### Platoon Effects in Baseball

One general topic that I’ve explored over the years is situational effects in hitting. In Curve Ball, for example, I looked at the home/away, opposite side/same side, ahead in the count/behind in the count effects and looked for interesting patterns. The big quest was to find situations where players really showed different talents for doing better in particular situations. For example, we’d love to find players with clutch talents, not players who have occasional clutch performances.

Anyway, I recently revisited the so-called platoon effects — how players hit better against pitchers of the opposite arm. For example, you could look at players in the 2016 season who had at least 100 PA against pitchers of both arms and look at the situational effect

Effect = wOBA (opposite arm) – wOBA (same arm)

But this analysis has a hidden bias. By only considering players who have at least 100 PA against each pitcher side, we are censoring hitters like Ryan Howard who really did not get the opportunity to bat much against left-handers. And a hitter like Howard would likely have a large Effect if he was given the opportunity to bat against righties and lefties. Generally hitters who are given the opportunity to bat against both pitcher sides may have smaller platoon effects than those who don’t have the same opportunity (like Howard).

### Platooning

Anyway, I realized that before I do a better analysis of platoon effects, I need to have a better understanding how players are platooned in current baseball. What do I know about platooning?

- There are more right-handed pitchers than lefties, so regular players who bat left would have a platoon advantage in a majority of plate appearances.
- Left-handed hitters would have larger platoon advantages then right-handed hitters.
- Managers often exploit the platoon advantage late in the game, especially in the choice of pinch-hitters.
- Although everyone believes in the platoon effect, I am unsure if teams or managers really have a good sense of the size of the effect. For example, should a team bat a good hitter without the platoon advantage or an average hitter with the platoon advantage? The answer to this question would depend on the size of the “true” platoon effects.

### A Platoon Graph

Using Retrosheet play-by-play data for the 2016 season, I collected the number of PA against right-handed and left-handed pitchers for each hitter. I computed the “platoon advantage percentage” defined by the percentage of PA facing pitchers of the opposite arm. In the following graph, I plot the platoon percentage against PA for all hitters. I have colored the points by the batter side “R”, “L”, or “B”.

The overall platoon advantage percentage for all hitters is about 53%. But basically few hitters have a platoon advantage close to 53 %. This graph clearly shows that left-handed hitters have a much larger platoon advantage than righties. The switch-hitters have platoon advantages close to 100%, but there are a few lefties with platoon advantages in the 90’s. Also this graph shows that the platoon advantage decreases for batters with more PAs. Regulars can get by with smaller platoon advantages since they are better hitters. There are some right-handed hitters with few PA (between 100 and 200) and high platoon advantages.

Out of curiousity, I was interested in identifying the top 10 hitters with at least 100 PA and the highest platoon advantages (Ryan Howard is 6th on the left-handed hitter list).

The right-handed hitters:

Name N P_opp 1 Franklin Gutierrez 283 76.7 2 Kelby Tomlinson 118 66.1 3 Enrique Hernandez 243 58.4 4 Mac Williamson 127 58.3 5 Austin Romine 174 56.9 6 Shane Robinson 109 56.0 7 Nolan Reimold 227 51.1 8 Billy Butler 273 50.5 9 Juan Lagares 155 49.7 10 Adam Rosales 246 46.3

The left-handed hitters:

Name N P_opp 1 Max Muncy 132 96.2 2 John Jaso 431 94.4 3 Steven Moya 100 94.0 4 Seth Smith 437 92.4 5 Justin Bour 312 90.4 6 Ryan Howard 360 90.3 7 Jarrod Dyson 327 89.9 8 Chris Coghlan 297 89.9 9 Rafael Ortega 198 89.9 10 Stephen Drew 165 89.7

### Going Forward

After this brief exploration, my interests in this general problem have changed. Since my basic analysis of platoon advantage effects seems flawed, it seems that I need a better understanding how teams use the platoon advantage. It would be interesting, for example, to see how teams vary with respect to platooning and see how this strategy has changed over the years.

Here is some Baseball-Reference history on platooning in baseball.

### Added on January 12

Here’s a response to several comments I received yesterday.

First, maybe I did not clearly distinguish platoon advantage from a platoon effect. Platoon advantage just means the percentage of PA’s where a hitter faced a pitcher of the opposite arm. Ryan Howard was used by the Phillies primarily against right-handers, so his platoon advantage is very high. Platoon effect is a measurement of how much better a hitter performs against pitchers of opposite arms (compared with the same arm). Really we don’t know much about Howard’s 2016 platoon effect since he had few opportunities to hit against righties.

Second, someone asked about my R code. Here is a function platoon_dist2() that will produce this graph from Retrosheet play-by-play data. Once you’ve loaded the function and have the Retrosheet data available, just type …

platoon_dist2(d2016, 2016)

Interesting and I hope you continue along this platooning path! Would also enjoy seeing the code for that graph in R if you would be so kind.

I’m confused how you are identifying the top 10 hitters with the highest platoon advantage.

Juan Lagares is listed as #9 among RHB but his 2016 wOBA was higher against righties (.306) than lefties (.282)

Meanwhile his teammate RHB Wilmer Flores had a ,281 wOBA versus righties and a .455 wOBA against lefties

Brian, see my new material at the end of the post.