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Premium Article Five Burning Questions (10/23)

October 22, 2012
Valuing the Preseason
A Bayesian Approach

by Kevin Pelton


There are two different ways to view the preseason, and they're both incorrect.

At one extreme, reading too much into player performance is dangerous for a variety of reasons besides comparing Jeff Green to James Worthy. The problems with preseason play are obvious. Not only are players not being used the same way they will during the regular season, the small sample size makes fluky performance likely. An eight-game stretch of the schedule can be misleading enough, and limited minutes only exacerbate the issue.

At the same time, the skeptic who writes off everything we see during the preseason is mistaken too. There is value to how players perform in game situations, especially when we're seeing units like the Lakers' star-studded starting five together for the first time. More simply, every time players step on the court they add some data to their track record.

My most in-depth study of preseason statistics is now four years old, but I see no reason to believe the conclusions have changed. Here's what I found:

I took the group of slightly more than 200 players who played at least 250 minutes in both the 2006-07 and 2007-08 regular seasons and at least 100 minutes in the 2007 preseason. Again, preseason performance proved surprisingly robust. The correlation of 2006-07 and 2007-08 per-minute Win% was .788; by comparison, preseason Win% had a .583 correlation with 2007-08 performance.

The more interesting question might be this: Does preseason performance offer us any additional information? After all, if what we're seeing is simply that better players play better no matter the circumstance, we already can identify these players based on their previous regular-season performance. To look at the matter this way, I created a regression seeking to predict 2007-08 regular-season performance from 2006-07 performance and 2007 preseason performance. Combining the two improves correlation slightly over 2006-07 performance alone, up to an r of .814. Looking at the coefficients on the two variables indicates that preseason Win% is about a fourth as useful as a predictor as Win% the previous season.

Since even I don't calculate player win percentages while watching games, I think it's more important to translate these results into a mindset for considering the preseason. It matters, but it's not nearly as meaningful as a player's track record. What the numbers indicate is that we ought to approach the preseason, like anything else, in Bayesian fashion. When the results are consistent with what we already know, they strengthen our conclusion.

I think this approach is particularly useful in the case of rookies. While NBA fans are just getting introduced to Jared Sullinger's heady, polished style of play, Sullinger's ability to play effectively despite giving up height to opposing big men is nothing new to those of us who watched him regularly at Ohio State. To the extent there was some skepticism about whether Sullinger would be able to translate that against elite athletes, his strong preseason tells us something valuable by reinforcing the assumption that he was a steal in the draft.

Sullinger's teammate, Green, is the counterexample. As ESPN Insider's John Hollinger pointed out on Twitter Saturday, Green's preseason performance really isn't that different from what he's done in the past on a per-minute basis. Even if Green was playing at a much higher level, his track record is well established over five seasons. There are reasons to believe that Green may be capable of more this season, as he gets a training camp with the Celtics for the first time and could spend more time on the wing than he has in years. However, it's going to take some time for Green to overcome his lengthy history of below-average play.

The most interesting example might be a player like Perry Jones III. Like Sullinger, Jones comes with relatively less certainty because of the transition from college to pro. The difference is that Jones' statistical track record is poor and never matched his obvious potential at Baylor. Now Jones, who nearly dropped out of the first round entirely, is challenging for a spot in the Oklahoma City rotation by averaging 18.3 points on 69.2 percent two-point shooting. The conflicting data means I no longer have any strong feelings about what Jones might be able to contribute this season. At the same time, we're still talking about 31 shots from the field. Jones is also hitting 14.3 percent of his free throws (1-of-7), a handy reminder that his numbers have hardly normalized.

It's easy to get seduced by preseason play. Since it's the first we've seen any of these players in months, there's a bit of "what you see is all there is" at play in elevating results into something more meaningful than it really is. Still, be careful not to overcorrect for this tendency. There is some meaning to the preseason. The trick is sorting the useful results from the misleading ones, and that's part science and part art.

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Kevin Pelton is an author of Basketball Prospectus. You can contact Kevin by clicking here or click here to see Kevin's other articles.

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2012-10-22 - Valuing the Preseason: A Bayesian Approach
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