Looking with Envy at Baseball Stats?

Posted on August 19, 2009 by


People who study statistics in basketball often look with envy at the numbers in baseball.  A hitter in baseball stands at the plate by himself.  Consequently, the numbers he generates is primarily about the actions he takes.  In contrast, basketball players run with four other players. The interaction between those players appears to diminish the meaning of the numbers generated.

The sport of football highlights the importance of interaction effects. The numbers we see for quarterbacks and running backs are very inconsistent across time.  This tells us that numbers in football are not just about the player, but also about the player’s teammates.  Consequently, forecasting the future in football – as Brian Burke recently noted – is very difficult.

People often argue that basketball is very much like football.  To illustrate this argument, just recently we discussed the impact Trevor Ariza will have on the Houston Rockets.  Ariza posted a 0.192 WP48 [Wins Produced per 48 minutes] for the Lakers in 2008-09.  Such a mark is nearly double what we see from an average player, indicating that Ariza will help the Rockets in 2009-10.  People argued, though, that Ariza had Kobe Bryant as a teammate last year; and without Kobe in Houston, Ariza won’t be nearly as productive.

Although this story was told, the evidence suggests otherwise.  Here is what Ariza did in 2007-08 and 2006-07 (much of which was spent in Orlando, without Kobe).

2007-08: 0.225 WP48

2006-07: 0.217 WP48

These numbers suggest that what Ariza does on the court is really about Ariza.

Now let’s think about baseball.  The Detroit Tigers just signed Aubrey Huff.  Last season Huff posted a 0.912 OPS, a mark that ranked 15th among 147 qualified Major League Baseball hitters.  In other words, Huff ranked in the top 10% in baseball.  This suggests that Huff is one of the most productive hitters in all of baseball, and therefore, fans of the Tigers – like me — should be thrilled.

When we look at the numbers from this year, though, it’s a very different story.  Huff’s OPS in 2009 (prior to coming to Detroit) is 0.726.  This mark ranks 136th out of 147 qualified hitters, placing Huff in the bottom 10% in the league.

If we look over Huff’s career we see a similar pattern.  Here is Huff’s OPS and ranking from 2003 to 2007:

2003: 0.922 OPS, 19th (top 17%)

2005: 0.853 OPS, 45th (top 41%)

2006: 0.813 OPS, 77th (top 60%)

2007: 0.779 OPS, 103rd (top 65%)

The past six years of Huff’s career demonstrates a great deal of inconsistency.  So which Huff did the Tigers add? Are they getting the player ranked in the top 10% in 2008? Or is it the player ranked in the bottom 10% in 2009? It seems likely that even Huff isn’t sure.  Huff’s job is to hit a round ball with a round stick, and that’s simply not an activity that can be predicted easily.

In the Wages of Wins we noted that the stories of Ariza and Huff are not unique.  The numbers attached to players in basketball are simply more consistent than the numbers we see in baseball. And this means that decision-making should be easier in basketball.  For example, the Portland Trail Blazers just signed Brandon Roy – a player ranked in the top 10% in the NBA [in WP48]– to a long-term contract.  If Roy stays healthy, the Blazers can count on him remaining a top player in the game.  And that will probably be true, regardless of his teammates.  A similar story can be told about Chris Paul, LeBron James, and Dwight Howard.  If these players stay healthy, teammates can come and go and these players will still rank towards the top of the league.  Likewise, a player like Jamal Crawford – who has consistently placed in the bottom half of the league rankings – is not going to transform into one of the top players in the game now that he is with the Hawks. 

If only people in baseball had the data we see in basketball.  Maybe the recent history of the Tigers would then be quite different.  The Tigers finished in second place with 88 wins in 2007.  They then added $40 million in payroll, and proceeded to lose 88 games and finish in last place.   Given what we know about inconsistency in baseball, this result doesn’t necessarily mean that the Tigers didn’t know what they were doing.  The Tigers might have simply suffered the wrath of baseball’s inconsistency.

In contrast, the Pistons added Allen Iverson in 2008-09 and announced that such a move would help the team contend.  The data, though, suggested fans of the Pistons were about to be disappointed (and eventually they were).

Hmmm…let’s think about this again.  The Tigers have a built in excuse when an entire season goes to hell.  The Pistons – because their data is better – don’t get to use this same excuse (although they try).  So maybe people in basketball should hope for the data we see in baseball.  


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Our research on the NBA was summarized HERE.

The Technical Notes at wagesofwins.com provides substantially more information on the published research behind Wins Produced and Win Score

Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:

Simple Models of Player Performance

Wins Produced vs. Win Score

What Wins Produced Says and What It Does Not Say

Introducing PAWSmin — and a Defense of Box Score Statistics

Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.