Advanced Stats and Your Boston Celtics


Given all the debate on how good (or Bad) the Celtics are going to be. I decided to settle the discussion once and for all with some advanced stats. Or at least add a little fuel to the debate.

First the stats I used (or skip below if you just want the answer):

xRAPM- This is an advanced adjusted plus minus stat. The version here comes from Nathan Walker at Basketball Distribution. He used three years of data and an aging factor.

ASPM- This a box score based stat developed by Daniel Meyers. I like this one, in part because it did the best in an independent study in terms of both consistency and predicting, though only narrowly. It's also pretty intuitive. I used two years of ASPM ratings weighted by minutes and giving more weight to last year than the prior year. I also added an aging factor.

Win Shares- Box score stat developed by Dean Oliver. I used two years of ratings and an aging factor.

Wins Produced- Box score stat developed by Dave Berri that loves rebounds. I used a projection by Arturo Galleti at Wages of Wins, using three years of ratings weighted by minutes and an aging factor.

EZPM- Evan Zamir's Play by Play data based stat. This one is sort of complicated, but it's the only one using play by play data. I only had one year of data and applied an aging adjustment.

Wisdom of Crowds- I included the ESPN projection just because the stats don't include the unbalanced roster, coaching change or 'rebuilding' factor. Not sure if the ESPN projection qualifies as wisdom or crowds, since there maybe a herding issue with writers wanting to go along with the crowd. But, here it is.

My assumptions:

I had to assign minutes so made some guesses based on a notional depth chart. Also, made some allowances for time missed through the season. For example, even if Rondo comes back on opening day, I'd expect him to have to take some time during the year. So even if he plays 36 minutes when he's available, 82 game average would be lower.

My first take I accidentally gave the Celtics more minutes than are allowed and we won more games. Maybe in the post Stern era we can get some 6 on 5 quarters for our guys.

Minutes matter, with every stat if I distributed them evenly the Celtics project worse.

Guys who didn't play in the NBA. For Olynyk and Pressey I compared them to other rookies I thought might be similar for each stat. I am projecting Olynyk to be a good rookie, which still gives him below average NBA player numbers. Pressey I put as below average rookie, though I hope I am wrong. For Vitor Faverani, I looked at his Europe stats and assumed he would fair worse against NBA competition.

The numbers:

The range came out surprisingly tight, 29 to 40 games, with an average of 37 wins. This isn't as terrible a team as many national writers assume, but certainly not great.

Name xRAPM Position Minutes ASPM WS WP EZPM ESPN Crowd
Avery Bradley -1.1 SG 21.6 -2.17 0.062 0.024 -2.49
Brandon Bass -2.1 PF 16.8 -1.06 0.112 0.081 -5.4
Courtney Lee -1.5 SG 16.8 -0.54 0.082 0.104 -0.12
Gerald wallace 1.7 SF 14.4 1.03 0.086 0.128 0.32
Jared Sullinger -0.2 PF 24 0.21 0.167 0.137 0.87
Jeff Green -1.4 SF 28.8 -0.86 0.099 0.053 -0.64
Jordan Crawford -2.6 PG 7.2 -3 0.049 -0.013 1.42
Keith Bogans -3.3 SF 4.8 -2.5 0.016 0.081 -3.83
Kelly Olynyk -0.6 PF 19.2 -0.4 0.055 0.04 -0.4
Kris Humphries -0.6 C 21.6 -2.29 0.114 0.191 -0.42
Marshon Brooks -3.5 SG 7.2 -2.3 0.055 0.062 1.22
Phill Pressey -2.65 PG 9.6 -2.65 0.004 -0.013 -2.5
Rajon Rondo 3.3 PG 28.8 2.24 0.115 0.225 2.99
Vitor Faverani -1.9 C 19.2 -1.9 0.041 0.04 -1.9

39 240 39 36 39 40 29

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