Score
Title
4617
/u/st00pidm0nkey tells of the best revenge against people parking in his private parking lot.
100
Plane safely landed after engine failure. Pilot shows up in comments, and so does the air traffic controller who was on the radio with him during the crash
559
/u/weblowinherseys explains the relationship between deep-rooted racism in America and President Trump's opposition to NFL player protests
425
Redditor Jim Bozak gives sage advice on how he has helped numerous people with suicidal ideations and depression, and how he has applied these lessons to improve his own life
18
Redditor explains one of the largest shows of force to intimidate North Korea—an operation to cut down a tree.
32
u/OutcastAtLast refers to a type of hamburger by it's greater taxonomic classification.
16
Great advice on how to park an airplane
20
News coverage of a light aircraft crash landing is posted, the pilot and his eBay plane "Yolobird" are well known in the community. /u/WingedGeek shows up in the comments after multiple users in the comments reply to check on him.
13
The books of Bret Easton Ellis (Less Than Zero, American Psycho) reviewed by a character from one of his books.
13003
All-star lawyer gives an update on his free Church of Mormon resignation service, announces he has represented over 22k people fleeing from the faith.
990
User creates the perfect 5th Horseman of the Apocalypse
932
Defense lawyer explains their motivation for defending murderers and why the death penalty is so harmful
109
/u/floodcontrol explains why physicians take so long to update their procedures to newfound knowledge
43
/u/Immolated_Marmoset explains recent GOP party politics in terms of The Godfather.
88
Redditors discover that Westeros was designed by flipping a map of the United Kingdom upside down, and that Sean Bean is actually from Winterfell (aka. Sheffield) IRL
4949
I suggest making a site that "checks" if your password is safe, but is really pretense to teach you about security; /u/Ketrel delivers
31
OP asks why people don't like Kevin Durant, and user explainss with a great, unbiased post.
456
Chinese exchange student taught to hate the Green Bay Packers with the power of memes
307
What I learned from trolling conspiracy for 3 years.
233
Redditor explains what we're all missing about Dune.
74
/u/Kim_Jong_OON describes magical things everybody uses
166
Was George Washington actually a good general?
111
Barbers remember some of their clients' final cuts.
13
Haunted baby monitor
50
u/davesoft explains why cryonics isn't viable, so simply that a literal five year old could understand
371
/u/eyegone52 finds the gif of his false eye fitting three days late and answers everybody's questions (check his profile to see all of the answers).
261
Redditor articulates the effects of TBI which he has witnessed firsthand
32397
Redditor realizes just how bad a Nice Guy he was, gets therapy, and turns it all around
0
Redditor writes a review of his life...
38
NSFW /u/KeeperOfTheSinCave offers some advice to an aspiring young couple on how to spice up their porn. (NSFW)
0
The Best Representation of Discourse in the Destiny.gg Community.
36
The first trailer of Wes Anderson's next movie, "Isle of Dogs" is released. Redditor /u/IsleOfDogs shows up in the comments.
45
u/WinterzHaze offers to send a random stranger a Christmas card and inadvertently creates a little project to sends 100 Christmas cards around the world. People are amazing.
138
Reditor provides an informative and persuasive argument regarding the size of the US military budget and is awarded several deltas for changing people’s minds.
76
/u/Wang_Dangler explains why the credit rating agencies were more to blame than Goldman Sachs during the banking crisis
7
/u/Kerbonaut2014 notices a serendipitous statistic about a football player resulting in a string on nice comments
54316
Redditor zooms in on the wristwatch that a facepalming John Kelly is wearing and cross-references the time with the timeline of the speech Trump was giving at the UN, confirming the photo as a genuine reaction to the POtuS' remarks.
108
/u/Film_Director gives us a Trump's-eye-view of his possible motives for running for President and the trouble it's landed him in
262
/u/ikma Provides a terrific off the cuff refutation of a racist fake statistics study linked by another user.
56
Redditor explains that movie scenes are censored in the Middle East for showing as little as kissing
202 0 DrLionelRaymond 10/10. Would hire. (I run the R&D wing of a data science company).
26 0 bokononpreist Did you find a difference between home and away games?
72 0 SpecialK_714 Ol' Roy already knew this tho
15 0 zamstat I hope it is okay if I play the role of skeptic. It's not that I don't think you did good work - this is a fantastic write-up - but there are a few things that make me hesitant. * Was your final sample size ~450 with only ~30 runs without timeouts? Given that there are over 5000 games in a given season, that seems small to me. Less than 10% of all games contain a run that might merit a timeout? If it is the right sample size, I am also surprised that a timeout was called in 95% (~30/450) of scenarios where a team went on a run of 6+ points in a short timeframe. I cannot tell from your code whether you limited the analysis to only those games where the final overall scoring margin during the game was greater than 5 points. You mentioned it in your documentation, but I could not verify whether it was implemented. I agree with your inclination to attempt to control for 'guarantee game' blowout where teams are likely to go on 6+ runs, the opponent is less likely to calla timeout, and the run is likely to continue. However, I don't think the solution is to restrict the dataset to only those games that ended up close. You lose some relevant timeout scenarios (e.g., team that is up large/has opponent go on 6pt run/calls timeout/proceeds to blow them out) as well as potentially bias the control scenarios. * I must admit that I am not 100% clear on your methodology. I think I understand how you assess the stoppage of runs for settings with a timeout: you start the time-window at the timeout and track performance over the next 10 possessions. I am less clear on how you handle non-timeouts. Do you start the clock once the run becomes official (i.e., 6+ points) or when it hits its peak? If either of these are true, I believe you might be giving an advantage to the non-timeout group. As a quick check, it would be interesting to look at the summary statistics regarding the run size between the timeout and non-timeout groups. * Have you considered a matching study design? That is, for every scenario where a timeout was called, find a similar scenario where a timeout was not called. You could match on the current scoring differential, the time left in the game, and even on how the run progressed (e.g., made 2, miss, made 3, steal, made 3). * Have you considered working with expected win probabilities? Given that you scrapped play-by-plays for every game, you could likely create empirical win probability tables for every second of a 40 minute game. I see two key advantages here. I personally think this better quantifies a run (is a game 'slipping' away?) compared to a simple point differential. I am skeptical of 6+ points being classified as a run as a blanket statement. Also, it may help eliminate the 'blowout' scenarios. Again, I think this was a great investigation. I especially want to thank you for sharing your code. *Edits for formatting*
12 0 Barnhard This is impressive.
7 0 hesnothere So I guess what you're saying is, Roy knew?
5 0 [deleted] Good work. Someone should pay you for this.
6 0 TotallyIngenuous I think a 5 point average score margin is probably too restrictive in order to determine competitive games. You could increase it to 10 and be comfortable. I think we can all agree that a game that oscillates between a 5 and 15 point lead for one team is still a competitive game.
4 0 ljfdlksdjfhkl A few comments. A couple of preliminaries, first on notation: p(x|y) is not the probability that x AND y occur. It is the probability that x occurs GIVEN that y has already occurred. Bayes rule is all about this: p(x and y) [often written p(x ∩ y)] = p(x|y)*p(y) = p(y|x)*p(x). Secondly, keep in mind that this is an observational study, and so inferring causality is tricky. In particular, p(run ended|timeout) is NOT the "probability that calling a timeout is responsible for ending a run". It is the probability that the run ended given that a timeout was called, and says nothing directly about causal links. I think your calculations of p(RE|T) are correct, but two things: (a) the denominator in your Bayes equation is actually just p(timeout called), which you could calculate directly and simplify your code. But also (b), do you need to do the Bayes bit at all? Can't you calculate p(RE|T) directly from the data, as you are doing now for p(T|RE)? [i.e. find all situations where a timeout was called, and tabulate the proportion of those where the run ended = p(RE|T)]. Either way, the absolute value of p(RE|T) is not particularly informative (so your statement "as low as a 22% chance that timeouts are responsible for ending runs" is a little misleading). Imagine a situation where the probability of a run ending (without timeout) is 0.1, but it's 0.2 when a timeout is called. That would seem to be pretty good evidence that calling a timeout is associated with an increased probability of the run ending, even though the probability of the run ending is still quite low in absolute terms. Which brings us back to causality. Ideally you want to find situations where timeouts were called, and comparable situations where timeouts were not called, and look for evidence of a difference in the two sets of outcomes. I realize that you already know this, I'm just writing it down. Having found that evidence, it's down to interpretation and judgement as to whether or not the timeout was the causal mechanism. So the more relevant interpretation of p(RE|T) would be to look at p(RE|T)-p(RE|not T). A positive value would indiate a potential positive effect of timeout. This is what you're doing in the last figure. But your differences are negative (p(RE|not T) > p(RE|T) ?), with timeouts being associated with a slightly lower probability of the run ending. Which might be genuine (perhaps timeouts tend to be called when coaches get desperate and the run is basically unsalvageable, so the fact that the timeout has been called is really an indicator of the calling team being outplayed, rather than any indication of the timeout itself having a negative effect on run ending). But also I wonder if the way you are viewing runs is slightly problematic - runs of up to 10 events seems quite long, and the chances of a timeout being called in that span are quite high (e.g. look at your score ratio=1.0 numbers: you have 456 runs, in 430 of which a timeout was called). So (a) you have very little data about what happens when timeouts are NOT called, which makes it difficult to make inferences about the effect of timeout. And (b) there is no distinction between a timeout called early in the run vs a timeout called late in the run. Maybe there is some value in shortening your 10-event window, and/or comparing runs of given length (e.g. find all runs that extended for at least 3 events. Calculate the proportion of runs that ended after timeout was called AT 3 events, and the proportion that ended at 3 events without timeout. Repeat for different run lengths). Final comment, it might be worth repeating this in a statistical modelling framework and comparing results. It would be fairly straightforward: fit a binomial generalized linear model where the outcome (run ended) is a function of whether timeout was called (true or false), and look at the coefficient of the timeout term (and test its significance, if you like). Sorry all of that sounds rather negative, it's not meant to be. There's definitely some interesting results in there, just needs some refining to bring them out. You might be interested in this study, which looks at a closely-analogous situation of timeouts in volleyball matches: [detail](http://untan.gl/articles/2016/07/16_timeouts-in-the-polish-volleyball-league.html) and [shorter summary](https://markleb1.wordpress.com/2016/07/11/the-truth-about-timeouts-part-two/). Basically - there's not a lot of evidence that timeouts help in volleyball, either. (Edit: formatting)
3 0 TotallyIngenuous Holy shit, now this is what I call content.
3 0 barrio-libre Please forward to Sean Miller.
3 0 purpletraitor69 how would I know?
2 0 TotesMessenger I'm a bot, *bleep*, *bloop*. Someone has linked to this thread from another place on reddit: - [/r/bestof] [\/u\/Chu\_BOT posts rigorous statistical analysis of whether timeouts affect scoring runs in basketball. Potentially gets a job offer on the spot.](https://np.reddit.com/r/bestof/comments/6zlsz6/uchu_bot_posts_rigorous_statistical_analysis_of/) - [/r/theydidthemath] [\[RDTM\] Do timeouts stop scoring runs? (a thrilling statistical analysis) (x-post from r\/collegebasketball)](https://np.reddit.com/r/theydidthemath/comments/6zmqs6/rdtm_do_timeouts_stop_scoring_runs_a_thrilling/) [](#footer)*^(If you follow any of the above links, please respect the rules of reddit and don't vote in the other threads.) ^\([Info](/r/TotesMessenger) ^/ ^[Contact](/message/compose?to=/r/TotesMessenger))* [](#bot)
4 0 4thgengamecock Shut up and take my up-vote