The purpose of the Statistical Scrutiny series is to attempt to explain or contest a player's performance evidenced by main stream statistics through an evaluation of statistics which do not often appear in a boxscore, for lack of a better term "sabermetric statistics." The "sabermetric statistics" measure results which are crucial to the player's overall performance, but often not included in the main stream stats, such as how often a player walks, strikes outs, hits a line drive, etc.
Since homering the first three games of the season, Ian Kinsler's batting average dipped as low as .170 before rising to .250 after a 4-4 game against the Angels. In the course of his current 5 game hitting streak, Kinsler has bumped his batting average 41 points. The question is whether Kinsler's performance was reflected by his early season statistical struggles or by his recent stellar performance.
When looking into some of the lesser referenced stats, Kinsler is having one of his "best" seasons. His walk percentage is at a career high; his strikeout percentage is at a career low; his power, as reflected by the stat "isolated power", is a career high; and his percentage of swings and misses is not only a career low, but is also tied for second best in all of baseball this season.
The obvious question is: why do Kinsler's mainstream stats, and his batting average in particular, not reflect the season his "sabermetric" stats indicate he's having? The answer can be found by evaluating Kinsler’s batting average on balls in play (“BABIP”). BABIP measures batting average exclusive of homeruns, strikeouts and sacrifices. BABIP can vary wildly and is also greatly affected by luck, especially in small sample sizes.
Several different statistical measures have been developed to “predict” a player’s BABIP. Put another way, these measures attempt to isolate the “luck” factor contained within BABIP. Two of these predictors are the line drive percentage method ("LD% method") and "Studes" method, both developed by Dave Studeman.
The LD% method is the simplest of the BABIP predictors. All that is required to predict BABIP with this method is adding .120 to a player’s line drive percentage. This method is based off the maxim that line drives become hits more often than other batted balls. Accordingly, a player who hits a high percentage of line drives will have a similarly high BABIP.
The Studes method is based on similar principles but it also seeks to include a player's propensity for flyballs, groundballs and strikeouts into the equation. While the strikeout rate does not have a direct link to BABIP, it does provide some additional corollary input to the equation.
For 2011, Ian Kinsler has a BABIP of .250. Based on the LD% method, Kinsler’s BABIP should be .289, which would equal Kinsler's career BABIP number. Based on the Studes method, Kinsler's BABIP should be .270. According to these prediction methods, bad luck may have lowered Kinsler’s BABIP at this point in the season by between 20 and 40 points.
If Kinsler’s BABIP was .280, the average between the two predicted values, his current batting average would be .297; his current on base percentage would be .386; and his current slugging percentage would be .499, assuming all the "added hits were only singles. The resulting .885 OPS would rank second among major league second baseman. The fortunate thing for Mr. Kinsler, and for the Rangers, is that the luck element of BABIP tends to even out over a season. The most recent five game stretch might be the first signs that Kinsler’s season will, in fact, be among his career best.