Batting Average and Earned Run Average: Are They Still Useful Baseball Stats?
Wednesday January 18th, 2012
Peter Stein (Fantasy Baseball Analyst – MLB reports): Just as baseball cards have become outdated, so too are the statistics that many of us memorized on the backs of those same cards as kids. The statistics that I am referring to are the generic stats used to measure a player’s success, particularly batting average for hitters and earned run average (ERA) for pitchers. Sabermetrics has taught us that there are better methods to more measure a player’s worth or success on the diamond. Far too often, numbers like ERA or batting average are skewed and do not accurately depict a player’s true level of skill.
However, batting average and ERA are statistics that are fixtures in the game, particularly in fantasy baseball. They are used to define players and probably will continue to do so. For those of us in standard 5X5 Roto Leagues, batting average and ERA account for two essential categories.
In 500 at bats, the difference between a .250 and .300 hitter is 25 hits. With six months in a season (approximately 24 weeks), that comes to about 1 hit per week. I repeat, one hit per week! I think I first heard this statistic from Major League I. Remember the old catcher with the bad knees, Jake Taylor?
If you have ever watched baseball, you know how much luck can play a factor. A guy can hit the ball on the screws four times- yet make four outs… but just as easily, getting three hits without hitting the ball out of the infield. Likewise, a pitcher’s ERA can be entirely skewed based on circumstances beyond their control. Therefore, I introduce to you two sabermetric statistics that are key in determining a player’s “true” batting average and ERA.
According to Fangraphs, Fielding Independent Pitching (FIP) “measures what a player’s ERA should have looked like over a give time period, assuming that performance on balls in play and timing were league average.”
The equation for FIP: ((13*HR)+(3*(BB+HBP-IBB))-(2*K))/IP + constant
XFIP takes it even a step further by replacing a pitcher’s homerun rate with the league average (10.6% HR/FB), since this statistic is subject to high volatility.
Considering the above, Fielding Independent Pitching and Expected Fielding Independent Pitching are great determinants for what a pitcher’s ERA should be. It can tell you if a player is overachieving or perhaps pitching better than their ERA might indicate. This is the key to fantasy baseball. Target the guys who have FIP’s lower than their actual ERA and sell high on the pitcher who’s FIP is much higher than their actual ERA. By no means is the stat perfect, but it certainly gives you insight into a player’s performance and is a better indicator of future success than ERA alone.
For batters, the key statistic in determining batting average is Batting Average on Balls in Play (BABIP), which according to Fangraphs “While typically around 30% of all balls in play fall for hits, there are three main variables that can affect BABIP rates for individual players: defense, luck, and changes in talent level.”
The average BABIP for players is between .290 and .310, although some hitters can maintain a much higher level. For example, Ichiro Suzuki has maintained a career BABIP of .351, well above the league average. Therefore, you can look at a player’s BABIP to see how well they are actually doing at the plate. Buy low on a guy whose BAPIP is thirty points lower than his career total. Chances are his batting average is suffering and he is a good buy-low candidate. The lower BAPIP indicates that has a victim of bad luck. Likewise, the guy who is sporting a .400 BAPIP simply cannot maintain that level and will see a major regression to the mean. In this case: sell, sell, sell!
A perfect BAPIP example is Austin Jackson, who exploded onto the fantasy scene as a rookie in 2010. With a .293 batting average and good speed, he was an attractive young player with a rising stock. However, his.293 batting average in 2010 coincided with a .396 BABIP. We know Jackson is not Ichiro (.351 BAPIP) and therefore we had to expect a major regression in 2011. Sure enough, his BAPIP dropped to .340 (still well above the league average) and as result, he finished the season with a .249 average. Therefore, I would not touch Jackson with a ten-foot pole in most leagues, at least not until he can cut down his strikeout rates and put the ball in play on a more consistent basis. Although he has proven he can produce a hit more often than most when he makes contact, he simply does not make enough contact at this point in his career to be a .300 hitter.
The young guns are generally the guys who are most difficult to read. With the veterans, you at least have their career BAPIP to use as a reference. However, do not be afraid to look at the minor league stats, which usually prove to be solid enough indicators. At the same time, never take too much stock in minor league numbers and make a hitter prove himself at the major league level.
Overall, stats like FIP and BAPIP are really just cheats for your fantasy baseball league. Batting average and ERA are statistics that are so deep-rooted that they will most likely be used forever to define a player’s success and as a result, will continue to be used in fantasy baseball. However, do not look at ERA and batting average to value a player and trying to predict their future ERA and batting average. FIP and BAPIP give you a more accurate story and are better indicators for future success- by at least attempting to eliminate the many variables that exist in the wonderful game of baseball.
***Today’s feature was prepared by our Fantasy Baseball Analyst, Peter Stein. We highly encourage you to leave your comments and feedback at the bottom of the page and share in the discussion with our readers. You can also follow Peter on Twitter (@peterWstein).***
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Posted on January 19, 2012, in The Rest: Everything Baseball and tagged austin jackson, bapip, baseball, batting average, earned run average, era, fangraphs, fantasy baseball, fielding independent pitching, fip, mlb, sabermetrics, statistics, stats, xfip. Bookmark the permalink. 4 Comments.