2062 – Platoon Advantage After Six Weeks

[RonCo]

We all understand the point of the platoon advantage, right? Get hold of that, and ride it to total success!

Well, maybe not.

But there is clear value in getting your righthanded batters facing lefties, and vice versa—to the degree that you have decent hitters, anyway. Scrubs don’t suddenly start to club doubles right and left simply because they face the opposite hand more often. Same goes for pitchers, too, of course—but with the opposite polarity.

In the old days I used to do various studies simply to see if the game had splits “properly” coded. That time is mostly passed. OOTP has been pretty good about this on the whole for a very long time. But now I like to do it to give me an idea of exactly how strong the advantage has actually been in play. How much value am I getting by hunting that handedness advantage?

After size weeks, we have a little grub to work with, so why not?

Let’s see how important the platoon advantage has been through mid-May.

As of May 8th, there have been over 40,000 plate appearances in BBA games. Here are the results of those plate appearances based on whether the pitcher or batter held that platoon advantage (note that, naturally, switch hitters always hold the platoon advantage):

Stat	Adv B	Adv P	Total
PA	21910	18357	40267
AB	20026	16901	36927
1B	3307	2877	6184
2B	1058	849	1907
3B	118	82	200
HR	656	540	1196
CI	5	2	7
E	201	199	400
BO	28	30	58
FC	16	16	32
FO	5548	4702	10250
GO	5110	4494	9604
K	3979	3110	7089
HBP	93	94	187
BB	1642	1284	2926
IBB	93	34	127

Here’s how that breaks out into classical stats:

Advantage	BABIP	BA	OBP	SLG	OPS
B	.291	.257	.318	.420	.737
P	.287	.257	.314	.413	.727
ALL	.289	.257	.316	.417	.733

So, there we have it. Of most intellectual interest is that, despite there being a .004 BABIP advantage to holding the platoon advantage, that isn’t translating into batting average. At least not yet. Even at 40K plate appearances, one can argue that in context of the league’s surroundings, the sample size has not stabilized. I’m not smart enough to figure that out, so take it for what it is. There is also the weather effect to take into account. Offense will tend to heat up was the weather does.

But the rest of the data shows that platoon advantage is filtering through OBP, and into SLG, and therefore, into OPS, at about a .010 advantage.

My gut reaction is that this is a little less than I was expecting.

Again, though, we’re only six weeks into the season.


Batter Data

Here’s some more interesting information, too. Let’s look at how batters of various flavors (RHB, LHB, Switchies) are doing against pitcher handedness:

Batter Vs.	BABIP	BA	OBP	SLG	OPS
LHB	.296	.262	.323	.432	.756
L	.285	.248	.309	.393	.702
R	.300	.266	.328	.444	.772
RHB	.288	.257	.316	.415	.731
L	.288	.254	.318	.413	.731
R	.288	.259	.315	.416	.731
SHB	.282	.245	.302	.390	.693
L	.258	.237	.295	.396	.691
R	.292	.248	.305	.388	.693
Total	.289	.257	.316	.417	.733

Interstinger and interestinger.

Note that, at present, our RHB are faring just about as well against RHP as they are Lefties (or are doing equally poorly against LHP as they are against Righties. LHB are, as one would expect, are getting kicked in the teeth by LHP, but are your best bet against Right handed tossers.

Then we come to the very interesting case of switchies.

Switch hitters are, on the whole, just not capable of much umpf. Their sub .700 OPS is the weakest of the bunch. But look at those splits. That’s interesting. Switch hitters hitting right handed are several points higher in the OBP category, while losing out in the Slugging category.

Not sure what to make of it all, but’s fun to think about.


Team Data

And, finally, here is one more chart full of information about our teams. Specifically, how often are we enjoying the platoon advantage.

Bat Team	PA	B	P	%Adv
Calgary Pioneers	1277	932	345	73.0%
Rocky Mountain Oysters	1240	801	439	64.6%
Chicago Black Sox	1223	768	455	62.8%
Boise Spuds	1261	784	477	62.2%
Phoenix Talons	1331	823	508	61.8%
Bikini Krill	1211	740	471	61.1%
Jacksonville Zombies	1212	723	489	59.7%
Charm City Jimmies	1261	744	517	59.0%
Madison Wolves	1227	719	508	58.6%
Las Vegas Hustlers	1323	765	558	57.8%
Long Beach Surfers	1237	713	524	57.6%
Louisville Sluggers	1250	716	534	57.3%
Montreal Blazers	1218	696	522	57.1%
Valencia Stars	1228	699	529	56.9%
Omaha Cyclones	1281	710	571	55.4%
San Antonio Outlaws	1270	696	574	54.8%
Yellow Springs Nine	1224	670	554	54.7%
Twin Cities River Monsters	1251	669	582	53.5%
New Orleans Crawdads	1251	668	583	53.4%
Mexico City Aztecs	1286	676	610	52.6%
Portland Lumberjacks	1240	650	590	52.4%
Atlantic City Gamblers	1264	647	617	51.2%
Sacramento Mad Popes	1318	666	652	50.5%
Austin Shredders	1303	651	652	50.0%
Des Moines Kernels	1223	601	622	49.1%
Nashville Bluebirds	1240	607	633	49.0%
San Fernando Bears	1318	645	673	48.9%
Vancouver Mounties	1250	605	645	48.4%
Charlotte Flyers	1268	581	687	45.8%
Cape Fear Swamp Foxes	1305	596	709	45.7%
Brooklyn Robins	1277	547	730	42.8%
Hawaii Tropics	1268	433	835	34.1%

Calgary leads the league in platoon advantage by a considerable distance. Followed by Rocky Mountain, Chicago, and Boise.

Hawaii’s hitters have faced the disadvantage more often than any other team, followed by Brooklyn, Cape Fear, and Charlotte.

Again, what does it mean? I don’t know. I suppose it says something about roster construction, and possibly game strategy employed by our managers. But you tell me.

Here’s the same data by pitching team:

Pitch Team	PA	B	P	%Adv
New Orleans Crawdads	1266	564	702	55.5%
Portland Lumberjacks	1254	561	693	55.3%
Jacksonville Zombies	1274	584	690	54.2%
Brooklyn Robins	1307	607	700	53.6%
Vancouver Mounties	1266	598	668	52.8%
Valencia Stars	1284	607	677	52.7%
Bikini Krill	1215	579	636	52.3%
Phoenix Talons	1284	637	647	50.4%
Charlotte Flyers	1252	628	624	49.8%
San Fernando Bears	1262	634	628	49.8%
Hawaii Tropics	1278	645	633	49.5%
Chicago Black Sox	1218	623	595	48.9%
Montreal Blazers	1216	630	586	48.2%
Twin Cities River Monsters	1253	656	597	47.6%
Madison Wolves	1252	659	593	47.4%
Des Moines Kernels	1232	649	583	47.3%
Austin Shredders	1338	733	605	45.2%
Louisville Sluggers	1250	690	560	44.8%
Rocky Mountain Oysters	1234	696	538	43.6%
Atlantic City Gamblers	1230	697	533	43.3%
Calgary Pioneers	1229	702	527	42.9%
Omaha Cyclones	1272	730	542	42.6%
Cape Fear Swamp Foxes	1256	735	521	41.5%
Nashville Bluebirds	1178	696	482	40.9%
Long Beach Surfers	1273	756	517	40.6%
Yellow Springs Nine	1264	757	507	40.1%
Boise Spuds	1297	780	517	39.9%
Charm City Jimmies	1255	757	498	39.7%
Sacramento Mad Popes	1238	771	467	37.7%
Mexico City Aztecs	1337	846	491	36.7%
Las Vegas Hustlers	1293	827	466	36.0%
San Antonio Outlaws	1279	907	372	29.1%

[Krathan]

This is interesting. I’m curious about the switch hitter thing. I wonder who the switch hitters are. Is it possible that a lot of them are weaker hitters playing premium defensive positions?

[Krathan]

Another interesting thing related to switch hitters: My best hitter so far this season has been my only switch hitter, Jose Bedreddin. He’s hit out of his mind vs RHP (1.115 OPS) while being merely good against LHP (.797 OPS).

[BaseClogger]

I’d be curious to see how effective those teams are with the platoon advantage too. It’s not good enough just to get yourself in that position if your players aren’t splitty (as your first set of data demonstrates). I thought I’d fair a little better with the hitters but having two RHH catchers is a huge disadvantage here. Based on how light hitting catchers are around the league I don’t sweat that.

[RonCo]

Another interesting thing related to switch hitters: My best hitter so far this Hayward has been my only switch hitter, Jose Bedreddin. He’s hit out of his mind vs RHP (1.115 OPS) while being merely good against LHP (.797 OPS).

Here are the top ten switch hitters in my data set by OPS. Note that only two of them -- Bedridden and NSH's Carter Cramer -- are getting serious reps:

ID	Batter	BatTeam	PA	BABIP	BA	OBP	SLG	OPS
60521	Kazunari Chikafuji	CCJ	38	.360	.361	.395	.778	1.173
66761	Enrique Galván	AUS	33	.333	.357	.455	.643	1.097
57722	Carter Cramer	NSH	137	.305	.320	.365	.727	1.092
56730	Isoruko Takimoto	JAX	48	.471	.409	.458	.614	1.072
73173	José Bedreddin	CHA	136	.408	.325	.375	.651	1.026
61718	J.R. Anderson	SA	38	.391	.333	.421	.576	.997
38419	Asil Çölasan	YS9	29	.300	.308	.379	.615	.995
65659	Juan Rangel	RMO	37	.200	.258	.378	.581	.959
55851	Ryan Geauxinue	BOI	57	.370	.364	.386	.545	.931
68206	Gerardo Ruíz	MAD	20	.273	.250	.400	.500	.900

[RonCo]

There are 32 switch hitters with 100 or more PA so far this season, here they are: (note how many are sub-.700 OPS)

ID	Batter	BatTeam	PA	BABIP	BA	OBP	SLG	OPS
70573	Craig Williams	SAC	163	.388	.309	.356	.395	.751
60634	Bane McCoy	CCJ	153	.248	.250	.314	.479	.792
50790	Rich Dares	PHX	149	.278	.240	.336	.310	.646
56656	Richard Vernon	CPF	146	.333	.269	.329	.351	.680
67567	Leo Hollenbeck	MAD	145	.300	.256	.359	.352	.711
62679	Resurrection Santos III	CLG	141	.327	.308	.362	.523	.885
66055	Roberto Hampton	LV	138	.274	.238	.319	.361	.679
57722	Carter Cramer	NSH	137	.305	.320	.365	.727	1.092
73173	José Bedreddin	CHA	136	.408	.325	.375	.651	1.026
60363	Mike McClure	BIK	136	.298	.233	.272	.403	.675
65144	Koray Kapkin	VAL	135	.366	.286	.333	.405	.738
66184	Bülent Kazaz	CLG	135	.295	.256	.304	.413	.717
65509	Mitch Wareham	HAW	135	.283	.252	.296	.402	.698
70343	Justin Vaive	CLG	134	.321	.239	.321	.359	.680
71248	Lúcio Guevara	RMO	131	.258	.252	.321	.454	.774
56652	Amphibian Johnson	SAC/VAN	131	.292	.248	.282	.344	.626
58914	Shane Holmes	RMO	126	.176	.160	.294	.349	.643
66341	Kata Ishibashi	BIK	126	.232	.227	.270	.370	.640
72314	Fadeuka Hadonov	VAN	122	.299	.275	.287	.358	.645
61851	Keith Williams	BIK	119	.261	.205	.235	.286	.521
55532	Steveland Morris	LBC	118	.247	.225	.263	.369	.632
72365	Pedro Vargas	LBC	117	.352	.306	.342	.477	.819
72270	Masakado Matsunaga	DM	116	.284	.284	.328	.523	.851
59077	Artus Kihlstedt	NO	112	.275	.221	.330	.326	.657
68439	Çelik Lüfi	CLG	109	.214	.182	.257	.333	.590
76722	José Jackson	LOU	108	.284	.275	.315	.549	.864
42756	Calvin Johnson	OMA	108	.333	.279	.296	.394	.691
66593	Haydar Syeda	AUS	108	.219	.180	.287	.292	.579
62505	Jesús Romero	VAL	107	.218	.194	.252	.296	.548
55976	Sammy McNeill	POR	107	.200	.188	.234	.277	.511
61219	Carlos Marcillas	TWC	105	.224	.205	.333	.432	.765
55671	Julius Lewis	SA	101	.214	.163	.228	.207	.434

[Bob Breum]

Many switch hitters have a serious platoon factor. I always check that whenever I am considering a player who switch hits. More often than not, they favor batting from the left side, which is obviously preferable.

[RonCo]

Per our discord chat, here is the same base data for last year (2061):

Splits	BABIP	BA	OBP	SLG	OPS
LHB	.295	.260	.323	.428	.751
vs RHP	.297	.263	.330	.440	.770
vs LHP	.286	.250	.304	.394	.697
---	---	---	---	---	---
R	.294	.261	.321	.418	.739
vs LHP	.295	.261	.326	.425	.750
vs RHP	.294	.261	.318	.415	.733
---	---	---	---	---	---
S	.293	.253	.319	.395	.714
vs. LHP	.288	.250	.313	.393	.706
vs. RHP	.295	.254	.321	.396	.717
---	---	---	---	---	---
Grand Total	.294	.260	.321	.419	.740

So, RHB did exhibit strong splits against the platoon advantage--but not in BABIP & Batting average. Again, its all in OBP and slugging, but that advantage is roughly the same as the gap in splits for LHB. Also, as expected, switch hitters were generally better from the left side of the plate. They were still the "worst" hitters overall...but still better than LHB vs. LHP.

General aside: This seems to me to continue to show that the main reason LHP are so valuable is that they literally destroy LHB. If you are on defense, you 100% want a LHB/LHP matchup. If you are on offence, you 100% want a LHB ve. RHP matchup. The RHB mtchups fit between the two LHB, and basically the switch hitter is mostly valuable (unless you have a "True Switchie" who can hit both ways) to avoid the LHB/LHP matchup.

[RonCo]

Still, the bottom line is (I think) that while splits for LHB are fairly wide (and the effect of splits is still moderately substantial), based on some data I've seen using older historical data (https://retrosheet.org/Research/SmithD/Platooning.pdf), they should still probably be a little bigger all around.

[breum]

Okay but can we get a graph rating wise? I'd wager the platoon factors are minimal in ratings and this is somewhere we need to improve player generation. I am curious though if the ratings differential is larger for power/gap rather than contact. That would be strange to me but would seem to explain your results. Also, per your link, there is basically no platoon factor for righties, which is a problem. Also there is no column listed to show the totals that these numbers are extrapolated from. What is the sample size for each of these groups?

[RonCo]

Yes, the data here suggests that splits for (at least) RHB BABIP/Contact are not strong enough. LHB splits look kind of okay, but could also stand some expansion.

Regarding how the splits look as we can the profile, I will still note that the change in rating spans will directly affect this--especially in the 1-5 range. A 10 raw-point split will show up far less often if the rating bar span is 60 points than it will if that same rating bar is 20 raw points.

[Trebro]

What this tells me is platoons are generally good but if the platoon made can't hit well enough then it's not necessarily worth it. it's also useful to keep enough good LHP around for matchups.