Platoon Hitter Projections

In my previous article, I found that left-handed platoon hitters who start games with the handedness advantage can expect to have that handedness advantage in 84.9 percent of their plate appearances in those games. Right-handed platoon hitters maintain their handedness advantage in 52.6 percent of their plate appearances in those games. Those percentages imply that relying on vs. left-handed pitcher and vs. right-handed pitcher split statistics to project the performance of platoon hitters in their starts with the platoon advantage overestimates their production in those starts. I wanted to see if I could do better based on my research, and so I created a (Marcel-) simple projection system.

Here’s how the system works. From 2004-2014, I identified every platoon hitter each season based on the thresholds of having at least 89 percent of total plate appearances come against opposite-handed pitchers for left-handed hitters and 45 percent for right-handed hitters. Next, I calculated those platoon hitters’ hits per plate appearance, doubles per plate appearance, triples per plate appearance, home runs per plate appearance, strikeouts per plate appearance, walks per plate appearance, and hit by pitches per plate appearance in those seasons and the two preceding seasons. I then weighted those three seasons using the Marcel weights of 5 for the most recent season, 4 for the year prior, and 3 for two years prior. That’s the projection.

I wanted to test whether those projections would beat similar projections based on vs. left-handed pitcher and vs. right-handed pitcher split stats—which does not account for the fact that platoon hitters are sometimes left in the game after the starter is pulled to face a same-handed reliever—and so I ran correlations of both split stat projections and my weighted split stat projections to predict actual hits per plate appearance, doubles per plate appearance, etc., in the following season. For each test, I required a minimum of 50 plate appearances in the predicted season, which created a sample of 495 total batters.

First, here are the correlations of the split stat projections.

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Correlations Based on Split Stats

	N	H	2B	3B	HR	K	BB	HBP
LHB	227	0.268	0.215	0.361	0.510	0.746	0.504	0.574
RHB	268	0.279	0.135	0.139	0.403	0.696	0.446	0.486
All	495	0.289	0.164	0.252	0.443	0.715	0.480	0.514

Next, here are the correlations of the weighted split stat projections.

Correlations Based on Weighted Splits

	N	H	2B	3B	HR	K	BB	HBP
LHB	227	0.269	0.223	0.362	0.507	0.749	0.506	0.606
RHB	268	0.286	0.095	0.159	0.471	0.721	0.511	0.527
All	495	0.292	0.146	0.274	0.487	0.734	0.540	0.556

Finally, so you don’t have to scroll back and forth, here is the difference between the two.

Correlation Advantage of Weighted Splits

	N	H	2B	3B	HR	K	BB	HBP
LHB	227	0.001	0.008	0.001	-0.003	0.003	0.002	0.033
RHB	268	0.007	-0.040	0.020	0.068	0.024	0.065	0.042
All	495	0.003	-0.018	0.022	0.044	0.020	0.060	0.042

The weighted split stat projections were not universally better. They lost on doubles for right-handed hitters and on home runs for left-handed hitters. But, overall, the weightings improved the projections in 12 of 14 tested stats (split by batter handedness).

Now that I’m confident that the weighted split projections are worthwhile, I’ve created 2016 projections for the platoon hitters from 2015. Because per-plate appearance statistics can be sort of hard to interpret, I’ve scaled everyone’s numbers to 600 plate appearances. They won’t actually get 600 plate appearances; it’s just to give you an idea of the quality of the player you can expect to have in his starts against opposite-handed starting pitchers.

Projected Stats in Starts with Platoon Adv. – Scaled to 600 PA

Hitter	Bats	H	2B	3B	HR	K	BB	HBP	BAVG	OBP	SLG	OPS
Franklin Gutierrez	R	154.2	32.7	0.0	45.2	171.8	36.6	6.4	.277	.329	.579	.908
Kiké Hernandez	R	167.9	37.5	8.8	18.3	113.3	43.2	5.2	.304	.361	.504	.864
David Peralta	L	167.7	27.2	13.1	18.4	115.1	43.3	3.2	.303	.357	.499	.856
Steve Pearce	R	135.6	32.7	1.2	28.6	114.6	54.7	10.1	.253	.334	.479	.813
Danny Valencia	R	158.7	37.9	2.0	21.3	120.8	40.3	2.1	.285	.335	.474	.810
Michael Conforto	L	143.3	39.8	0.0	25.6	120.6	51.6	2.8	.263	.330	.477	.806
Ben Paulsen	L	155.7	32.0	5.7	21.3	158.8	36.3	4.0	.278	.327	.470	.796
Scott Van Slyke	R	135.7	32.4	0.8	21.4	154.8	65.3	8.9	.258	.350	.445	.795
Justin Bour	L	145.1	26.2	0.0	28.0	135.9	48.3	2.3	.264	.326	.464	.790
Andre Ethier	L	146.5	29.7	7.4	13.7	105.1	58.5	7.2	.274	.354	.434	.788
Clint Robinson	L	147.1	25.2	1.6	15.9	90.1	63.6	7.9	.278	.364	.422	.787
Wilin Rosario	R	161.4	35.8	0.8	23.1	115.8	28.1	0.8	.283	.317	.469	.786
Darin Ruf	R	133.1	26.1	0.0	26.1	151.5	53.7	13.9	.250	.335	.446	.781
Matt Adams	L	157.5	33.5	2.9	19.9	127.5	32.7	1.7	.278	.320	.454	.773
John Jaso	L	139.4	35.0	2.1	12.2	108.9	69.6	7.8	.267	.361	.412	.773
Chris Coghlan	L	139.6	32.8	7.3	14.6	113.3	61.0	3.7	.261	.341	.431	.772
Seth Smith	L	133.6	38.7	4.8	14.2	121.2	67.7	4.8	.253	.344	.426	.769
Chris Carter	R	112.5	22.8	0.7	33.1	198.1	71.9	5.7	.215	.317	.452	.768
Pedro Alvarez	L	127.8	20.8	1.0	31.6	163.1	56.1	3.1	.236	.312	.454	.766
Ryan Raburn	R	133.1	32.2	1.6	22.2	146.0	53.9	7.3	.247	.324	.436	.760
Derek Dietrich	L	126.1	26.5	6.3	20.3	132.2	42.6	26.1	.237	.325	.425	.750
Rajai Davis	R	153.7	31.2	9.4	12.3	111.2	33.4	5.2	.274	.321	.429	.749
Jake Smolinski	R	130.1	23.9	5.3	20.3	126.5	52.2	10.4	.242	.321	.420	.741
Carl Crawford	L	160.0	30.2	4.8	11.0	97.1	30.5	4.9	.283	.326	.412	.738
Joey Butler	R	151.2	27.0	0.0	17.1	181.5	37.7	5.1	.271	.323	.412	.735
Brandon Guyer	R	138.5	31.9	2.7	10.0	99.2	36.6	31.7	.260	.345	.387	.732
Ryan Howard	L	129.7	29.2	1.7	23.6	163.5	47.3	5.0	.237	.303	.426	.729
Chris Young	R	123.9	33.0	2.1	20.6	124.3	57.5	5.3	.231	.311	.415	.726
Alejandro De Aza	L	140.4	26.7	7.8	12.1	133.8	46.8	6.7	.257	.323	.401	.724
Tyler Collins	L	148.5	29.4	7.3	11.7	117.8	33.6	2.4	.263	.308	.404	.711
Kelly Johnson	L	131.7	21.6	2.0	21.5	144.5	49.4	2.5	.240	.306	.405	.711
Miguel Montero	L	126.7	20.0	0.0	17.0	129.5	66.7	7.4	.241	.335	.376	.711
Shane Victorino	R	145.4	23.4	3.9	11.2	88.6	34.8	16.0	.265	.327	.383	.710
Paulo Orlando	R	145.3	32.6	13.8	15.7	116.6	13.1	3.8	.249	.270	.434	.704
Scooter Gennett	L	155.1	31.2	5.1	10.5	100.8	22.5	3.4	.270	.302	.397	.699
Conor Gillaspie	L	141.4	31.1	5.0	11.3	101.2	41.4	2.6	.254	.309	.389	.698
Nolan Reimold	R	124.9	19.6	2.0	19.4	172.5	59.7	3.0	.232	.313	.385	.698
A.J. Ellis	R	111.5	23.8	0.3	14.5	98.1	89.7	3.9	.220	.342	.354	.696
Travis Snider	L	130.4	26.3	3.4	14.3	136.4	55.5	2.9	.241	.315	.381	.696
Tim Beckham	R	123.5	18.4	10.7	23.8	181.4	34.0	7.7	.221	.275	.420	.695
David Murphy	L	141.3	30.8	1.4	13.9	76.5	40.8	1.8	.253	.306	.389	.695
Jake Lamb	L	138.9	21.7	7.0	11.1	153.1	49.3	1.2	.253	.316	.378	.694
JR Murphy	R	149.3	30.4	2.2	9.6	153.6	36.8	2.5	.266	.314	.380	.694
Dustin Ackley	L	134.6	28.0	4.5	16.2	97.8	41.6	2.3	.242	.298	.396	.693
Josh Phegley	R	135.6	33.2	1.2	22.0	121.9	26.4	3.5	.238	.276	.416	.692
Will Venable	L	133.6	20.8	5.4	14.5	141.6	46.0	3.6	.243	.306	.379	.685
Alex Avila	L	109.6	22.8	0.5	15.2	184.9	88.3	1.7	.215	.333	.351	.684
Jonny Gomes	R	118.0	20.9	0.0	15.8	167.2	68.2	9.3	.226	.326	.356	.682
Chris Denorfia	R	140.3	24.4	4.0	8.7	117.7	46.2	0.9	.254	.312	.360	.672
Grady Sizemore	L	134.1	32.4	3.2	10.0	119.9	46.5	1.9	.243	.304	.368	.672
Ike Davis	L	114.0	29.9	0.0	12.4	126.1	78.0	0.6	.219	.321	.347	.668
David DeJesus	L	125.4	27.5	3.7	10.6	100.5	48.8	11.2	.232	.309	.356	.665
Matt Joyce	L	112.5	26.6	1.5	14.2	135.9	68.0	5.3	.214	.310	.351	.661
Ezequiel Carrera	L	143.5	25.6	1.9	6.7	134.4	32.1	9.1	.257	.308	.345	.653
Gordon Beckham	R	128.6	28.7	0.3	11.5	96.7	37.9	7.9	.232	.291	.347	.638
Jeff Francoeur	R	133.5	26.0	2.0	15.4	138.7	25.2	2.0	.233	.268	.366	.634
Skip Schumaker	L	133.8	33.7	0.0	3.3	106.1	46.6	3.3	.243	.306	.322	.628
Jake Marisnick	R	127.8	21.7	4.7	13.5	164.7	26.8	7.6	.226	.270	.353	.623
Melvin Upton Jr.	R	110.8	23.1	3.3	10.2	176.7	66.5	2.2	.208	.299	.322	.621
Mike Aviles	R	133.3	22.4	0.5	10.2	71.2	28.7	2.4	.234	.274	.330	.604
Clint Barmes	R	125.1	33.6	0.8	7.9	140.4	29.0	10.0	.223	.274	.328	.601
Shane Robinson	R	125.2	15.0	6.7	2.1	79.9	52.8	1.5	.229	.299	.293	.592
Alexi Amarista	L	123.6	17.9	5.1	6.3	89.2	37.6	1.9	.221	.272	.304	.576
Hernan Perez	R	135.9	30.3	6.5	2.5	130.7	12.0	0.0	.231	.246	.317	.564

Franklin Gutierrez has had insane home run per flyball luck over the last two seasons, but regression would not change the fact that he has been an incredible source of power in his limited plate appearances. Among the platoon options, he is the best projected power source in his platoon starts in 2015. Chris Carter, Pedro Alvarez, Justin Bour, and Steve Pearce are the other platoon hitters projected to hit 28 or more home runs per 600 plate appearances in their platoon starts.

David Peralta has likely graduated from his platoon role. Ender Inciarte is no longer in Arizona, and Peralta was nearly a 4-win player last season. That eliminates one of the premiere batting average platoon options, but there are several others. Kike Hernandez is projected to hit .304 in his starts versus lefties, assuming he can get on the field behind Corey Seager and the rest of that loaded Dodgers lineup. Ditto for Carl Crawford and his projected .283 average. Some of the good options who should regularly see the field this year include Danny Valencia (.285)—who looks like the primary Athletics starter at third base following the Brett Lawrie trade—Ben Paulsen—who should share first base duties with Mark Reynolds in Colorado—Clint Robinson (.278), Matt Adams (.278), and Scooter Gennett (.270).