The Effects of Luck: Lucky Hitters
In this series, Tyler Wasserman takes a look at which players were most affected by luck in 2011. In Part 2 of this 4 Part series, he examines which hitters should see significant declines in 2012 due to exceptional luck in 2011. Each player’s stats shown are 2011 (AVG/OBP/SLG/wRC).
Part 1 - Unlucky Hitters
Emilio Bonifacio (.296/.360/.393/85)
As we saw in the first part of this series, the main stat for luck is BABIP, and Bonifacio had the 3rd highest BABIP in all of baseball last year at .372. While he does have a very nice .339 career BABIP, .372 is simply unsustainable. This is especially true given the fact that he’s had a ground ball rate above 50% every season. Look for his BABIP to regress to around his career number, with his batting average and OBP following towards his career marks of .269 and .328 respectively.
Read MoreThe Effects of Luck: Unlucky Hitters
In this series, Tyler Wasserman takes a look at the players most affected by luck in 2011. In Part 1 of this 4 Part series, he’ll examine which hitters should see significant improvement in 2012 due to poor luck in 2011. Each player’s stats shown are 2011 (AVG/OBP/SLG/wRC).
Mark Teixeira (.248/.341/.494/101)
In 2011, Teixeira fell victim to a measly .239 BABIP compared to a .296 career BABIP. His batted ball percentages were in line with his career averages, with a slightly higher FB % and lower GB % than usual for him. This is a good sign, as it means the higher number of ground balls is not the cause of the horrid BABIP, which was the 3rd worst in all of baseball. His 11.1 BB % is virtually the same as his career 11.5 BB %, and his K % was actually better than his career numbers. His power is still there, shown by 39 HRs, .494 SLG %, and .246 ISO. The only thing that wasn’t there last year was the hits falling in. Look for Teixeira to get back to his previous numbers of 120+ wRC with an uptick in his entire slash line.
Read MoreSabermetric Glossary: BABIP
by Ryan Rigato | Guest Writer |
Batting Average on Balls In Play (BABIP) is one of the main statistics used to determine whether any specific player is having a particularly lucky season in terms of batting average or ERA. The league average BABIP usually falls around .300. The formula for calculating BABIP is:
(H – HR) / (AB – K – HR + SF)
Variables in BABIP:
1) Luck: The variable responsible for the most fluctuation in BABIP is random variation, basically luck. An example of this is a softly hit “blooper” that flies over the head of a second baseman but too short for the right fielder to track down.
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