author: u/No Data     Author: u/No Data
    Score: 0     Score: 0
 
This month
1: Example 1: [No Data](No Data)
    Author: u/Lil_KleinStein2     Author: u/No Data
    Score: 1     Score: 0
2: [No Data](No Data) 2: [No Data](No Data)
    Author: u/No Data     Author: u/No Data
    Score: 0     Score: 0
3: [No Data](No Data) 3: [No Data](No Data)
    Author: u/No Data     Author: u/No Data
    Score: 0     Score: 0
 
This Year
1: Here’s a Grinch facing the truth template 1: Effort is good
    Author: u/flameboy915     Author: u/Whymanwhy12
    Score: 812     Score: 99404
2: It knows what I want Gravity Falls template 2: Masturbation sense tingling
    Author: u/CaptainRadLad     Author: u/Saintrph
    Score: 724     Score: 58905
3: Spray painted Spongebob meme 3: Always be prepared
    Author: u/Morchel03     Author: u/TheSpookiestUser
    Score: 666     Score: 57919
 
All Time
1: Here’s a Grinch facing the truth template 1: Effort is good
    Author: u/flameboy915     Author: u/Whymanwhy12
    Score: 812     Score: 99404
2: It knows what I want Gravity Falls template 2: Masturbation sense tingling
    Author: u/CaptainRadLad     Author: u/Saintrph
    Score: 724     Score: 58905
3: Spray painted Spongebob meme 3: Always be prepared
    Author: u/Morchel03     Author: u/TheSpookiestUser
    Score: 666     Score: 57919
submitted by InsiderMemeBot-dev to InsiderMemeBot_Test [link] [comments]