Home Run Derby: Does it ruin swings? December 15, 2010
Posted by tomflesher in Baseball, Economics.Tags: Baseball, baseball-reference.com, Chris Young, Corey Hart, David Ortiz, Hanley Ramirez, home run derby, home runs, Matt Holliday, Miguel Cabrera, Nick Swisher, Vernon Wells
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Earlier this year, there was a lot of discussion about the alleged home run derby curse. This post by Andy on Baseball-Reference.com asked if the Home Run Derby is bad for baseball, and this Hardball Times piece agrees with him that it is not. The standard explanation involves selection bias – sure, players tend to hit fewer home runs in the second half after they hit in the Derby, but that’s because the people who hit in the Derby get invited to do so because they had an abnormally high number of home runs in the first half.
Though this deserves a much more thorough macro-level treatment, let’s just take a look at the density of home runs in either half of the season for each player who participated in the Home Run Derby. Those players include David Ortiz, Hanley Ramirez, Chris Young, Nick Swisher, Corey Hart, Miguel Cabrera, Matt Holliday, and Vernon Wells.
For each player, plus Robinson Cano (who was of interest to Andy in the Baseball-Reference.com post), I took the percentage of games before the Derby and compared it with the percentage of home runs before the Derby. If the Ruined Swing theory holds, then we’d expect
The table below shows that in almost every case, including Cano (who did not participate), the density of home runs in the pre-Derby games was much higher than the post-Derby games.
Player | HR Before | HR Total | g(Games) | g(HR) | Diff |
Ortiz | 18 | 32 | 0.54321 | 0.5625 | 0.01929 |
Hanley | 13 | 21 | 0.54321 | 0.619048 | 0.075838 |
Swisher | 15 | 29 | 0.537037 | 0.517241 | -0.0198 |
Wells | 19 | 31 | 0.549383 | 0.612903 | 0.063521 |
Holliday | 16 | 28 | 0.54321 | 0.571429 | 0.028219 |
Hart | 21 | 31 | 0.549383 | 0.677419 | 0.128037 |
Cabrera | 22 | 38 | 0.530864 | 0.578947 | 0.048083 |
Young | 15 | 27 | 0.549383 | 0.555556 | 0.006173 |
Cano | 16 | 29 | 0.537037 | 0.551724 | 0.014687 |
Is this evidence that the Derby causes home run percentages to drop off? Certainly not. There are some caveats:
- This should be normalized based on games the player played, instead of team games.
- It would probably even be better to look at a home run per plate appearance rate instead.
- It could stand to be corrected for deviation from the mean to explain selection bias.
- Cano’s numbers are almost identical to Swisher’s. They play for the same team. If there was an effect to be seen, it would probably show up here, and it doesn’t.
Once finals are up, I’ll dig into this a little more deeply.
Micah Owings and Cobb-Douglas Production July 22, 2010
Posted by tomflesher in Baseball, Economics.Tags: Brooks Kieschnick, Cobb-Douglas function, David Ortiz, Micah Owings, Reds, run production
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Micah Owings, who is one of the best two-way players in baseball since Brooks Kieschnick, was sent down to the minors by the Cincinnati Reds yesterday. As big a fan as I am of Micah (really, look at the blog), I think this was probably the right decision.
Owings was being used as a long reliever. For a big-hitting pitcher like Micah, that’s death to begin with. Relievers need to be available to pitch, so the Reds couldn’t get their money’s worth from Owings as a pinch hitter, since he wouldn’t be available to re-enter the game as a pitcher unless they used him immediately. They also weren’t getting their money’s worth as a pitcher, since, as Cincinnati.com notes, the Reds’ starting pitching was doing very well and so long relief wasn’t being used very often.
Letting Owings start in AAA will give him the best possible outcome – he’ll have regular opportunities to pitch, so he won’t rust, and he’ll get to bat at least some of the time. Owings needs to be cultivated as a batter because that’s where his comparative advantage is. I doubt he’ll ever be at the top of the rotation, but he could be a competent fifth starter. If he pitches often enough to get there, he’ll add significant value to the team in terms of his OBP above the expected pitcher. He’ll get on base more, so he’ll both advance runners and avoid making an out.
A baseball player is a factory for producing run differential. He does so using two inputs: defensive ability (pitching and fielding) and offensive ability (batting). In the National League, if a player can’t hit at all, he’s likely to produce very little in the way of run differential, but at the same time, if he’s a liability on defense, he’s not likely to be very useful either. Defense produces marginal runs by preventing opposing runs from scoring, and offense produces marginal runs by scoring runs. Having either one set to zero (in the case of a pitcher who can’t hit at all) or a negative value (an actively bad pitcher) would negatively affect the player’s run production. This is similar to a factory situation where labor and equipment are used to produce goods, and that situation is usually modeled using a Cobb-Douglas production function:
with Y = production, z = a productivity constant, K = equipment and technology, L = labor input, and is a constant between 0 and 1 that represents relatively how important the input is. K might be, for example, operating expenses for a machine to produce widgets, and L might be the wages paid to the operators of the machine. This function has the nice property that if we think both inputs are equally important (that is,
= .5) then production is maximized when the inputs are equal.
In general, production of run differential could be modeled using the same method. For example:
where P = pitching contribution, F = fielding contribution, B = batting contribution, and and
are both between 0 and 1 and would vary based on position. For example, David Ortiz is a designated hitter. His pitching ability is totally irrelevant, and so is his fielding ability outside of interleague games. The DH’s
would be 0 and his
would be very close to 0. On the other hand, an American League pitcher would have an
very close to 1 since pitcher fielding is not as important as pitching and his hitting is entirely inconsequential in the AL. Catchers would have
at 0 but
much higher than other positions.
The upshot of this method of modeling production is that it shows Owings can make up for being a less than stellar pitcher by helping his team score runs and be a considerably better investment than a pitcher with a slightly lower ERA but no run production.
Measurability and Derek Jeter February 26, 2009
Posted by tomflesher in Baseball, Economics.Tags: basketball, Daryl Morey, David Ortiz, Derek Jeter, economics, Economics haiku, plus-minus, Shane Battier
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Skip Sauer at The Sports Economist had an interesting post about Houston Rockets forward Shane Battier’s lack of traditional stats and Rockets GM Daryl Morey’s belief in him regardless. Morey’s use of an adjusted plus-minus stat to justify hiring Battier is reminiscent of Billy Beane’s attention to on-base percentage in building the Oakland As as detailed in Moneyball.
What I take from Sauer’s post is that plus-minus is a surrogate variable for ability to be a team player. That opens the broader question of what can be measured and whether nonmeasurable statistics are ever useful in building a team.