Context Rules All by Eric Seidman August 26, 2011 Baseball statistics mean absolutely nothing without context. Without the ability to place numbers in the appropriate context it’s impossible to seriously parse meaningful information out of data points. Unfortunately, context is often forgotten or ignored when talking about various aspects of the game, leading to inaccurate assessments and faulty conclusions. While there are numerous uncertainties surrounding statistics, there’s at least one sure thing: we can’t know much of anything without factoring in the appropriate baseline. When looking at a slash line, context most certainly matters. Otherwise, there would be no way to determine if a .255/.320/.375 is good or not. In a .270/.340/.420 league, it isn’t; but the numbers look mighty fine if the league is hitting .250/.320/.360. Fans intuitively get what constitutes a good or bad line, because their knowledge of the game builds a subconscious understanding of the league average. We might not be able to rattle off the league batting average, on base percentage and slugging percentage, but the general vicinity for each is more commonly known. This season, however, the league averages for each of those stats is significantly lower. In 2005, the National League hit .262/.330/.414. This season, the senior circuit dropped to an average of .253/.319/.391. In 2005, Angel Pagan’s .264/.324/.385 would be considered below average. Now, his line looks right in line with the rest of the league. The problem is that it becomes tough to adjust our mental barometers. Pagan’s line is judged in the context of what the league used to be, which can lead to the misguided conclusion that he isn’t hitting well this season. Mark Teixeira is another interesting player. He has a .345 OBP and .515 SLG for the Yankees right now, compared to a .365/.481 a year ago. Given the importance of on base percentage, relative to slugging, it would seem that his numbers are worse this year. Appropriate context clears things up, though. Teixeira posted a .367 wOBA last season. Despite his 20-point drop in OBP, his current wOBA is .371. In addition to adjusting numbers based on the context of the specific league and year, parks loom large when evaluating player performance. Take Eric Hosmer and Jason Heyward as examples. The former is being lauded as having a solid rookie season for the Royals, while the latter is lambasted for his sophomore slump in Atlanta. Hosmer is hitting .272/.322/.423, while Heyward is putting up a disappointing .222/.311/.397. Now, I’m not going to defend Heyward’s performance — even though he deserves to play every day he isn’t performing up to expectations — but it should be pointed out that the two players are not far apart when looking at general productivity. Using wRC+, which adjusts for both park and league, Hosmer’s 100 isn’t too far above Heyward’s 96. Lastly, splits prove troublesome because context is used incorrectly. If Carlos Gonzalez hits vastly better at Coors Field than in road stadiums, his self-split on its own isn’t anywhere near as relevant as that split compared to the league H/A split. Still, stories will compare his home production to his overall production. Similarly, when judging the hitting prowess of a player against same-handed pitching, comparing the split wOBA to the overall mark of the player isn’t the appropriate way to properly understand that player’s productivity. To get a handle on how the player fared, the league split for batters against same-handed pitchers must be introduced. Individual splits are meaningless if they aren’t compared to the league split. Contextualizing numbers when making arguments or evaluating players is extremely important relative to choosing the appropriate metric. Without context, even the right statistic can be wrong.