Monday, May 16, 2011

The Anti-Infield Fly Rule

The infield fly is logically the easiest batted ball to turn into an out in baseball. At this point in the season, eleven hitters with enough at bats to qualify for the batting title have yet to hit an infield pop up this season.

Ranked in order of number of at bats, here they are:

  1. Howie Kendrick, 164 at bats

  2. Michael Young, 158

  3. Derrek Lee, 154

  4. Elvis Andrus, 146

  5. David Wright, 146

  6. Yunel Escobar, 143

  7. Brandon Phillips, 142

  8. Joey Votto, 139

  9. Jose Tabata, 124

  10. Jack Cust, 117

  11. Gerardo Parra, 109

Two Rangers make the list with Michael Young at #2 and Elvis Andrus tied #4.

As a bonus tidbit, only one of the eleven has yet to homer, Jack Cust. Over his career, Cust has hit a homer every 19.5 at bats, which is only exceeded among the players on the above list by Votto's homer every 18.5 at bats.

Saturday, May 14, 2011

Statistical Scrutiny: The Sour Luck of Ian Kinsler

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.

Observations on Leonys Martin's Second Game

Leonys Martin's second game failed to match his first stat line: 3 for 5 with two doubles and a stolen base, but it did provide some additional insight into his game. Martin exhibited the ability to be a tough out, a drag bunt with promise, a good eye and some situational hitting.

Batting lead off for the Roughriders, Martin put together a nine pitch at bat in which he in which he spoiled four straight solid pitches after running the count to 2-2. On the ninth pitch, Martin grounded out to short, but he made a routine play fairly close by hustling down the line.

Martin's second at bat only lasted one pitch, a failed drag bunt attempt. He had also attempted a drag bunt in his first at bat as well. The first attempt was a bit late and resulted in a foul back to the backstop. In his second attempt, Martin dropped the bat too far resulting in a harmless pop out to the first baseman. While he hasn't perfected the timing of the drag bunt, he did show good footwork and a quick jump out of the box on both occasions. With a bit more work, he could certainly turn that into an asset for his offensive game.

Both Martin's third and fourth at bats came with runners in scoring position. In the fifth, Martin batted with a runner on third and only one out and he was able to put the ball in play and bring in the run. In the seventh, Martin batted with runners on first and second. After running the count to 3-0, Martin took a called strike, which appeared to be ball four. On the next pitch, Martin grounded out again, but both runners were able to advance.

Overall, Martin went 0-4, but each at bat flashed the tools of a very promising hitter.

Wednesday, May 11, 2011

Rangers Starters Impressing with Fastball Velocity

 The Texas Rangers have quite a collection of power fastballs in their rotation as Alexi Ogando (4th overall), Derek Holland (tied for 12th overall) and Matt Harrison (tied for 19th overall) represent the only trio from the same team in the top 20 starters in average fastball velocity.

Even more distinct might be the presence of two Ranger lefties at the top of that list.  The top lefty starters in average fastball velocity are:  
  1. David Price, TB - 94.5 mph
  2. Derek Holland, TEX - 93.1 mph
  3. Clayton Kershaw, LAD - 93.1 mph
  4. Jorge de la Rosa, COL - 92.9 mph
  5. CC Sabathia, NYY - 92.7 mph
  6. Matt Harrison, TEX - 92.6 mph
  7. Madison Bumgarner, SF - 92.6 mph
Other than the Rangers, the only other teams with as many as two pitchers in the top 20 are the Mariners with Michael Pineda (#1) and Felix Hernandez (#8) and the Giants with Tim Lincecum (#14, tied) and Madison Bumgarner (#19, tied).

Such Is Baseball...

"A good friend of mine used to say, 'This is a very simple game. You throw the ball; you catch the ball; you hit the ball. Sometimes you win; sometimes you lose; sometimes it rains.' Think about that for a while." – Bull Durham

Baseball is a simple game. Yet, in more than a century of play, baseball has displayed a power of randomness that belies its simplicity. The game's design compiles a series of seemingly unrelated actions. Individually, each those actions are simple, but compounded they offer true complexity.

The paradox of this simplistically complex nature is why the game has captured imaginations for over a century. The game is cruel, yet fair. It’s ordered, yet unpredictable. It’s transparent, yet deceptive. By its very nature, baseball provides metaphors for similar paradoxes in life.

The brilliance of baseball exists in the unending attempts to quantify its simple transactions into a formula to predict its complex results. For decades, statistical analysis has been enhanced to increase the accuracy of these predictions, all the while enhancing the temptation to solely rely on the statistics, which can never truly capture the paradox of the game.

As my interest in baseball's nature has grown, I have developed a true respect for the game’s resistance to being "understood." In similar fashion, “life” presents a complexity based upon a series of seemingly simple actions, and in doing, resists being understood. Arising from this resistance is the idea of “C’est la vie”…such is life.

The intent of this blog will be to seek to understand the game: its paradoxes, its statistics, and its results. Without question, this intent will be stymied by the inevitable resistance to understanding, and when that occurs…

Such is Baseball.