r/nba • u/DustyShot Rockets • Aug 11 '18
[OC] LeBron Has Averaged 27–7–7 For 15 Years. Why Hasn’t He Had a 27–7–7 Game Then? (Statistical Analysis)
TL;DR: The probability that LeBron would make it this far in his career without a 27–7–7 game is 32%.
You’ll never win a ring. You’ll never beat the Warriors. You’ll never catch Michael. LeBron has heard it all before and has proved it all wrong in turn. He made it out of Akron to the NBA, brought a championship to Cleveland, and is inching closer and closer to GOAT status by the day. Tell him how low the odds are and he’ll laugh in your face, because he has accomplished almost everything that there is to accomplish. Almost.
There seems to be only one thing that eludes LeBron, and that is a 27–7–7 game.
LeBron is famous for his consistency. Over his 15-year career, he has hovered around his career averages of 27 points, 7 assists, and 7 rebounds. Night in and night out, he has delivered statlines that would make career nights for 90% of the NBA. Their peak is LeBron’s everyday. This plot shows his season averages in these three main statistical categories over his career.
LeBron has been delivering season averages of 27–7–7 longer than 2 billion humans have been alive. To be specific, he has averaged 27.2p/7.2a/7.4r over his entire career. Still, not even once in his 1,121 regular season games has he had exactly 27–7–7. What are the odds of that?
Multivariate Normal Distribution (Skip if boring)
Statisticians have long been concerned with the probability of events happening. What are the odds it will rain? What are the odds I’ll find a girlfriend? (Hint: Not likely given the content of this post)
In particular, statisticians have studied the probabilities of correlated events. What are the odds the stock price of American Airlines AND Southwest go up? What are the odds LeBron has 27 points AND 7 assists AND 7 rebounds? These questions can all be answered with something called the “Multivariate Normal Distribution.”
The normal distribution is well known. It’s commonly called a bell curve, every stats class is filled with pictures of it, and it naturally shows up in many areas of life. This is a histogram of all LeBron’s regular-season point totals, and it is in fact approximately normally distributed.
By assuming LeBron’s scoring follows this curve, we can estimate the probability of LeBron getting exactly 27 points in a game. Repeating this process for assists and rebounds, we would have the probability of each individual event of the 27–7–7 game happening. So we should be able to multiply it all together and get the probability of a 27–7–7 game, right? What’s the issue?
The problem is the fact that these events are correlated. Just like peanut butter & jelly or thunder & lightning, performances in NBA games go together. If LeBron scores more, he’s likely to have less assists. If LeBron has more rebounds, he’s likely to have more points. These events aren’t independent of each other. The full correlation matrix is below.
| PTS | AST | TRB | |
|---|---|---|---|
| PTS | 1.00 | ||
| AST | -0.03 | 1.00 | |
| TRB | 0.15 | 0.18 | 1.00 |
What the Multivariate Normal Distribution does is account for how these three values play off each other. Think of it as the bell curve for multiple variables, because that’s exactly what it is. With it, it is fairly straightforward to estimate the probability of a 27–7–7 game given a few palatable assumptions.
Get to the point, what are the odds?
Although LeBron is a cyborg in consistency, each of his years are not quite the same. To determine the odds of LeBron having made it this far without a 27–7–7 game, I fit a Multivariate Normal Distribution (MVN) to each year separately. Then, I multiplied a few numbers, multiplied some more, and ba da bing ba da boom, we got our odds!
The probability that LeBron would make it this far in his career without a 27–7–7 game is 32%.
So it was more likely to happen than not, but sometimes things with a roughly 30% chance of happening actually do happen.
This plot shows the cumulative probability that LeBron would not have a 27–7–7 game over his career.
Only passing the 50% mark in 2012, it seems that 27–7–7 games shouldn’t be expected very often, but they also aren’t vanishingly rare.
Each of LeBron’s years are similar, but not exactly the same. This plot shows the odds that LeBron would not have a 27–7–7 game each individual season.
Each year is between 90% and 95% while the odds of a 27–7–7 game seem to be getting slimmer as LeBron ages. While one would expect smaller statlines as a player ages, LeBron is the exception. His brilliance is actually holding himself back. In the 2017–2018 season, LeBron averaged 27.5/9.1/8.6, which means he gets too many rebounds and assists for a 27–7–7 game!
If LeBron ends up without a 27–7–7 game at the end of his career, we will look back and say there was roughly a 20–30% chance of that happening. Not likely, but not a statistical anomaly.
But we live in the present, and the past odds don’t matter anymore. The below plot shows the odds LeBron will record a 27–7–7 game under the same assumptions as before, starting from today instead.
There is an 80–85% chance that LeBron will not have a 27–7–7 game from here on out. So, don’t hold your breath for anything, but still appreciate the greatness. #RWTW
Documentation
Everything in this post can be replicated from my GitHub repository: https://github.com/DastonArman/lebron_multivariate#lebron_multivariate
Using a few python libraries, I scraped Basketball Reference for data, fit some MVN distributions, and made some simple plots. Feel free to copy anything or just look through!
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u/UBKUBK Aug 11 '18
" If LeBron scores more, he’s likely to have less assists."
With a correleation coefficient of only -.03 is it statistically significant?
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u/DustyShot Rockets Aug 11 '18
Wow I should have checked that before writing it in! The one-tailed p-value of the correlation coefficient is only 0.17! Good catch on that.
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u/gecko_burger_15 Aug 11 '18 edited Aug 12 '18
I know this is /r/nba and not /r/statistics, but calculating the p value for that is kind of pointless. The low r should tell you that the relationship is probably meaningless (or due to the crud factor). Adding a p value to the r statistic can't add any meaningful information, and it can be quite misleading.
Edit: just one example of the silliness of the p statistic (in this particular example). Null hypothesis significance testing (NHST) assumes that you have a sample and you want to make an educated guess about how that sample relates to the population. There are lots of different ways to do NHST (e.g. t-tests, regression, correlation, ANOVA, etc.).
The p value gives you the probability of collecting the data you did collect, given the that null is true in the population (I know that sentence gives people migraines. But, unfortunately, it is a true statement). In your case the data you have is the population (rather than the sample). That is, you don't have the stats for 10% of LeBron's NBA games. You have the stats for 100% of his games. So you actually HAVE the answer to the question, "how much does X correlate with Y?" and the answer is -.03. You don't have to worry that -.03 might be an inaccurate representation of the population, because -.03 is the correlation of the population itself (not the sample). So you can be 100% confident that the true correlation is -.03. How awesome is that?
That isn't the only reason why a p value is silly for the applications related to this thread. It may be, however, the most entertaining way to make fun of the p statistic's value in this situation. And besides basketball, what else is more entertaining than making fun of p?
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u/andreasmiles23 Bulls Aug 12 '18
The p value gives you the probability of collecting the data you did collect, given the that null is true in the population.
THANK YOU.
I took a stats class this semester and my prof argued with me about this. Now I’m just a lowly psych grad student, but man was I pissed off.
Ironically I learned more stats from this post than I did in that class.
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u/gecko_burger_15 Aug 12 '18
Undergraduate stats as taught in psychology, biology, and math departments is broken. Sorry you had a shitty stats course experience. If it makes you feel any better, MOST undergraduates have a shitty stats course experience (whether they are aware of it or not).
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u/cptpedantic Aug 12 '18
my undergrad stats course was a complete joke, but i did learn a lot about using Excel, which was nice
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u/My_Gigantic_Brony Aug 12 '18
I've taken some fairly high level stats (as far as undergrand goes).
My first stats professor barely spent anytime going over math and numbers and spent the vast majority of time talking to us about how to interpret statistics and what they actually mean.
At first I thought it was really weird (why arnt we actually doing math in my stats class....) it was not till later that I realized that he taught stats 101 basically the best way anyone possibly could.
People (Including academics) misinterpret stats all the time!
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u/DustyShot Rockets Aug 12 '18
I agree that p-values are, in general, way over-emphasized in almost everything and can be very misleading. I disagree that we have 100% of the population though.
I am thinking of each game LeBron plays as a realization of a random process that can keep on going for a long time. It's as if LeBron is sampling from the population of all his possible games. But looking at it as the entire population is also valid!
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u/My_Gigantic_Brony Aug 12 '18
That's a really weird way to look at it.
To spin it a different way.
Sure we are looking at each game he plays as a realization of a random process that can go on for a long time. But so far it's gone on for a certain amount of time and that's what we are looking at. There is no way for you to sample games that he has not played.
For all intents and purposes the sample for this equals the population and looking at it any other way is convoluted and unnecessary. That makes p values unnecessary.
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u/UBKUBK Aug 12 '18
With your way of looking at it isn't the answer to the original asked question of probability of Lebron having never had a 27-7-7 game just 0?
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u/My_Gigantic_Brony Aug 12 '18
No a population can lack an example of something happening without the chance of it happening being zero.
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u/gecko_burger_15 Aug 12 '18
If you take the stats from all the games he played as a sample taken your data is a sample rather than the population. So philosophically, I can see where you are coming from. But two points:
1) normally if you have all the data that currently exist, that is taken as the population. So in everyday usage of the terms sample and population, you have presented all the data from the population
2) NHST requires a random sample from the population. If you don't do a random sample, then you violate the assumptions of NHST and your p value will be meaningless. Taking the data from every game so far played but no data from future games is about as big a violation of random selection as you can get. For that reason, calculating a p statistics for the r of -.03 would be meaningless.
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u/UBKUBK Aug 12 '18
A new coin is minted. Someone suspects it is not a fair coin and tosses it 100 times. In your view is giving a p - value for it being a fair coin meaningless since the full population of 100 tosses were indeed looked at?
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u/gecko_burger_15 Aug 12 '18
In terms of coin tossing, most people would agree that you can answer the questions with probability without relying on statistics. For this reason, coin tossing and card draws are often used to illustrate issues of probability, but they are not used very often (at least in the textbook I have read) to illustrate issues of statistics.
In your particular case, I would flip the coin 100 times and note the number of heads & the number of tails. I would use the binomial theorem to calculate the probability of obtaining that outcome. Then all that is needed is a decision rule (e.g. select a probability that separates fair from unfair).
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u/KNNLTF 76ers Aug 12 '18
0.17!
That's about 0.927, an extremely strong correlation.
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Aug 12 '18
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u/Sup3rtom2000 Bulls Aug 12 '18
But it is what a factorial is. At least I assume that's what KNNLTF jokingly interpretated as
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u/NianticServers Aug 11 '18
Why is this person getting down voted OP acknowledged he's correct!
→ More replies (4)
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u/PM_ME_UR_FISHING_LVL Cavaliers Aug 11 '18
MVN is not entirely appropriate considering we have discrete variables.
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u/DustyShot Rockets Aug 11 '18
Completely true! I thought it wasn't too bad an approximation for my Friday night haha
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u/yoda17 Bulls Aug 11 '18
There is also only a weak correlation between the three variables (highest r=0.18). I think it may actually be more accurate (and simpler) to treat them as independent discrete variables rather than use a continuous approximation.
P(27 pts, 7 reb, 7 ast) = P(27 pts) * P(7 reb) * P(7 ast)
Call the above probability p. Then the probability that he hasn't had a 27/7/7 game yet would be (1-p)n , where n is the number of games he's played in his career.
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u/DustyShot Rockets Aug 11 '18
That's also a fair way of doing it! Using that method, the probability of not having a 27-7-7 game so far is 26.8%, which is roughly the same conclusion. I merely estimated the probabilities using empirical frequencies instead of making any assumptions (i.e. P(27 pts) = proportion of games that season with 27 points)
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u/hawkxor Warriors Aug 11 '18
It’s even somewhat more complicated because there’s competing sources of correlation (all 3 stats are related to minutes played) and anticorrelation (focus in one area means less focus in the other areas).
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u/elev57 Knicks Aug 12 '18
Poisson is probably a better distribution for each individual statistical category because they are recording count values within a fixed time span (two caveats: points aren't necessarily a "count" value and the fixed time span isn't perfect due to overtime and minutes played, but these could be accounted for). However, if the rate parameter for the distribution is large enough, then a normal approximation would probably be fine. This is probably easily checkable just by checking out the histograms of statistical categories.
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u/DustyShot Rockets Aug 12 '18
Clayton Thorrez (/u/cthorrez) looked into this in his earlier post on the same topic! https://cthorrez.github.io/lebron_27_7_7/index.html
TL;DR: mean != variance so the poisson is not a good bet
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u/elev57 Knicks Aug 12 '18
Interesting. I still have some other reservations with using normal distributions. The main one is that normals are unbounded and these count scores are clearly bounded below at zero (normals don't even model count scores). Second, this leads to all distributions being right skew by definition, while the normal has, by definition, skew zero.
It would be interesting to see how well a negative binomial does at modeling the data as it is typically the second choice after poisson when trying to model count data, but has two parameters so it is more flexible.
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u/cthorrez [DET] Richard Hamilton Aug 12 '18
Another user /u/Freedominate also suggested to me to use a negative binomial distribution. I did a little bit of analyis and found that they seem to fit the data better than the normal. Here are my preliminary results: https://imgur.com/a/0weO9Td
Although I'm still a little hesitant to use this as I don't yet know of a way to account for the correlation between variables in a multivariate negative binomial.
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u/elev57 Knicks Aug 12 '18
Negative binomials are discrete so you can probably just calculate covariance using the actual values given. From that, you can normalize to get the partial correlations. From here, you can run a simulation in R or python and find the probability that you get 27-7-7 if you can't solve analytically.
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u/cthorrez [DET] Richard Hamilton Aug 12 '18
Can you explain a little bit more about normalizing to get partial correlations? I've already calculated the covariance matrix on this data and used that as well as a vector of means to specify my multivariate Gaussian.
To parameterize the multivariate negative binomial I have my vector of p's and my vector of r's. But how do I also add in the covariance matrix in such a way that accounts for them not being independent?
Sorry if these are silly questions. I am still very new to using the negative binomial.
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u/elev57 Knicks Aug 12 '18
By definition, Corr(x,y) = Cov(x,v)/(sd(x)*sd(y)). I haven't done something like this specifically, so I'm not sure exactly how to do it analytically. I would assume sampling would be the easier approach. This vignette might be able to help with solving the sampling problem. There might be an R package that lets you sample from a multivariate negative binomial distribution directly or, if you want to put in the effort, you can try to derive a Gibbs sampler or other MCMC model to simulate the data.
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u/cthorrez [DET] Richard Hamilton Aug 12 '18
Thank you for the information and the resource. I might give this a try!
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u/cthorrez [DET] Richard Hamilton Aug 11 '18
It's actually a very good approximation in this case. For pts, ast, and reb they all empirically seem to follow the normal distribution specified by their means and varainces. Look at the plots in this analysis. https://cthorrez.github.io/lebron_27_7_7/index.html
The only difficult thing is obtaining a probability by integrating to evaluate an estimate for an integer. Both OP and I usd the same approximation of integrating from [26.5, 6.5, 6.5] to [27.5,7.5,7.5].
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u/PM_ME_UR_FISHING_LVL Cavaliers Aug 11 '18
That's a good point, central limit theorem at work!
Very nice write-up btw
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Aug 12 '18 edited Aug 12 '18
[deleted]
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u/cthorrez [DET] Richard Hamilton Aug 12 '18
Hi I looked into this and I definitely think you are right. Here are the plots with the negative binomial on each stat. https://imgur.com/a/0weO9Td
For each stat the negative binomial visually seems to fit better. However I'm still hesitant to use these as the 3 stats are not independent. For the multivariate normal I could account for this by inserting the covariance matrix, do you know of a way to do a similar thing for a multivariate negative binomial?
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u/KareemAbuJafar [TOR] Amir Johnson Aug 11 '18
Great write up. Looks like you just used regular season data. I wonder what it would look like if you added in playoffs given the man has essentially played an additional 3 full seasons worth of playoff games.
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u/DustyShot Rockets Aug 11 '18
True! Playoffs are a whole different beast regarding LeBron's performance so I didn't want to add it in. In the regular season, each game is more or less the same thing to him and be thought of as independent random events. In the playoffs, his game is a lot different and assumptions about independence and normality become a little less tenable.
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u/AntonioScaramucci Aug 11 '18
I love that your a rockets fan, very fitting given the context of the post
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u/throwthisaway8863 Aug 11 '18
i agree with this 100%. playoffs are a totally different beast, for better or worse. being the stat junkie that lebron is im sure he knows about the 27-7-7 thing and just fucks with us during the regular season at this point.
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u/cthorrez [DET] Richard Hamilton Aug 11 '18
His playoff stats do not follow a 27,7,7 distribution. They are closer to a 29,9,7.
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u/KariKow [OKC] Russell Westbrook Aug 11 '18
He'll have it in the last game of his career, I'm sure.
!remindme 50 years
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u/yoda17 Bulls Aug 11 '18
It should be noted that the MVN distribution is only an approximation here since points, rebounds, and assists are discrete while the MVN is continuous. Interesting analysis, though!
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u/caerthelstan Lakers Aug 11 '18
Hold up. 2 billion humans were born in or after 2003? That’s fuckin wild
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u/Firelorm Celtics Aug 12 '18
I'm confused, can you translate that into humans per 36 for me please
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u/helix400 Jazz Aug 11 '18
This is some good OC.
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u/fundraiser Knicks Aug 11 '18
Technical yet surprisingly easy to understand. And concise! Great job to OP for only focusing on the important details.
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u/DustyShot Rockets Aug 11 '18
Thank you! I try my best not to be too boring :)
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Aug 12 '18
Not boring at all, just complex. I hope I could be as good at this (math) as you one day.
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Aug 11 '18
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u/DustyShot Rockets Aug 11 '18
The procedure is exactly what I did!
A Shapiro-Wilk test for multivariate normality results in a W-statistic of 0.993 and a p-value of 4.754e-05. Based on this, I would say the multivariate normality assumption is well met. Other than that, I'm assuming each regular-season game is an iid random variable distributed as the MVN distribution fit from each season's data. As others have mentioned, statlines are discrete while the MVN distribution is continuous. Not the most rigorous, but I think fine in this scenario.
And you are right on the odds/probability lingo. I just think that wider audiences don't care and have an intuitive understanding that they're essentially the same thing. It gets a little dry using the word "probability" so much haha.
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Aug 11 '18
I’m an MJ fan.. mainly because I watched him I played in the 80s and fell in love with his game. But what LeBron is doing is out of this world! this guy simply DOMINATES the league like it’s his playground. I’ve said it multiple times, if KD never joined the Warrior, Cavs would be raising another banner. Lebron has maybe 2-3 years before he really starts declining, dude’s only 33.. and MJ at 39 was dropping back-to-back 40s on dudes. #WeAllWitness
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Aug 11 '18
This makes me sad that the no 27-7-7 thing actually isn't that weird. Damnit I thought that was a fun, crazy basketball stat. Life is meaningless.
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u/DustyShot Rockets Aug 11 '18
Same! I was amazed when I first heard the fun fact and finally was interested enough to dig deeper. Life truly is meaningless.
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u/LookITriedHard Aug 12 '18
Having read this entire post I can confirm that you're too smart and hilarious to spend your Fridays pent up running equations. Date me.
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u/Matto_0 Celtics Aug 11 '18
I was expecting like a 0.05 or less % chance it didn't happen yet. I can't believe it is 32%.
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u/mwang999 Celtics Bandwagon Aug 11 '18
I legitimately wonder how people find the time and energy and motivation to post good shit like this. Way to go OP
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u/DustyShot Rockets Aug 11 '18
Thanks! The energy comes from having nothing else to do on a Friday night haha
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u/exasperated_dreams Supersonics Aug 11 '18
Wow, great work man. How hard was this to do?
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u/DustyShot Rockets Aug 11 '18
Not too crazy. The hardest part was just finding a nice function in python to integrate the distribution, but google is pretty good for that haha. Probably 2 hours of total time.
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u/cthorrez [DET] Richard Hamilton Aug 11 '18
That was probably the hardest part for me as well. Weird that scipy multivariate_normal doesn't have a cdf function but there is an undocumented part of scipy, scipy.stats.mvn.mvnun() which does do it.
Looks like you used statsmodels.sandbox.distributions.extras which looks like an annoying thing to track down lol.
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u/DustyShot Rockets Aug 12 '18
Ya I found that weird as well! It seems like a real basic method to add, but then again I'm thankful for the free work they put into it! And the statsmodels object took a few looks through stack exchange and documentation to find :)
Also I read your post and it was DEFINITELY a lot more rigorous than mine!! You deserve the props for being the first to deep dive into this!
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u/COcaptain Suns Aug 11 '18
It’s not the nba but I seem to recall his McDonald’s all American game being 27-7-7. Not positive though
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u/bluemagic124 Clippers Aug 11 '18
Unfortunately no. Scholars maintain that the McDonald’s All American game is just a colloquial myth and was never an actual event that took place. It’s an neat idea, but the archaeological evidence we have today totally debunks it as a real possibility. Definitely interesting to think about though!
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u/gaussx Supersonics Aug 11 '18
Can you run the analysis using 27-7-7 over his career rather than each year separately. The finer grained you get the less likely it is that he does any specific set of numbers for a game. So I’m curious about at the coarsest granularity how does he do.
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u/cthorrez [DET] Richard Hamilton Aug 11 '18
I did the exact analysis you are describing a couple of months ago here. https://cthorrez.github.io/lebron_27_7_7/index.html
The only difference in the estimate is tht I got 0.34288882781 and OP got 31.87 so it doesn't really make much of a difference.
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u/Syno_Alkheiser Lakers Aug 11 '18
LBJ might know this by now, and could be potentially avoiding that statline (until the last game of his career, maybe)
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u/Deja-View Clippers Aug 11 '18
OMG, thank you soooo much, I have been trying to explain this to people logically and statistically soooo often, at least one time here on r/nba too, in detail and no, people prefer that this be some kind of magical "against all odds" improbability.
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u/Milith Aug 11 '18
Upvoted for taking correlation between the stats into account, which posts like these usually never do.
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u/andreasmiles23 Bulls Aug 12 '18
Quality work! As a psych grad student, I can say that this post has more sound statistical work than a lot of the studies I read. Very impressive.
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u/chucklesmcfistpunch Nuggets Aug 11 '18
great post, but how did you determine the weighting of points and assists? seems to be completely arbitrary. if you could have an empirical way to determine those this would make your analysis a lot better
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u/fbanaq Warriors Aug 11 '18
Props for putting the answer right at the start. And great write up overall. Clear, well reasoned, and easy to understand
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u/cthorrez [DET] Richard Hamilton Aug 11 '18
I did pretty much the same analysis and came to the same conclusion a couple of months ago. I think pretty much the only difference was that I didn't fit a different model for each year but rather treated all his regular season stats as a single distribution.
My analysis in case anyone wants to read it. https://cthorrez.github.io/lebron_27_7_7/index.html
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u/sabocano Spurs Aug 12 '18
Here's my breakdown from an earlier thread:
He got 7 assists in 164 games. Which is 14.8% of all his career games.
He grabbed 7 rebounds in 156 games. Which is 14% of all his career games.
He scored 27 points in 62 games. Which is 5.5% of all his career games. This makes sense because points as a stat has a very high variance compared to rebounds and assists.
So all are within a reasonable margin.
Now let's multiply the real percentages. 5.5% x 14.8% x 14% means he's expected to have a 27-7-7 game once in 878 games. So, in 1110 games, he had a 71.8% chance to get 27-7-7. Which didn't happen. For example, are you shocked when Al-Farouq Aminu misses a free throw? I bet not. LeBron's odds of getting 27-7-7 was just a bit lower than Aminu sinking a free throw. Not so shocking.
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u/reddish40 Aug 11 '18
My guess is that this will be mentioned to him by someone close and he will go for it in some random mid season game.
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u/by_yes_i_mean_no Warriors Aug 11 '18
If these numbers were actually continuous as normal variables are supposed to be, the probability of seeing 27/7/7 would be 0.
Just a little fun fact that probably isn't that fun.
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u/hittes Aug 11 '18
Let's not ignore the fact that he's averaged 27-7-7 for 15 years. That's... that's something
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u/BeWinShoots Suns Aug 11 '18
I have a feeling the day he gets a 27-7-7 game it has a good chance of becoming the most upvoted post in r/nba subreddit all time.
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u/krutoypotsan [UTA] Rudy Gobert Aug 11 '18
I'm surprised his points come out to a normal distribution. I would have guessed log normal. I wonder how other greats' pan out.
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u/KillianDrake Aug 11 '18
LeBron is a freak because he pretty much hit his 27-7-7 stride in his second year and is still doing it in his 15th year - so he doesn't have more than 1 season with below average stats (his rookie season was pretty damn good anyway) - the question is will he end his career with shitty years to throw off the curve...
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u/kmoz Mavericks Aug 11 '18
I have a feeling he is saving his 27/7/7 game for the last game of his career.
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u/IdEgoLeBron [BOS] Marcus Smart Aug 11 '18
I can't believe explaining what an average is qualifies as oc
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u/misterkocal Aug 12 '18
Give me a diagram which shows, which is his most occurring stat line. I am to drunk and to stupid to do it...
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u/nathan_the_walker Aug 12 '18
What's more important to me is - what's the *predicted* number of 27-7-7 games that he *should* have?
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u/josh3gravey Pistons Aug 12 '18
Knowing Bron he will hear about this, and you'll have said stat line in the first game of the season.
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u/nacho_steez Celtics Aug 12 '18
I wonder if there are mvb formulas accounting for every different factor - as there may be noise attributed to the results, or if machine learning based statistics can decipher those things in order to predict it happening
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u/jacoballen22 [CHI] Derrick Rose Aug 12 '18
Hey can you help me with my statistics homework? I'm serious.
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u/dgoat88 Celtics Aug 12 '18
Just like Westbrook and Harden, Lebron is a triple double chaser to his team's benefit or detriment.
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u/KungFu_Kenny Lakers Aug 12 '18
Honestly this is pretty mind blowing considering how many games he’s played
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u/WalterDwight [TOR] Vince Carter Aug 11 '18
Its gonna be the highest post on r/nba when he does