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Monday, August 26, 2024

Re-Leveraging Aaron Judge

By Tangotiger 09:50 AM

I introduced Leverage Index about twenty years ago. One of the early things I did with it back then, which has not really been followed-thru by anyone, is Re-Leveraging the data. I will explain what that means, using Aaron Judge as the example.

Leverage Index (LI) is simply a measure of how much impact that particular moment has on the game, in real-time. The average moment is 1.000. The highest leveraged moment (think bottom of the 9th, bases loaded, down by a run or two) will be around 10. Naturally, you can have an LI approach 0 in a blowout.

The top ace reliever will average an LI of 2.0, basically saying that the moment they come into the game has twice the impact as a random moment in a game.

AARON JUDGE

Aaron Judge, because he plays for the Yankees, and because games seem to be decided one way or the other earlier than normal, has an LI of only 0.9. That's not a reflection of HIM, but rather his circumstances. Right away, we can see that whatever he does, on average, it will be depressed by 10%. We'll take care of that in a moment.

The most crucial moment that Aaron Judge hit a HR is with an LI of almost 4, which is quite high. He has three more HR with an LI of around 2. Another 13 HR with an LI above 1. Another 13 with an LI above 0.5 Then 21 more HR with an LI of under 0.5. The average LI of when he hits a HR is only 0.78. This is much lower than his average circumstance of an LI of 0.9. When folks say that Judge hits alot of useless HR, this is what they are actually saying. How many useless HR is he hitting? I'll get back to that in a moment.

He has 31 doubles and triples. The average LI of those is 0.77, pretty much the same as his HR. This is not looking good for Judge. So far, his extra base hits are coming in substantially lower-leverage situations, even accounting for his overall low-LI to begin with.

His singles have an LI of 0.91, which is the almost the same as his overall average LI. His unintentional walks and HBP are at 0.84. His outs are also at an LI of 0.91.

Ok, so we have our evidence that Judge is actually not rising to the occasion. How can we measure that?

RE-LEVERAGING

When Judge hit that high-LI HR, the one with the LI of almost 4, that in essence meant that this plate appearance will swing the outcome of the game 4X as much as a random plate appearance. In other words, it's practically as if he had a 4-PA game in one PA. And so when he hit the HR in this situation, it is essentially as if he went 4-4 with 4 HR. And that's what we'll do: we will leverage this single PA and single HR as a 4PA event, counting it as 4 HR.

Of course, when he hits a HR in a 0.01 LI circumstance, that will count as 0.01 PA and 0.01 HR.

When we apply this to all his plate appearances, we end up with 491 plate appearances (instead of his actual 561, sans IBB). In order to properly re-leverage, we will bump up all his leveraged-stats by ~10%, so that we end up with 561 re-leveraged PA.

And when we do that, what happens? His actual 51 HR are re-leveraged as 45.4 HR. In other words, he loses 5.6 HR. And so we can say 5.6 of his HR are useless.

His 31 2B+3B become 27 when re-leveraged. So he loses 4 more extrabase hits. He gains 4 singles, loses 3 walks+HBP. And gets an extra 11 outs.

In the end, his actual wOBA of .497 ends up being re-leveraged as .467. This is a 30 point drop in wOBA, which we can easily convert to runs: divide by 1.2 and multiply by his PA of 561 to give us a loss of 14 runs.

IMPACT

In other words, whatever context-neutral value you may have as his run production, you need to drop it by 14 runs in order to properly account for the game situation. These are 14 runs that Aaron Judge did contribute to, but that the Yankees did not benefit from. So, when you translate his performance into wins, via WAR, you can consider removing 1.4 wins from his total. It all depends on whether you think it matters if his performance impacts a game in real-time or whether the circumstances are irrelevant. If the impact matters, then remove 1.4 wins. If the circumstances are irrelevant, then keep those rose-colored glasses on, I don't want to keep you from enjoying your own reality.

I will say this: the choice usually depends on how it affects your player. Had his re-leveraged performance would have gained him 1.4 wins, I am sure his legion of fans would accept the premise of Re-Leveraging.


#1    Tangotiger 2024/08/26 (Mon) @ 10:22

The biggest winners in Re-leveraging:

+3.2 wins: Profar
+3.0: McMahon
+2.6: Varsho
+2.0: Westburg
+1.9: Nimmon

And the flip side:
-2.3: Arozarena
-2.3: EDLC
-2.2: Harper (*)
-1.7: Canzone
-1.7: Toglia

(*) Where are you Jayson Stark?


#2    Tangotiger 2024/08/26 (Mon) @ 10:28

How about for pitchers?

Biggest losers in wins:
3.5: Chase Anderson
2.4: Devenski
2.3: Suarez, José
2.0: Contreras, Roansy
2.0: Rosenberg, Kenny

Biggest gainer in wins:
2.0: Kinley, Tyler
1.5: Abbott, Andrew
1.2: Thornton, Trent
1.2: Kirby, George
1.1: Salazar, Eduardo


#3    laughingstock 2024/08/26 (Mon) @ 12:56

Based on the fact that coming into this season Arozarena and Harper would likely have been included near the top of “clutch-est players” lists, I’m inclined to think this is much more luck than skill


#4    Pat Senechal 2024/08/27 (Tue) @ 00:45

I mean, these give mostly the same results as the current WPA based clutch lists right? The bottom 3 hitters match for both. So it might not be “new”, but I do think giving a weighted stat like is a nice way to show leveraged season stats.

I looked up Arozarena, and oddly enough, he was below average in career WPA before this awful season, but the championship-WPA is high. So I guess he hit better in close division races, and worse when they’re locks or out of it. And the postseason WPA/cWPA is also high, so I guess it depends what you measure.

But it has always been a noisy metric.


#5    Tangotiger 2024/08/27 (Tue) @ 01:23

I like the transparency of this method, the way we can explain it conversationally.

The other method (which is also my method that Fangraphs publishes) is a similar approach but doesn’t have this clarity to it


#6    jgf704 2024/09/03 (Tue) @ 19:42

What about the quickie version where we add in the difference between Judge’s WPA (4.7) and WAA (7.7). So -3 wins.

(A slightly more stickler version would add back in dWAR, because WAA *does* include fielding and position adjustment [dWAR components], while WPA does not, so subtract another -0.5 wins).


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