With ups and downs, the excitement of Michael Brantley’s return and the torture of Edwin Encarnacion’s first 63 plate appearances, the 2017 Cleveland Indians have gotten off to a middling start over the first 14 games. If this happened in June when the Indians were already comfortably above .500, Tribe fans would not notice. Indeed, we would be taking in the beauty of perhaps the best middle infield duo in baseball with Francisco Lindor and Jose Ramirez. Yet, for many reasons, fans are nervous. There are people on edge regarding one of the three or four most talented teams in Major League Baseball. The purpose herein is to dispel this discomfort as deep down inside, we are a little anxious in the early going.
The simplest angle to note is that the Indians are beloved by projection systems. Teams have yet to play even a meager 10% of their games, so the sample size needed to play into those projections has yet to be present. Indeed, baseball’s massive season exists to strip out as much variance or luck as possible in the sample. Such length makes individual games tougher to analyze. With Twitter, sports radio, and a nation that loves football, it is important to emphasize that baseball is a different animal. You have to become comfortable with waiting a significant amount of time and for a significant sample before drawing conclusions or rethinking preconceived expectations. So, if your theory regarding the 2017 season was that the Indians were loaded and en route to a playoff appearance, there is far too small a sample to be shaken from this assertion. If a major injury or suspension occurs a la Starling Marte, one can shift their expectations, but patience with conclusions in baseball is essential.
In order to provide more context regarding what it means for a sample to even out, or to strip the variance, you can look to a few early season indicators.
One of the easy items is run differential. Over the course of the season, a positive run differential has a strong correlation to a winning record.1 The Indians have a middling early run differential at minus-1, but they have basically played to their run differential and their talent projects for significant uptick in run differential. Whereas the Detroit Tigers, first in the American League Central as of this writing at 8-5, have a run differential of -13. The conclusion which can be drawn is that they have won significantly more games than their performance would dictate, and these things have a way of leveling out with some exceptions such as the 2016 Texas Rangers. Pythagorean win-loss and base runs have the Tigers as 5-8 or 6-7. The Tigers team is still aging and there is no need to panic about their early positive start.
Time to turn to BABIP (Batting Average on Balls in Play). First, BABIP for individuals players is mostly skill-driven with contact quality and speed inputs. However, early in the season, there can be some fluky outcomes which create BABIP outliers.
The Indians pitching staff has the highest BABIP against with runners in scoring position of .395, .13 points higher than the second-highest team. The highest BABIP against in 2016 with runners in scoring position was .319. The Indians can expect positive normalization and more stranded runners moving forward, which leads to better run prevention. Similarly, the Indians offense in these situations has a .208 BABIP which is fourth worst in Major League Baseball. In 2016, the lowest BABIP in the RISP context was .265. Therefore, cluster luck has adversely plagued the Indians offense early. When hits start to fall or get through with greater frequency, the Indians runs scoring will undoubtedly improve.
As the statistics normalize, the Indians loaded roster will take off and leave early April fears behind.
- run differential is quite simply team runs scored – team runs allowed [↩]