Because it takes it takes 910 at bats for batting average to stabilize, it is not very helpful to look at the small sample of at bats a player has had in 2014 (as the video below will show). When you try to decide whether or not to by into a player's early season slump …
253 Batting Average Risers and Fallers
Because it takes it takes 910 at bats for batting average to stabilize, it is not very helpful to look at the small sample of at bats a player has had in 2014 (as the video below will show).
When you try to decide whether or not to by into a player’s early season slump or success, you have to look a bit deeper.
So we will look at the players that are projected, by Steamer, to outperform or underperform their current batting average by the largest margin for the rest of the season.
Below are some players that should outperform or underperform their current batting averages, according to their Steamer projections.
Batting Average Risers and Fallers
[table id=63 /]
Players to Buy Low
These good guys make for good buys in the coming weeks, despite their slow start to the season.
Carlos Santana, C/1B/3B, Cleveland
Santana, to the chagrin of many Fantasy owners, has batted .151, but there have been many reasons to expect Santana to live up to his .245 rest of season projection. With increased walk rates—BB% (2013: 14.5%, 2014: 19.1%) — and plate discipline — O-Swing% (2013: 25.8%, 2014: 17.3%) — Santana has been a more patient hitter.
At its essence, Santana’s struggles have stemmed from his fall to an 11.8 LD%. While line-drive rates show a low year-to-year correlation, Fantasy owners should expect Santana’s LD% to regress back to his career average of 18.7%, and increase his AVG along the way.
Prince Fielder, 1B, Detroit
Like Santana, Prince Fielder’s walk rate has improved from 2013, while his average has decreased.  Fielder did not have a month in all of 2013 where he hit under .228, not that that’s an impressive number, but it’s a lot more desirable than the tango he has done with the Mendoza line in April. But here’s the kicker. The league average BABIP on line drives is .682, and Fielder’s career average BABIP on line drives is .727. Compare that with the .563 BABIP on line drives that Fielder had in April, and we can be certain that a lot of the hard hit balls Fielder hit right at opponents in the first month will begin to find empty space and increase his average.
Players to Sell High
Get ready to move some of these players, as they are off to uncharacteristically hot starts, which means they should dip back down soon.
Chase Utley, 2B, Philadelphia
Utley has hit sixty-five points over his career average BABIP in 2014, and surprise surprise, he has hit almost exactly sixty-five points over his career AVG this year. More importantly, like Marcus Giles, Edgardo Elfanso, Carlos Baerga, and Chuck Knoblauch, Ultely has been to fall apart from a physical perspective over the recent years. The combination of the regression that will come in Utley’s BABIP and his physical durability, make him a good sell high candidate. Look to see if your leagues Jedd Gyorko owner has grown impatient.
A Player We’re Not Sure What to Do With
This guy falls into a category we’re not sure how to handle.Â
 Alexei Ramirez, SS, Chicago White Sox
I’m not sure what to make of these numbers, partly because I’m not sure when plate discipline numbers stabilize, although, I would assume it happens quickly.
Ramirez has swung less at pitches in the strike zone — Z-Swing% (2013: 69.3%, 2014: 63.5%) — and made more contact with pitches in the strike zone — Z-Contact% (2013: 93.5%, 2014: 97.5%). While it remains outside the knowledge of the author on whether or not there is an inverse correlation between Z-Swing% and Z-Contact%, it intuitively makes sense.
If a hitter begins to lay off of pitches as pitchers attack his weaknesses, even though those pitches may be strikes, and only swings at strikes he knows he can mash, he should be able to make more contact with pitches that are strikes because he doesn’t swing at pitches he can’t handle.
Devin Jordan is obsessed with statistical analysis, non-fiction literature, and electronic music. If you enjoyed reading him, follow him on Twitter @devinjjordan.