Every year, a discussion of the definition of “value” inevitably comes up in the context of the MVP awards. That discussion is particularly prominent this year with Mike Trout, who was inarguably the best player in the American League, unlikely to win the award because his team sucked. The anti-Trout side of the argument goes: the MVP is for the most valuable player, and you can’t be that valuable if your team didn’t win anything.

But value goes both ways. If the Angels would have had the same season result – no playoffs – with or without Trout, the same can be said for, say, the Cubs and Kris Bryant. Bryant or no Bryant, the Cubs almost certainly would have won their division and probably would have still held the National League’s best record. Bryant, however, is likely to be announced tonight as the NL MVP, whereas Trout will probably get a fourth (!) consolation prize. Bryant wasn’t really all that crucial to his team’s success; his value is diminished by the fact that his teammates didn’t need him!

Now, that argument might sound silly, but I don’t know that it’s that much sillier than the argument against Trout. Taking the word “value” literally, the question becomes: who was most important to their team’s success? If you want to get into the nitty-gritty of value, isn’t that what you’re really asking?

To that end, I created a way of looking at how many wins each MVP candidate contributed to their specific team. I did this by subtracting each player’s offensive runs created (“Off” on our leaderboards) from their team’s runs scored and adding each player’s defensive runs saved (“Def”) to their team’s runs allowed. I then recalculated the team’s Pythagorean record. The result is a sort of wins-above-average-per-162 statistic, specific to the team, which allows us to asses where on the win curve the team would have been left without the player.

The win curve part is important because it allows for a distinction between a player like Bryant, who makes his team’s Pythagorean record budge from 107 wins to 102, and a player like Corey Seager, whose team goes from 90 to 85 – a much more drastic change in playoff chances.

wcurve

So here are several top performers from both leagues, sorted entirely unscientifically by what looked to me like the most impressive contribution to their team.

AL Team-Specific Value
Player Team Off Def Wins Added Over Avg Win Change WAR
Josh Donaldson TOR 46.3 4.2 5.08 90.6 » 85.6 7.6
Mookie Betts BOS 40.7 10.6 4.48 98.2 » 93.7 7.8
Francisco Lindor CLE 10.8 27.7 3.97 91.3 » 87.3 6.3
Robinson Cano SEA 30.5 3.4 3.34 87.1 » 83.8 6.0
Kyle Seager SEA 24.4 6.0 3.01 87.1 » 84.1 5.5
Mike Trout LAA 67.7 0.7 7.38 80.0 » 72.6 9.4
Jason Kipnis CLE 14.8 9.1 2.39 91.3 » 88.9 4.8
Jose Altuve HOU 43.3 -2.5 4.31 83.4 » 79.1 6.7
Manny Machado BAL 23.7 15.9 4.03 83.9 » 79.9 6.5
Ian Kinsler DET 22.8 10.7 3.37 83.9 » 80.6 5.8
Carlos Correa HOU 21.1 4.7 2.68 83.4 » 80.7 4.9
Dustin Pedroia BOS 12.7 14.8 2.53 98.2 » 95.6 5.2
Adrian Beltre TEX 22.6 15.2 3.69 81.8 » 78.1 6.1
Adam Eaton CHW 16.8 18.0 3.66 77.9 » 74.3 6.0
Brian Dozier MIN 31.9 2.3 3.38 65.8 » 62.4 5.9
David Ortiz BOS 37.1 -15.2 1.50 98.2 » 96.7 4.4
Miguel Cabrera DET 32.8 -8.4 2.44 83.9 » 81.5 4.9
Gary Sanchez NYY 18.5 4.9 2.55 78.6 » 76.1 3.2
Kevin Kiermaier TBR 8.9 13.8 2.40 76.6 » 74.2 3.8
Evan Longoria TBR 18.8 2.0 2.29 76.6 » 74.3 4.5

 

NL Team-Specific Value
Player Team Off Def Wins Added Over Avg Win Change WAR
Corey Seager LAD 33.9 17.5 5.51 90.4 » 84.9 7.5
Brandon Crawford SFG 8.4 28.0 4.07 90.2 » 86.2 5.8
Justin Turner LAD 18.6 16.0 3.73 90.4 » 86.7 5.6
Daniel Murphy WSN 43.3 -7.6 3.30 97.1 » 93.8 5.6
Kris Bryant CHC 49.1 11.0 5.57 107.7 » 102.1 8.4
Anthony Rendon WSN 12.4 12.9 2.67 97.1 » 94.5 4.7
Neil Walker NYM 11.0 10.9 2.52 87.2 » 84.7 3.7
Brandon Belt SFG 28.0 -6.0 2.23 90.2 » 88.0 4.4
Buster Posey SFG 9.1 10.8 2.19 90.2 » 88.0 4.0
Joc Pederson LAD 17.2 3.3 2.13 90.4 » 88.3 3.6
Nolan Arenado COL 19.8 8.6 2.50 79.7 » 77.2 5.2
Christian Yelich MIA 27.0 -5.3 2.54 78.0 » 75.5 4.4
Starling Marte PIT 20.7 1.4 2.26 78.1 » 75.8 4.0
Dexter Fowler CHC 25.8 2.7 2.49 107.7 » 105.2 4.7
Addison Russell CHC -2.4 21.9 2.38 107.7 » 105.3 3.9
Anthony Rizzo CHC 34.6 -5.8 2.23 107.7 » 105.4 5.2
Joey Votto CIN 45.7 -18.7 3.15 68.0 » 64.9 5.0
Freddie Freeman ATL 45.5 -7.7 4.48 67.6 » 63.1 6.1
Jean Segura ARI 27.7 -1.0 2.62 68.6 » 66.0 5.0
Paul Goldschmidt ARI 34.6 -10.4 2.55 68.6 » 66.1 4.8

For the record, I would vote for both Trout and Bryant. I don’t agree with this line of thinking. This is just another way to look at it, and if you want to make an argument for Mookie Betts, Josh Donaldson, or Corey Seager, it’s a pretty compelling one.

The obvious caveat is that by using Pythagorean record, this method doesn’t measure exactly what happened, it measures what probably should have happened. That’s a whole ‘nother argument to have in regards to the MVP; we see it pop up as well in the Cy Young race with ERA vs. FIP. Additionally, the exact interactions between team and player are more complicated than just adding and subtracting total runs. This method isn’t perfect. But it’s fun to think about nonetheless.