For all your fancy-pants statistical needs.

Praise for The Basketball Distribution:

"...confusing." - CBS
"...quite the pun master." - ESPN

Y2YWCF: A Quick Note on Regression to the Mean

"They gained Kevin Durant and they're going to win LESS games? No way!!"


This logic on its own is incorrect for many reasons. We will call it the Year to Year Win Correlation Fallacy (or Y2YWCF* for short).The most important reason this statement should be is because of is regression to the mean.

Single-year-win totals are subject to variance - for this example, we would statistically assume Warriors had some things go their way they probably won't have this season.

Here's the breakdown of year-to-year win totals, via basketball reference, since the 30-team ERA, (2011 adjusted for lockout):

(By prior year and following year, I just mean one year and the following year)

Using this chart, we can see how a typical team regresses.

In fact, a 73-win team would be expected to only win 61 games the following season!
And from a basic stats perspective**, adding Kevin Durant to a stacked team would not net an additional 12 wins.

In this dataset, 49% of all NBA teams regress towards 41.

"How many games will the Miami Heat win this season"
Ok. Here's some projections:

Year to year correlation (from the formula used in Part I):

My initial projection (a blend):


Most rating systems obviously had the Heat lower after losing their best player of ever, Dwyane Wade, for pride reasons. His BPM rating put his wins above replacement at +4.32 last season.

Miami also will probably have zero playing time from Bosh for (mostly?) health reasons, who was +4.86 Wins Above Replacement:

Oh yeah also Luol Deng is a Laker now. Last season he had +6.21 Wins Above Replacement for Miami.
FiveThirtyEight's Projection after 1 Win:

So....35 is still looking pretty good. Unless you're a Heat fan.

*- I was hoping for something catchier GSBLEWA31LEAD but I couldn't find a good way to make it fit.

*- Also from an advanced stats perspective (NetRating). The Warriors' Net Rating last season was lower than we would expect from the 73-win GSW team last yr (or you could say, their Win% was higher than their NetRtg expects). This is another important factor that we expect to regress, which I kind of mentioned at the beginning.

2016 NCAA Tournament Bracket Cheat Sheet (UPDATED 3/17)

2016 NCAA Tournament Bracket Cheat Sheet (UPDATED GOOGLE DOC 3/17)

Each team is ranked by their expected # of wins.

-Odds come from 10,000 simulations of the tournament, taking into account injuries, Four Factors adjustments, pace, and if the teams have a very close rating - free throw%.  I have updated the sheet to include an adjustment for shortened lineups (i.e. best players playing).

-Sleeper Rating is a rating from 1 to 5 that measures total volatility above Expected Wins, with successive rounds being weighted twice as much (i.e. using ESPN scoring). It's a good measure for teams with statistical ability to go further than my Exp. Wins suggests.

LARGE POOL PICK VALUE = (a team's odds  -  the public's expected odds )x total point value
This highlights high-value picks versus the field (namely, ESPN's bracket challenge)

VALUE + EXPECTED POINTS = Total Point Value + Large Pool Pick Value
This is a slightly more conservative version of "Large Pool Pick Value"

All statistics from except injury estimates from
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I wish my heart were as often large as my hands.