Position Players on the Hill
October 28, 2009 1 Comment
Since the Laws of Voros McCracken were published way back in the early 21st century, baseball statistical analysts have sought to firmly establish whether or not pitchers have any control over their batting average on balls in play. However, one confounding variable has always been selection bias, whether the pitchers who make it to the major leagues have some special control over their BABIPs and that the players who have control are not in the majors because they can’t control this variable. As a result, the assertations of statistical analyses don’t have a set “control group” through which to analyze their players. If we had a reliable control group of players to test this BABIP theory against, we would have a clearer picture of whether or not these players can control their BABIP.
Therefore, I thought it would be interesting to see the results of position players who take the mound. Certainly, they fit the criteria that we want in a control group. For one, they must certainly be worse (though, it’s possible that they are better than minor league pitchers) than minor league pitchers. Second, they pass the “scout selection bias” that goes along with pitchers who make the major leagues, that they were not selected by scouts or player analysis experts to play in the majors. Though, it should be noted that many of these pitchers do have some sort of pitching experience, and should have enough athletic ability to post good velocities. In addition, they are selected by their managers as competent pitchers. Either way, it is a reasonable assumption that these pitchers are far worse than their major league counterparts and that they do not fall under the “attrition” bias, that their poor performance will shut them out of the league, as happens with many players with poor debuts.
Alas, let’s get on to the results. The sample was taken from all player seasons in the last 15 years, where pitchers threw fewer than 10 innings and played as a position player for more than 50 games. The table is compiled at the end of the page and was derived from statistics at the Baseball Databank. The total sample comprised 54 innings.
I’ll leave the results here then let you guys talk it over.
First, the BABIP. I still think that I may have totaled the number of balls in play wrong, so I’d love for someone else to check it for me. However, the total BABIP for the sample was .269. This was especially intriguing given that it was actually lower than the standard .300. I was hoping to see a number in the upper .300s, which would mean that there would be a spectrum of BABIPs that could include the results of lesser pitchers. It’s still possible that there is such a spectrum. However, this study did not lend evidence to this effect.
Second, was the relative skill of the pitchers. Don’t fear, just because the BABIP didn’t pan out as expected doesn’t mean that the rest of the numbers didn’t as well. First, the pitchers compiled a total 7.33 ERA, with a 7.66 BB/9 rate and 4.0 K/9 rate. These results were a little surprising, as I expected the ERA to be much higher than 7.33, at some place in the teens. In addition, I thought that the K rate would be much lower, as I didn’t think that MLB hitters struck out against position players at such a frequency. Maybe it isn’t so embarrassing to be retired via the K by a non-pitcher, or maybe players should just be embarrassed every time they are K’d by Carlos Silva.
Without fly ball data, I was unable to assess the HR/FB rates. However, they were not all that high, as 9 home runs were registered in 178 balls in play. However, without fly ball data, it is difficult to say the effect. However, if we guess and say that 37.07 percent of BIP were fly balls (for a total of 66 fly balls), this means that 9/ 66+9 balls left the yard, or 12 percent of fly balls – just 1-2 percent worse than the league average for MLB pitchers. Strange.
With such a small sample size, it is yard to pull any concrete results from the data. However, it does seem to lend evidence against the notion that there is a BABIP and HR/FB selection bias against major league pitchers.
Beyond that, I’ll let you readers discuss.
Here are the sums of the data:
BIP: 178 H on BIP: 48 BABIP .26966
HBP: 6 H: 57 IPouts: 162
BFP: 263 HR: 9 BB: 46
SO: 24 IBB: 0 ER: 44
IP: 54 K/9: 4.0 ERA: 7.3333
And, one last note, I removed Rick Ankiel from the results, as he was formerly an accomplished pitcher, but still crept into the query.