Hitting Regression Candidates

Every season is rife with players whose actual numbers differ from their expected stats. These deviations can stem from a variety of factors, including limited at bats, unfavorable metrics or flat out luck. In this article we’ll look to identify some hitters who exceeded their expected numbers in 2019, while also highlighting some who underperformed, by looking at the stats BABIP (batting average on balls in play), xBA (expected batting average) and xwOBA (expected weighted on-base average) compared to BA and OBP.

BABIP will be our principle measure in uncovering which batters are unlikely to repeat last season’s performance. Its formula is

(Hits – HR)/(AB – HR – K + SF)

Before continuing, it’s important to note BABIP is not a perfect metric and slightly favors players who strike out more and homer less. League average BABIP is right around .300, however because it is a deviant of BA which typically ranges anywhere from .200 to .350 we will instead compute the difference between BABIP and BA to determine which players did not perform as expected in 2019. The average difference of .043 will serve as a basis. xBA and xwOBA will be used to confirm the difference between BABIP and BA is significant. The 360 players with at least 200 plate appearances (PAs) last season were considered. With that, let’s get started.

Due for Positive Regression

Players whose BABIP – BA was below the league average of .043 and was not in line with their recent differential appear below. xBA was employed as a comparison to check if advanced analytics also suggest an increase.

Player	POS	Team	BABIP	BAvg	Diff	xBAvg
Max Kepler	OF	MIN	0.244	0.252	-0.008	0.262

Kepler was one of 17 players who had a lower BABIP than BAvg in 2019. This was the first season of Kepler’s career where his BABIP was not at least 12 points higher than his BAvg, and his xBAvg also promotes a higher batting average for 2020.

Player	POS	Team	BABIP	BAvg	Diff	xBAvg
Edwin Encarnacion	DH	CHW	0.239	0.244	-0.005	0.242

In the three seasons prior to 2019, Encarnacion’s BABIP was 13 points higher than his BAvg so the negative differential last year looks like an outlier. Slugging 34 homers last season prove Encarnacion still has enough in the tank to contribute and improved BABIP will aid his potential production.

Player	POS	Team	BABIP	BAvg	Diff	xBAvg
Joc Pederson	1B/OF	LAD	0.249	0.249	0.000	0.254

Pederson is trending up in 2020 given that he appears to be an everyday starter once again, and improved BABIP is another factor that promotes this. Pederson’s BABIP averages .027 points higher his BA for his career. Compare that to last season’s identical rates along with .005 points higher xBAvg and all signs indicate improved BAvg for the upcoming season.

Player	POS	Team	BABIP	BAvg	Diff	xBAvg
George Springer	OF	HOU	0.305	0.292	0.013	0.287

Although Springer’s xBAvg was lower than his actual BAvg in 2019, his below average BABIP – BAvg of .013 is considerably lower than his career average differential of .040. This wide gap alone indicates improved luck for Springer in 2020.

Player	POS	Team	BABIP	BAvg	Diff	xBAvg
Marcel Ozuna	OF	ATL	0.257	0.241	0.016	0.288

Ozuna’s career BABIP – BAvg of .042 suggests that his 2019 differential of .016 is due for improvement. What further supports this is his -.047 gap between BAvg and xBAvg is the second widest among all 360 hitters. Both metrics support better play from Ozuna in 2020.

Player	POS	Team	BABIP	BAvg	Diff	xBAvg
Freddie Freeman	1B	ATL	0.318	0.295	0.023	0.292

As if we needed another reason to be high on Freeman, his career gap in BABIP and BAvg of .047 is more than double his rate in 2019. His xBAvg was slightly lower than actual BAvg, but a strong Atlanta line up and positive BABIP regression makes Freeman even more attractive.

Player	POS	Team	BABIP	BAvg	Diff	xBAvg
Starling Marte	OF	ARI	0.319	0.295	0.024	0.304

Marte is another player whose 2019 BABIP and BAVG differential was not in line with his career rate of .055, and this is supported by his xBAVG. His xwOBA was also .008 points below expected, which promises more times on base this season in a stronger Diamondbacks line up.

Unlikely to Repeat

These are players whose BABIP exceeds their BA by a substantial margin, is not in line with career norms and is supported by xBA. There is a not so obvious trend of young players who performed better than expected in 2019.

Player	POS	Team	BABIP	BAvg	Diff	xBAvg
Joey Gallo	OF	TEX	0.368	0.253	0.115	0.229

Gallo enjoyed a huge breakout year in 2019, however these numbers do not appear sustainable. He had the second largest differential between BABIP and BA, and his xBA was substantially lower than BA. The one saving factor is that Gallo’s career BABIP – BA is .073; still lower than 2019’s rate but well above the league average .043.

Player	POS	Team	BABIP	BAvg	Diff	xBAvg
Fernando Tatis Jr.	SS	SD	0.410	0.317	0.093	0.259

There’s a lot to like about Tatis, but these numbers indicate last season’s breakout is far from the norm. Tatis led the league in BABIP and had the largest gap between BAvg and xBAvg. Some of this success is undoubtedly due to his hustle but expect major regression before investing an early round draft pick.

Player	POS	Team	BABIP	BAvg	Diff	xBAvg
Keston Hiura	2B	MIL	0.402	0.303	0.099	0.266

Another electric rookie from 2019 with enticing overall prospects, however the expected stats don’t support a sustainable breakout. Hiura was top 10 in differentials between both BABIP and xBAvg with BAvg – not a good sign. Think twice before selecting Hiura during the first 10 rounds.

Player	POS	Team	BABIP	BAvg	Diff	xBAvg
David Dahl	OF	COL	0.386	0.302	0.084	0.267

Dahl was a surprising All-Star in 2019 and the numbers supported it, however he appears to have overachieved. The differential between Dahl’s BABIP and BAvg is almost double the league average and that between his xBAvg and BAvg is bottom 15. He is still deserving of a roster spot, but only in the last few rounds of your draft.

Player	POS	Team	BABIP	BAvg	Diff	xBAvg
Yoan Moncada	3B	CHW	0.406	0.315	0.091	0.291

Once the top prospect in all of baseball, Moncada finally delivered solid contributions in 2019. The numbers don’t support the breakout, unfortunately, as Moncada had a top 15 BABIP – BAvg and his xBAvg was lower than his BAvg. This along with a high strike out rate indicate he should be going after pick 150 rather than his current spot around 125 in points leagues.

Player	POS	Team	BABIP	BAvg	Diff	xBAvg
Adalberto Mondesi Jr.	SS	KCR	0.357	0.263	0.096	0.237

In roto formats, Mondesi Jr. can be a huge asset due to his speed but in points leagues he is hardly deserving of a roster spot. His BABIP and xBAvg compared to BAvg were both bottom 30 differentials, and on top of that his well below average xwOBA of .298 was .016 higher than predicted. Expect a decline in 2020.

Player	POS	Team	BABIP	BAvg	Diff	xBAvg
Luke Voit	1B	NYY	0.345	0.263	0.082	0.249

Voit is another player who enjoyed a breakout 2019 that doesn’t appear repeatable. His BABIP and xBAvg exceeded BAvg by a wide margin and playing time isn’t considered a lock on a strong Yankees team. Voit is being selected near the end of drafts but is best left on waivers.