# Should Mike Trout Bunt If Jeff Mathis Bats Next?

In what’s becoming a weird tradition on FanGraphs, I wrote an article about bunting last week. It included the usual disclaimers: these are rules of thumb rather than absolutes, managers should absolutely consider edge cases, and so forth. Disclaimers are for nerds, though, and writing about bunts is a sure way to get a good amount of “Hey you have to consider the specific players doing it, stop using neutral contexts.”

Most of the time, I’d just ignore it. All players aren’t created equal, and yet rules of thumb exist. Surely managers are bright enough to realize that if Mike Trout is up there, maybe you should reconsider your guidebook written for average major leaguers. Today, though, I was looking for a topic. So let’s get Mike Trout up there! Let’s put Jeff Mathis on deck! Let’s create those corner case scenarios that everyone always mentions when writers talk generic rules.

The first scenario is simple: let’s put Mike Trout at the plate in a tie game in the bottom of the 10th. You probably already know the simple math: if instead of Trout a generic batter had the first at-bat of the inning, bunting would be a wise choice. Instead, we’re starting with Trout, followed by an exactly average team behind him.

Here are Mike Trout’s 2020 projections, presented in a way you probably aren’t used to:

Trout’s Outcome Grid, 2020 (proj)
Result Rate
Strikeout 21.1%
Other Out 36.8%
Unintentional BB 16.2%
Hit by Pitch 2.0%
Single 12.1%
Double 4.5%
Triple 0.4%
Home Run 6.9%

Rather than wRC+ or a triple slash line or anything, this is just the percentage chance of each outcome. From there, we can simply work out what happens given each outcome. On a strikeout, for example, the team ends up with a man on second and one out. Given that we’ve specified completely average hitters from then out, we can use the handy win probability chart from my last bunting article and work out the value that Trout adds swinging away.

For example, the team outright wins if Trout whacks an extra-base hit. For our purposes, we’ll also credit half of his singles with two bases and half with one — the runner on third will keep things conservative. That means that half of his singles will end up with first and third with no one out, still a pretty great situation. The walks and HBP’s result in first and second with no outs, and the remaining outs are a mixture of flyouts and groundouts. All told, the mix looks like this:

Situation After Trout
Baserunners Outs Frequency Win Pct.
Second 1 37.6% 70.4%
Third 1 20.3% 82.4%
First/Second 0 18.2% 81.5%
First/Third 0 6.1% 92.2%
Game Over x 17.8% 100%

Hey, pretty good! That works out to an 81.4% chance of winning after accounting for ties and the like. That’s not too bad, and breakeven with an intentional pass — you can see the intentional walk value in the “first and second, no outs” row of the table. It’s also better than the overall odds of a team winning when they enter the bottom of the 10th tied; that works out to 80.4% (accounting for ties, naturally). That’s right: Trout adds 1% of a win by coming to the plate there, which is honestly less than I’d expect.

One quick note: why does having runners on first and second result in more wins than only a runner on second? It’s a matter of redraws, essentially: sometimes the lead runner makes an out trying to score. When they do, having another runner a single base behind gives the team another shot. Imagine a sacrifice fly attempt with second and third and one out. If the lead runner makes an out at the plate, the batting team still has another runner in scoring position for the next hitter. It’s not a big edge, but it’s not meaningless either.

How good is Trout as a bunter? I have no idea! He has a grand total of zero sacrifice bunts in the majors, though he did rack up 16 in limited playing time in the minors. Let’s call him a dead average bunter, because I refuse to believe Trout is actively bad at anything. If he’s an average bunter, we already know the team’s equity there, again from the last article: 81.8%. It’s more or less a dead heat, but technically, Mike Trout should bunt if the hitters coming up after him are average.

To be clear, this is all pretty marginal. If my estimates for runners advancing on Trout’s outs are off, or if he’s not a very good bunter, he should probably swing away. The hitters after him matter too, of course: we’re assuming average outcomes for them, but Johnny Exactlyaverage isn’t on the Angels — he’d probably start for them at first base if he were.

Let’s start working on Trout’s teammates. Right now, Anthony Rendon will likely bat behind Trout. Wham! Now he’s Jeff Mathis, the player with the worst projected batting line in 2020, in some kind of weird delayed-Samson reaction to changing his hairstyle last year. Aside from being yet another failed long-term contract, what does that do to Trout’s decision to bunt?

First, a quick review of the probabilities of each outcome:

Situation After Trout
Baserunners Outs Frequency Win Pct.
Second 1 37.6% 70.4%
Third 1 20.3% 82.4%
First/Second 0 18.2% 81.5%
First/Third 0 6.1% 92.2%
Game Over x 17.8% 100%

Of course, with Mathis up next, things get worse. Here’s Mathis’s own grid of outcomes:

Jeff Mathis Outcomes, 2020 (proj)
Result Rate
Strikeout 34.6%
Other Out 41.0%
Unintentional BB 6.4%
Hit by Pitch 0.0%
Single 12.8%
Double 3.8%
Triple 0.0%
Home Run 1.3%

To make those interact with Trout’s outcomes, we’ll need to figure out a few more things. First, how often does a runner score from third when Jeff Mathis flies out? In his career, 40.5% of his fly outs (and pop outs) in a sacrifice fly situation have scored a run. We’ll stick with that for his fly ball outs.

Next, for groundouts, I looked up every time there was a groundball out with a runner on third, in the ninth or later, in a tie game with one out. I used the entire league and a long history to get a better idea of the proportions. That comes out to 29% of the time where the runner scores, 49.3% of the time where the batter is out, and 21.7% of the time where the lead runner is out. Now we can translate Trout’s results plus Mathis’ results into a win probability, assuming (again) that the batters after Mathis are roughly average.

With Mathis batting after Trout and Trout swinging away, their team wins from this situation about 77.1% of the time. If you’ll recall from above, that’s down from 81.4% if Mathis were an average hitter. Interestingly, that’s nearly the same as the win probability after Trout walks; Trout is an interesting case where enough of his value comes from walks that pitching to him is often going to result in a walk anyway. Substitute in an almost-as-good hitter with a lower strikeout rate, and the math would flip immediately towards walking him.

Our question, though, is whether Trout should bunt here. The answer is a resounding no. Mathis is such a wild combination of poor contact and outright strikeouts that the team would only win 73.8% of the time after Trout attempts a bunt, significantly lower than if he swings away or if the opponent walks him. At last! We’ve found a situation where naive bunting rules steer us meaningfully astray.

I mean, kind of. You don’t really need an exception to the rule to tell you that if the actual best hitter in baseball is up, with the actual worst hitter in baseball due up next, maybe you shouldn’t bunt. That’s kind of unspoken in the original rule.

In fact, because of the way baseball works, the worst hitter in baseball is tremendously unlikely to bat directly after the best hitter in baseball, particularly in a year with no double switches. To me, the more interesting finding here is that even Trout should be close to indifferent between bunting and swinging away if he comes to the plate to start the bottom of a tied extra inning.

In practice, that doesn’t mean he should be flipping a coin up there to decide what to do. It means that he can take a peek at the defense, consider who’s pitching, and occasionally drop in a surprise bunt. It’s merely a useful extra tool in his bag; if he plays it straight up 85% of the time and drops down a quick bunt 15% of the time, that’s tremendously difficult to defend. Do you want to be the third baseman charging Mike Trout as he swings away? I don’t think so.

In any case, let this be a reminder of two things. When someone suggests a rule of thumb, don’t take it as gospel. You can probably twist it around, some way somehow, until it doesn’t make that much sense. On the other hand, baseball is a game where structure matters a lot relative to talent. Spot the worst team in baseball two runs, and they’re the best team in baseball. The Orioles are favored against the Yankees if it’s the bottom of the 10th and they’re at home. Mike Trout has a wRC+ below 100 after an 0-2 count. Rules are generally very resistant to changes in player talent level, because the situation dictates the player’s actions, rather than vice versa. That doesn’t mean to believe everything you see written about baseball on the internet — definitely don’t do that! We writers make mistakes all the time, as good as our intentions are. But sabermetric writers suggest broad rules of thumb because, generally speaking, that’s a good way to think about baseball.

Ben is a writer at FanGraphs. He can be found on Twitter @_Ben_Clemens.