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By Tangotiger 04:03 PM

There’s two things that we care about the most in evaluating the range of an outfielder: how much distance does he have to cover, and how much time does he have to cover it. Distance over time. That’s the definition of speed. The entire problem with fielding metrics is the concept of uneven opportunities. You see, when it comes to hitters, they all face very similar opportunities: they face similar pitchers throwing to a similar strike zone in similar parks with similar fielders. It’s not as if what Mike Trout is facing is much different than what Josh Donaldson is facing. Whatever differences exist is very much on the periphery.

But for fielders, we don’t have that situation at all. A fielder can get a bunch of balls hit right at him for easy outs, or he can get a bunch of balls that even Willie Mays might have problems with. It’s like crediting Barry Bonds with an out instead of an IBB, because he didn’t get a hit. We need to be able to understand the quality of opportunities for our fielders.

The first thing we’ll do is plot all balls in play, based on how far the RF was to the ball when it landed or would have landed had it not been caught, and how much time that ball was in the air.

The red dots are the outs by the RF, the blue lines are the outs by another fielder, and the green triangles are the hits. You can see the three clear zones, along with the overlapping sections. As you’d expect, when a ball is in the air long enough, the ball will get caught, and if it’s not in the air long enough, it won’t.

Most of these batted balls have nothing to do with the RF, or more importantly, nothing to do with the talent of the RF. So, let’s section off the above chart. First, we’ll focus on all the “automatic hits”.

These are balls that no one had a chance to make a play, be it infielder or outfielder. As you can see a third of one percent of these batted balls were turned into an out by a RF. Next are the “easy outs”:

In this case, the hangtime and/or distance needed allowed for either the RF or one of his mates to make the play. Less than 3% are hits, with the vast majority of those right along the boundary lines. When we section off data like this, we’re always susceptible to those boundaries.

Then the next section is the balls that are unplayable by the RF.

In this case, the RF is essentially a bystander, as the play is happening in the infield, or elsewhere in the outfield. Just one out of every 2000 such plays are made by the RF. If we put it all together, we see that these balls comprise the vast majority of all batted balls, and that these batted balls show almost nothing of the talent of the right fielder.

More importantly, our focus is on the middle area. Let’s focus on that section, and we’ll blow it up:

This section is the Opportunity Space of our rightfielder. The average BABIP in this section is around .400, that is, 0.4 hits per ball in play (in this Opportunity Space).

Even this section can be further sectioned off, as most of the outs are in the upper band and most of the hits are in the lower band. However, if you are a really good outfielder, then you will make outs where hits are dropping in for others. Similarly, a poor fielder will allow hits to drop in where most other fielders are catching them. For example, let’s take this Opportunity Space, and limit it to four great-fielding rightfielders: Adam Eaton, Jason Heyward, Mookie Betts, and Peter Bourjos.

We see plenty of red, the outs they are making. They are making twice as many outs as hits dropping in. Including the outs made by their mates, we see that in this particular Opportunity Space, a space that is mostly owned by the RF, their team BABIP is .284. Remember, league average is around .400. We can also compare this to a set of poor-fielding rightfielders:

And we see plenty of green. The overall BABIP in this SIMILAR Opportunity Space is .485, which is worse than the league average and much worse than our great-fielding outfielders.

And this is the key. The Opportunity Space. Now that we can focus on similar Opportunity Space, we can make fair comparisons. The Straight Arrow readers are already thinking ahead here, since even this particular opportunity space can be further sectioned off. And this has been done as well. Once I do that, once I create subzones, we can make even clearer comparisons. And the great fielders make about 0.12 more outs per ball in their Opportunity Space. And the poor fielders are about 0.10 fewer outs per ball in Opportunity Space. Fielders have about 120 balls in their Opportunity Space per season. That is, a rightfielder’s range talent is tested about 120 times per season. And so you can see that the range of outs made between the best and worst rightfielders is about 25 outs, which is around 20 runs.

This is actually in-line with what you see from other fielding metrics. So, did we do all this for nothing? Nope. Statcast gives us two huge benefits.

The uncertainty range is much smaller. If you compare the best of the publicly available fielding metrics to Statcast, you get a range of +/- 5 runs for every single rightfielder. If you see someone with a +6 runs, then you can feel confident you are seeing +1 to +11 runs. And if you see someone with a +10 run value, then you can feel confident you are seeing between +5 and +15. But, how confident are you that the +10 player performed better than the +6? StatCast reduces that uncertainty substantially. Statcast gets us there much much faster. Compare for example Adam Eaton and Matt Kemp’s catch charts, courtesy of @darenw:

The lower line represents a speed of 32 feet per second, with a 1.5 second “startup” time. The line above that is 30 feet per second with a 1.75 second startup time. As you can see, Adam Eaton has several balls in that dark red region, whereas Matt Kemp has zero. Put simply, Adam Eaton runs faster than Matt Kemp, and so, he can get to more balls. There’s also a player’s jump and routes to consider, but we can synthesize all of that into one speed number. And as you’ll see as we continue this series, we’ll be able to come up with even better estimates of talent than the above process of binning/sectioning has been showing. The main point is that if you see a player with balls caught in the red zone, he is a quality outfielder, and the more balls you see caught in that zone, the better he is. Even if you don’t know the number of opportunities! Only certain types of players can hit 450 HR, and only certain quality of outfielders can catch balls that require 30 to 32 feet per second of running speed.

Because Statcast has the distance value for each play as well as the hangtime, it has the two central figures that a fielding metric needs. And those two values allows us to limit the uncertainty and do so with a much smaller sample size than we’d otherwise need. We’re in the top of the second…