2022 Gold Glove Winners and Comparisons

2022 Gold Glove Winners and Comparisons

 Drew Duffy (November 1, 2022)

About a week and a half ago, Major League Baseball released their finalists for the Rawlings Gold Glove Awards. With my weighted errors and overall defensive output model, I took some time to predict my winners for the awards. Like I wrote in my previous post, there are still some flaws in my model that make absolute predictions difficult. I also recognized some positions that would be hard to evaluate with my current model, namely pitchers and the utility players. I have listed the 2022 winners that I predicted (highlighted in yellow):

P: Not enough data on pitchers in my model

C: Jose Trevino (New York Yankees),  J.T. Realmuto (Philadelphia Phillies)

1B: Vladimir Guerrero Jr. (Toronto Blue Jays), Christian Walker (Colorado Rockies)

2B: Andres Gimenez (Cleveland Guardians), Brendan Rodgers (Colorado Rockies)

3B: Ramon Urias (Baltimore Orioles), Nolan Arenado (St. Louis Cardinals)

SS: Jeremy Peña (Houston Astros), Dansby Swanson (Atlanta Braves)

LF: Steven Kwan (Cleveland Guardians), Ian Happ (Chicago Cubs)

CF: Myles Straw (Cleveland Guardians), Trent Grisham (San Diego Padres)

RF: Max Kepler (Minnesota Twins), Mookie Betts (Los Angeles Dodgers)

Utility: Working on a better way to evaluate these types of players

I correctly predicted 11/16 gold glove winners with my model and the one’s I missed were very competitive. For NL 1B, Christian Walker was my close second after Matt Olson (Walker had better OAA and DRS but worse Weighted Errors). In the AL 2B, Andres Gimenez originally graded lower than Jonathan Schoop (Gimenez was 2nd in OAA and DRS but Schoop was 16 Outs better than Gimenez). I originally thought that AL 3B was going to be a difficult one to choose but Urius took the crown. NL SS, was the biggest toss up this year in my opinion (Rojas had the top DRS, Swanson had the top OAA, and Swanson edged Rojas in Weighted Errors, but given the values on each, Rojas slightly graded out better). Finally, AL RF, Kyle Tucker had more DRS than Max Kepler (who had better OAA). Kepler also had an advantage in Weighted Errors, so I would think this race was very close as well. 

Overall, I was hoping to at least guess 66% correct (I ended up with 68.75%) with this being my first attempt at evaluating defenders. I think there is still room for coaches and evaluators to incorporate my weighted errors idea into their evaluations in a similar way. It is clear that SABR’s SDI (SABR Defensive Index) is a good basis for the award currently but it is not a definite metric for the winners. It is also clear to see that DRS is a big factor in judging the winners as well. I would love to see some aspects of errors come into the equation in the future. I look forward to refining my defensive output model to better predict the most valuable defenders in the league for the upcoming season and hope that understanding the impact of errors can aid in determining the winners of future awards.