OF Arms

Yesterday, David announced that the UZR data presented here on the site has been updated to include outfield arm ratings and double play ratings for infielders. So, today, I figured I’d take a look at some of the guys who have been standouts in those categories. This afternoon, we’ll look at outfield arms.

ARM ratings, like UZR, vary a bit from year to year. Because of that, it’s generally better to look at more than one season’s worth of data to get an idea of how much value a player is adding with his throwing ability from the outfield. So, here are the leaders in ARM over the past three years:

Alfonso Soriano – +25.6 runs
Jeff Francoeur – +23.4 runs
Ichiro Suzuki – +12.5 runs
Nick Markakis – +10.8 runs
Michael Cuddyer – +10.4 runs

and now the trailers over the same time period.

Brian Giles – -19.5 runs
Juan Pierre – -16.3 runs
Jermaine Dye – -13.5 runs
Shawn Green – -12.3 runs (and he didn’t play in ’08!)
Adam Dunn – -12.2 runs

As you can see, the spread in value of a strong arm versus a weak arm is significantly smaller than it is with range. The very best arm is +45 runs compared to the very worst arm over a three year period. In range, the spread is almost 100 runs from best (Carl Crawford) to worst (Brad Hawpe). So, while arm strength is nice, it is simply not as important as range.

That doesn’t mean that it doesn’t have any impact, though. Over the last three years, Soriano is averaging +8.5 runs per season with his arm. That’s almost a win per year in value. Likewise, Francouer, Markakis, Ichiro, and Cuddyer get significant value from their ability to gun down runners and hold runners from advancing.

These numbers cover 2006 to 2008. But, what if we go back in time, and look at 2003 to 2005?

At the top, we see Jim Edmonds at +21.8 runs, followed by Richard Hidalgo (+17.9), Alex Rios (+17.1), Rocco Baldelli (+16.8), and Ichiro again (+14.0). The noodle arms are led by Juan Pierre (-18.4), Jason Bay (-13.8), Tike Redman (-13.7), Brady Clark (-13.2), and Johnny Damon (-13).

Pierre, as you may have noticed, shows up in the bottom of both three year periods. Indeed, since 2002, Pierre’s arm has been worth -42.2 runs, canceling out more than half of the +70.9 runs he got with his range. He has been consistently awful at throwing, and it’s just yet another reason why the contract the Dodgers gave him was absurdly awful.

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Dave is a co-founder of USSMariner.com and contributes to the Wall Street Journal.

14 Responses to “OF Arms”

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  1. Xeifrank says:

    Quick question… are +10 run arms from a RFer, CFer and LFer all of equal value? ie – if you move a +10 arm from CF to LF would you expect to see an increase in arm value (given a good sample size of course)?
    vr, Xei

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  2. philosofool says:

    just when you thought Adam Dunn’s defensive skill set couldn’t get any worse….

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  3. Anthony says:

    Letting Shawn Green Play RF still ranks up there as one of Omar/Willie’s worst decisions, right after trading for him.

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  4. lookatthosetwins says:

    One person that really stands out on the list to me is Edmonds. I’ve never thought that he had a particularly good arm for a centerfielder. One thing that separates him from a lot of other fielders, though, is the fact that he plays a very short center. I wonder if this led to an increase in his arm rating.

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  5. lookatthosetwins says:

    Just curious,

    Are you going to explain the methodology used to get these ratings? How does it compare to those used at THT?

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    • Mike K says:

      I second this. Soriano and Ichiro! for example match up very well (with half a run) over the three year period with THT’s ratings. Francoeur however is off quite a bit (he’s listed as 5 runs worse at THT). So I’m certinly curious as to the methodology, where the differences are, and why this one is “better”.

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    • Matt Harms says:

      I’d be curious on the methodology too, especially how it handles situations where runners just flat-out won’t run on guys.

      Because to me, this doesn’t explain who has the best arms in the league, but rather, which outfielders convert outs when people DO run on them. (And this probably explains why Soriano’s number is so how: people just keep running on the guy despite his incredibly high outfield assists in left).

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  6. Paul says:

    I always read that its very difficult to quantify the defensive contribution of catchers. I’ve always assumed that a big part of that was the impact of a catcher’s reputation on potential base stealers. Those with a reputation of a strong arm see fewer chances (and contribute defensively just by having the reputation). Does something similar play into outfielder’s ARM ratings? It seems like runners might be less likely to take an extra base if they know the outfielder has a cannon. Is there any way to consider that effect (if it exists at all)?

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    • lookatthosetwins says:

      I know from the hardball times study that they gave a certain score when a runner doesn’t advance in situations where a runner usually would advance. I’m sure this study does something similar. Runner on second holding at third will give you a certain score, throwing him out at home will give you a much larger score, and him scoring will give you a negative score.

      What doesn’t get measured is when a player hits a ball off the baggy (as a Twin’s fan, this example really sticks out in my mind) and stays at first because of Cuddyer’s arm. I doubt in most parks this matters much, but I can remember quite a few instances where this happened. This probably only happens very much in Minnesota and Boston though, so trying to give Cuddyer or Manny a rating for this would be close to impossible. I generally just assume that Cuddyer, at least for one more year (until the new park is finished) is more valuable than any ARM rating will show.

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  7. Brian Cartwright says:

    “What doesn’t get measured is when a player hits a ball off the baggy”

    It can be measured if the study is modeled that way. MGL will have to be the one to say for sure what went into his formula.

    In general, on steals, batters stretching and runner stretching, the runner can be held, advanced, or thrown out trying to advance. Each of these, depending on the base and number of outs, has an expected rate of ocurrence and run value. In each situation, calculate the expected holds, advances and kills (usually based on what everyone else has done in the same situation, long term) and subtract the observed value, then multiply the difference by the run value. Finally, sum all the run values for each situation into a season total for each player.

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    • lookatthosetwins says:

      I guess we’ll wait and see until the methodology comes out, but it really depends on if the pbp data includes if the ball was hit over the fielder’s head or not. If it doesn’t, then I can’t imagine how they could capture this effect.

      With a runner on second on a single, there is a certain probability of him scoring. With a runner on third on a fly ball, there is a certain probability of him scoring.
      If you give credit for every time someone hits a ball to the outfield and doesn’t go to second base, then you have real problems. This play is sort of a flukey play that usually only happens in parks with very short porches. If you say that out of 100 times, a batter went to second 20 times, went to third 5 times, and stayed at first 75 times, and give the fielder credit accordingly, then you are really giving him credit depending on if your pitchers gave up more doubles than singles, and not any type of skill the fielder posseses.

      I could certainly be wrong, but I really doubt that this type of play was taken into account. This really isn’t a big deal though, as it really only happens in a few parks, and not that often at them.

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  8. MGL says:

    Didn’t see this thread until today. I pretty much do the same thing as THT. Outfielder’s get credit (plus or minus) depending on what the runners do on a hit or a fly ball out. A runner can stay put, advance, or get thrown out. So a fielder will get credit not only if he throws out more than his share of runners, but also if he keeps more than his share of runners from advancing extra bases.

    I adjust for park effects, like LF at Fenway (where the assumption is that the LF’er plays close) or all fields in Coors (where the OF’ers play deep).

    I also account for the type of hit (line drive, fly ball, etc.), the speed, and the location of the ball (where it is caught or lands), as well as the number of outs. And I put different base runner configurations in different buckets – e.g. runners on 1 and 2 are treated differently than a runner on 2 only. Obviously these are important variables.

    I don’t do anything for a fielder who may prevent a player from stretching a single into a double, or double into a triple, because there is really no good way of knowing this from the data with any degree of reliability. (I suppose I could look at how many singles, doubles, and triples an outfielder allows for each location, speed, and type of batted ball. In fact, I think I looked at that a while ago and found that indeed the players with best arms also allowed fewer doubles as compared to singles and triples as compared to doubles, to the tune of a couple more runs a year.)

    I do, of course, include in the “credit” column when a fielder throws a runner out attempting to stretch a hit. And again, all of the credits and demerits are based on the the league-average rate. For example, if there were 100 singles against an OF’er (on a certain batted ball type in a certain location with a certain number of outs) and he threw out 3 (3%) attempting to stretch, and the average OF’er threw out 2% given the same batted ball characteristics and outs, then the OF’er would get some credit equal to the value of erasing a runner on first (like a CS) with that many outs.

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  9. MGL says:

    One more thing. When you look at even several years of combined arm data, and you see a spread of 45 runs, like David shows above, the actual spread in true talent is less than the spread of what you see. Obviously the more the number of years, the closer the observed spread is to the actual spread, but the former is always larger than the latter. In this case, a spread of 45 runs in 3 years is probably equivalent to a “true” spread of maybe 35 runs or so, or 12 runs a year (+6 to minus 6). If we assume that the largest spread we see is equivalent to around 3 SD, then I think it is safe to assume that the SD of arm talent is around 2 runs per season. Compared to around 5-7 runs per season in UZR range and errors for OF (5 at the corners and 7 in CF). (These are educated guesses). Which makes arm maybe 25% of total defense in the OF.

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  10. The Typical Idiot Fan says:


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