Juan Soto and the Mega Contract

Juan Soto has emerged as one of Major League Baseball’s most electrifying young stars. Bursting onto the scene as a teenager, he helped carry the Washington Nationals to a World Series title at just 20 years old. Since then, the left-handed slugger has only bolstered his legacy—leading all of MLB in Wins Above Replacement (WAR) in 2021 and consistently ranking among the league’s most productive hitters. After being traded twice in just over a year, Soto entered free agency and signed one of the most lucrative contracts in professional sports history: 15 years, $765 million, with an average annual value (AAV) of $51 million.

That AAV trails only Shohei Ohtani’s unprecedented $70 million deal—though Ohtani uniquely contributes as both an elite pitcher and hitter. Soto, by contrast, becomes the highest-paid player in history based purely on offensive performance, while still offering solid value as a defender in left field. Yet even more striking is how differently these two contracts are structured. Ohtani’s deal features heavy deferrals, lowering his annual payroll salary to just $28.2 million and a $46 million average for luxury tax purposes. Soto’s contract has no deferred money, placing a full $51 million on the luxury tax books each season—including $61.9 million in actual payroll during his first five years (before an opt-out).

These numbers raise important questions:
- How good does Soto need to be to justify this historic investment?
- How does his deal compare to other mega-contracts handed out in the luxury tax era?
- Are teams getting fair value when they pay premium salaries for high-WAR players, or is efficiency lost at the top?

To answer these questions, this analysis evaluates Soto’s contract through both an absolute and comparative lens. We’ll estimate how much WAR he needs to generate to match his price tag, incorporating both era-adjusted and raw WAR metrics. According to historical data, teams have paid approximately $8 million per WAR in free agency over the past two decades, equating to 3.32% of a team’s luxury tax payroll per WAR since the system’s introduction in 2003 (Paraball Notes, 2024). This benchmark will serve as a foundation for evaluating Soto’s expected value over time.

In addition to Soto’s individual valuation, we’ll also explore broader trends in free agent spending:

By integrating statistical modeling, WAR-based valuation, and historical context, we’ll assess whether Soto’s record-setting contract represents an overpay, an undervalued bargain, or simply the true market rate for generational talent in today’s MLB economy.

Data Loading

We will load in the following built-in R packages and our own datasets.

library(ggplot2)
library(dplyr)
library(knitr)
library(kableExtra)
library(tidyverse)
library(ggrepel)
library(readr)
library(ggcorrplot)
library(broom)
library(purrr)
library(ggimage)
library(scales)
load("C://Users//imksy//Documents//Juan Soto.RData")

Defining a Mega Contract

In 1991, Bobby Bonilla signed a 5 year, $29 million total deal with the New York Mets, at the time the largest contract in team sports history. Quickly afterwards, salaries starting skyrocketing across the sports landscape, as revenue and TV contracts exploded in the late 1990s through the 2000s, on top of general economic inflation. As you see, Soto now makes almost 9 times as much per year than Bonilla did. So the definition of a mega contract has changed a lot.

We specifically will be looking at contracts signed in the 21st century, as the MLB implemented the luxury tax in 2003 (more on that later). According to baseball reference, all of the top 50 largest MLB contracts have been signed in the 21st century. In order to be classified as a mega contract, we chose the cut off to be either $165,000,000 total contract value (right on top 50 all time in MLB history), or a shorter term deal worth at least $30 million AAV (i.e Alex Bregman’s new contract). We also only looked at batters for our comparisons, so we ended up with 34 mega contracts for our Juan Soto analysis, including him.

WAR values before and after mega contracts

We can split a player’s career WAR (wins above replacement) into two distinct categories; before they signed their mega contract, and after they signed their mega contract. This would allow us to easily glean why a team signed a player to a mega contract, and how well they performed compared to pre large contract days once they signed a deal in free agency. We will tier the contracts into tier 1 (above $500 million total), tier 2 (above $300 million total), and tier 3 (above $150 million total)

(Note: Alex Rodriguez’s second mega contract is listed as A-Rod)

Mega Contract WAR Summary
name period years_count total_fWAR total_bWAR total_efWAR total_ebWAR avg_fWAR avg_bWAR avg_efWAR avg_ebWAR contract_start contract_years AAV total_contract_value Mega_Contract_Tier
A-Rod after 8 22.600 23.09 26.15 28.25 2.825 2.886 3.269 3.531 2008 10 27,500,000 275,000,000 Tier 3
Aaron Judge after 2 16.537 15.29 15.08 15.44 8.268 7.645 7.540 7.720 2023 9 40,000,000 360,000,000 Tier 2
Aaron Judge before 7 35.700 36.92 35.55 38.53 5.100 5.274 5.079 5.504 2023 9 40,000,000 360,000,000 Tier 2
Albert Pujols after 10 5.600 12.75 18.03 23.82 0.560 1.275 1.803 2.382 2012 10 24,000,000 240,000,000 Tier 3
Albert Pujols before 11 81.200 86.64 76.96 85.44 7.382 7.876 6.996 7.767 2012 10 24,000,000 240,000,000 Tier 3
Alex Bregman before 9 37.372 39.61 40.77 44.42 4.152 4.401 4.530 4.936 2025 3 40,000,000 120,000,000 Tier 3
Alex Rodriguez after 7 56.100 56.40 52.63 55.92 8.014 8.057 7.519 7.989 2001 7 25,200,000 176,400,000 Tier 3
Alex Rodriguez before 7 35.000 38.06 31.74 36.47 5.000 5.437 6.348 7.294 2001 7 25,200,000 176,400,000 Tier 3
Anthony Rendon after 5 4.188 3.69 9.29 8.16 0.838 0.738 1.858 1.632 2020 7 35,000,000 245,000,000 Tier 3
Anthony Rendon before 7 32.800 30.02 34.42 32.72 4.686 4.289 4.917 4.674 2020 7 35,000,000 245,000,000 Tier 3
Bryce Harper after 6 23.591 23.27 29.87 29.21 3.932 3.878 4.978 4.868 2019 13 25,384,615 330,000,000 Tier 2
Bryce Harper before 7 30.600 27.79 33.24 31.44 4.371 3.970 4.749 4.491 2019 13 25,384,615 330,000,000 Tier 2
Buster Posey after 8 41.600 32.20 43.22 35.83 5.200 4.025 5.402 4.479 2013 9 18,333,333 165,000,000 Tier 3
Buster Posey before 4 15.700 12.64 14.55 13.76 3.925 3.160 3.638 3.440 2013 9 18,333,333 165,000,000 Tier 3
Carlos Correa after 3 9.815 10.36 10.51 11.61 3.272 3.453 3.503 3.870 2022 6 33,333,333 200,000,000 Tier 3
Carlos Correa before 7 25.000 34.08 29.59 39.79 3.571 4.869 4.227 5.684 2022 6 33,333,333 200,000,000 Tier 3
Christian Yelich after 5 11.642 10.12 15.14 14.06 2.328 2.024 3.028 2.812 2020 9 27,000,000 243,000,000 Tier 3
Christian Yelich before 7 33.800 31.75 35.79 34.01 4.829 4.536 5.113 4.859 2020 9 27,000,000 243,000,000 Tier 3
Corey Seager after 3 15.139 15.67 16.81 17.59 5.046 5.223 5.603 5.863 2022 10 32,500,000 325,000,000 Tier 2
Corey Seager before 7 23.700 21.17 28.52 27.29 3.386 3.024 4.074 3.899 2022 10 32,500,000 325,000,000 Tier 2
Dansby Swanson after 2 9.285 8.76 10.35 9.91 4.642 4.380 5.175 4.955 2023 7 25,285,714 177,000,000 Tier 3
Dansby Swanson before 7 15.200 14.59 22.53 24.01 2.171 2.084 3.219 3.430 2023 7 25,285,714 177,000,000 Tier 3
David Wright after 11 39.200 38.16 42.44 42.71 3.564 3.469 3.858 3.883 2007 12 13,750,000 165,000,000 Tier 3
David Wright before 3 12.800 11.00 14.12 12.07 4.267 3.667 4.707 4.023 2007 12 13,750,000 165,000,000 Tier 3
Derek Jeter after 10 44.700 41.23 47.45 43.56 4.470 4.123 4.745 4.356 2001 10 18,900,000 189,000,000 Tier 3
Derek Jeter before 6 23.100 28.01 21.03 28.80 3.850 4.668 4.206 5.760 2001 10 18,900,000 189,000,000 Tier 3
Fernando Tatis Jr after 3 13.709 14.73 15.46 17.72 4.570 4.910 5.153 5.907 2021 14 24,285,714 340,000,000 Tier 2
Fernando Tatis Jr before 2 6.600 6.94 10.77 11.01 3.300 3.470 5.385 5.505 2021 14 24,285,714 340,000,000 Tier 2
Francisco Lindor after 4 23.288 21.49 23.25 22.79 5.822 5.372 5.812 5.697 2021 10 34,100,000 341,000,000 Tier 2
Francisco Lindor before 6 29.400 28.10 33.63 32.55 4.900 4.683 5.605 5.425 2021 10 34,100,000 341,000,000 Tier 2
Giancarlo Stanton after 10 21.836 23.10 26.99 27.86 2.184 2.310 2.699 2.786 2015 13 25,000,000 325,000,000 Tier 2
Giancarlo Stanton before 5 21.500 21.56 22.80 24.21 4.300 4.312 4.560 4.842 2015 13 25,000,000 325,000,000 Tier 2
Joe Mauer after 8 18.300 22.04 23.77 27.61 2.288 2.755 2.971 3.451 2011 8 23,000,000 184,000,000 Tier 3
Joe Mauer before 7 34.200 33.16 35.23 35.40 4.886 4.737 5.033 5.057 2011 8 23,000,000 184,000,000 Tier 3
Joey Votto after 10 27.139 30.21 33.18 36.01 2.714 3.021 3.687 4.001 2014 10 21,800,000 218,000,000 Tier 3
Joey Votto before 7 32.400 34.31 33.27 35.90 4.629 4.901 4.753 5.129 2014 10 21,800,000 218,000,000 Tier 3
Jose Altuve after 7 28.254 24.52 32.35 29.52 4.036 3.503 4.621 4.217 2018 7 23,428,571 164,000,000 Tier 3
Jose Altuve before 7 26.600 28.23 30.87 32.11 3.800 4.033 4.410 4.587 2018 7 23,428,571 164,000,000 Tier 3
Juan Soto before 7 35.174 36.44 39.63 42.13 5.025 5.206 5.661 6.019 2025 15 51,000,000 765,000,000 Tier 1
Kris Bryant after 3 -1.367 -1.33 0.64 0.33 -0.456 -0.443 0.320 0.165 2022 7 26,000,000 182,000,000 Tier 3
Kris Bryant before 7 31.800 28.78 34.02 31.50 4.543 4.111 4.860 4.500 2022 7 26,000,000 182,000,000 Tier 3
Manny Machado after 6 24.634 23.39 30.95 30.95 4.106 3.898 5.158 5.158 2019 11 31,818,182 350,000,000 Tier 2
Manny Machado before 7 30.200 34.43 32.89 36.90 4.314 4.919 4.699 5.271 2019 11 31,818,182 350,000,000 Tier 2
Marcus Semien after 3 14.670 17.03 16.33 18.88 4.890 5.677 5.443 6.293 2022 7 25,000,000 175,000,000 Tier 3
Marcus Semien before 9 25.200 28.77 31.46 35.14 2.800 3.197 3.496 3.904 2022 7 25,000,000 175,000,000 Tier 3
Mark Teixeira after 8 18.200 19.32 23.79 25.94 2.275 2.415 2.974 3.243 2009 8 22,500,000 180,000,000 Tier 3
Mark Teixeira before 6 26.500 31.30 27.72 32.91 4.417 5.217 4.620 5.485 2009 8 22,500,000 180,000,000 Tier 3
Matt Olson after 3 12.362 14.51 14.01 16.20 4.121 4.837 4.670 5.400 2022 8 21,000,000 168,000,000 Tier 3
Matt Olson before 6 15.200 18.29 20.04 23.02 2.533 3.048 3.340 3.837 2022 8 21,000,000 168,000,000 Tier 3
Miguel Cabrera after 8 2.310 2.37 11.28 11.96 0.289 0.296 1.611 1.709 2016 8 31,000,000 248,000,000 Tier 3
Miguel Cabrera before 13 65.600 64.77 67.79 68.87 5.046 4.982 5.215 5.298 2016 8 31,000,000 248,000,000 Tier 3
Mike Trout after 6 23.158 21.66 29.30 28.71 3.860 3.610 4.883 4.785 2019 12 35,583,333 427,000,000 Tier 2
Mike Trout before 8 64.700 64.56 59.99 63.70 8.088 8.070 7.499 7.963 2019 12 35,583,333 427,000,000 Tier 2
Mookie Betts after 4 23.143 23.77 24.39 25.47 5.786 5.942 6.098 6.367 2021 12 30,416,667 365,000,000 Tier 2
Mookie Betts before 7 40.100 45.81 43.36 49.50 5.729 6.544 6.194 7.071 2021 12 30,416,667 365,000,000 Tier 2
Nolan Arenado after 6 24.171 25.33 27.67 28.91 4.028 4.222 4.612 4.818 2019 8 32,500,000 260,000,000 Tier 3
Nolan Arenado before 6 25.400 31.41 28.19 33.69 4.233 5.235 4.698 5.615 2019 8 32,500,000 260,000,000 Tier 3
Rafael Devers after 2 7.259 7.15 8.39 8.34 3.629 3.575 4.195 4.170 2023 10 31,400,000 314,000,000 Tier 2
Rafael Devers before 6 17.800 15.34 21.92 20.65 2.967 2.557 3.653 3.442 2023 10 31,400,000 314,000,000 Tier 2
Shohei Ohtani after 1 9.074 9.22 8.10 8.63 9.074 9.220 8.100 8.630 2024 10 70,000,000 700,000,000 Tier 1
Shohei Ohtani before 6 19.925 19.48 23.76 23.84 3.321 3.247 3.960 3.973 2024 10 70,000,000 700,000,000 Tier 1
Trea Turner after 2 7.719 6.37 8.39 7.45 3.859 3.185 4.195 3.725 2023 11 27,272,727 300,000,000 Tier 2
Trea Turner before 8 30.400 29.91 37.20 37.68 3.800 3.739 4.650 4.710 2023 11 27,272,727 300,000,000 Tier 2
Vladimir Guerrero Jr before 6 16.543 21.50 21.53 26.31 2.757 3.583 3.588 4.385 2026 14 35,714,286 500,000,000 Tier 1
Xander Bogaerts after 2 6.443 5.60 7.09 6.47 3.222 2.800 3.545 3.235 2023 11 25,454,545 280,000,000 Tier 3
Xander Bogaerts before 10 37.800 35.17 44.76 42.83 3.780 3.517 4.476 4.283 2023 11 25,454,545 280,000,000 Tier 3

Analyzing our mega contract players before and after their free agent signings, we have 13 players who were better before their contract kicked in, 8 players better after their contract kicked in, and 10 players about the same based on eWAR. Since the before value is slightly skewed to less WAR due to teams bringing a player up from the minors for their first MLB playtime after midseason for arbitration and contract length purposes, we used +- 0.5 average WAR for them to be equal in their play before and after. We used average WAR instead of total WAR since the years before and after were rarely equal.

Luxury Tax Implementation

In 2003, the MLB implemented the current day luxury tax, called the Competitive Balance Tax, after a failed attempt in 1997 during the players’ strike. The aim was meant to try and balance out competition across the league, instead of making it richest big market teams vs moneyball bargain bin hunting teams. From the MLB website:

“Each year, clubs that exceed a predetermined payroll threshold are subject to a Competitive Balance Tax – which is commonly referred to as a”luxury tax.” Those who carry payrolls above that threshold are taxed on each dollar above the threshold, with the tax rate increasing based on the number of consecutive years a club has exceeded the threshold.

A team’s Competitive Balance Tax figure is determined using the average annual value of each player’s contract on the 40-man roster, plus any additional player benefits. Every team’s final CBT figure is calculated at the end of each season.”

For the first year being above the luxury tax threshold, there is a 20% tax on overages, for the second year 30%, and for the third year or more, 50%. There is another surcharge for being $20 million+ above the threshold, 12% up to $40 million, 45% up to $60 million, and 60% subcharge for any higher than that. Plus, a team’s first round pick can be moved down 10 spots if they aren’t in the top 6. While the penalties are harsh, MLB teams, especally big market ones, continue to hand out these mega contracts and go above the luxury tax threshold, because at the end of the day, the only main penalty is paying more money, and building an elite team will bring in revenue to offset the losses.

Percentage of Luxury Tax Per Mega Contract

The luxury tax threshold has increased every year, few exceptions. Naturally, mega contract values have gone way up. All the tier 1 mega contracts have been signed in the 2020s. All tier 2 mega contracts have been signed in the 2010s and 2020s. And all other mega contracts in the 21st century. To adjust for this inflation and to compare contracts across different years, we can evaluate by the percentage of the luxury tax they take up, rather than straight up average salary, season by season.

Mega Contract Luxury Tax Summary
index name name_last year PA AB BB HR H SF HBP BA OBP fWAR bWAR efWAR ebWAR key_bbref key_fangraphs contract_start contract_years AAV period playerID age payroll payroll_percentage
1410 Jose Altuve Altuve 2011 234 221 5 2 61 1 2 0.276 0.297 0.200 0.61 0.88 1.26 altuvjo01 5417 2018 7 23428571 before altuvjo01 21 178000000 13.162
1411 Jose Altuve Altuve 2012 630 576 40 7 167 4 6 0.290 0.340 1.900 1.44 2.61 2.33 altuvjo01 5417 2018 7 23428571 before altuvjo01 22 178000000 13.162
1412 Jose Altuve Altuve 2013 672 626 32 5 177 8 2 0.283 0.316 0.500 1.13 1.82 2.31 altuvjo01 5417 2018 7 23428571 before altuvjo01 23 178000000 13.162
1413 Jose Altuve Altuve 2014 707 660 36 7 225 5 5 0.341 0.377 5.200 5.50 5.62 5.80 altuvjo01 5417 2018 7 23428571 before altuvjo01 24 189000000 12.396
1414 Jose Altuve Altuve 2015 689 638 33 15 200 6 9 0.313 0.353 4.400 3.98 4.94 4.42 altuvjo01 5417 2018 7 23428571 before altuvjo01 25 189000000 12.396
1415 Jose Altuve Altuve 2016 717 640 60 24 216 7 7 0.338 0.396 6.800 7.90 7.15 8.32 altuvjo01 5417 2018 7 23428571 before altuvjo01 26 189000000 12.396
1416 Jose Altuve Altuve 2017 662 590 58 24 204 4 9 0.346 0.410 7.600 7.67 7.85 7.67 altuvjo01 5417 2018 7 23428571 before altuvjo01 27 195000000 12.015
1417 Jose Altuve Altuve 2018 599 534 55 13 169 1 6 0.316 0.386 4.900 5.12 5.18 5.51 altuvjo01 5417 2018 7 23428571 after altuvjo01 28 197000000 11.893
1418 Jose Altuve Altuve 2019 548 500 41 31 149 3 3 0.298 0.353 3.500 3.77 4.00 4.13 altuvjo01 5417 2018 7 23428571 after altuvjo01 29 206000000 11.373
1419 Jose Altuve Altuve 2020 210 192 17 5 42 0 1 0.219 0.286 0.100 -0.21 1.90 1.80 altuvjo01 5417 2018 7 23428571 after altuvjo01 30 208000000 11.264
1420 Jose Altuve Altuve 2021 678 601 66 31 167 6 4 0.278 0.350 5.200 4.45 5.54 5.00 altuvjo01 5417 2018 7 23428571 after altuvjo01 31 210000000 11.156
1421 Jose Altuve Altuve 2022 604 527 66 28 158 1 10 0.300 0.387 6.600 5.22 6.65 5.76 altuvjo01 5417 2018 7 23428571 after altuvjo01 32 230000000 10.186
1422 Jose Altuve Altuve 2023 410 360 44 17 112 1 5 0.311 0.393 4.025 2.80 4.54 3.31 altuvjo01 5417 2018 7 23428571 after altuvjo01 33 233000000 10.055
1423 Jose Altuve Altuve 2024 682 628 47 20 185 0 7 0.295 0.350 3.930 3.37 4.54 4.01 altuvjo01 5417 2018 7 23428571 after altuvjo01 34 237000000 9.885
2204 Nolan Arenado Arenado 2013 514 486 23 10 130 2 1 0.267 0.301 1.800 2.48 2.54 3.07 arenano01 9777 2019 8 32500000 before arenano01 22 178000000 18.258
2205 Nolan Arenado Arenado 2014 467 432 25 18 124 5 4 0.287 0.328 2.600 3.63 3.05 4.17 arenano01 9777 2019 8 32500000 before arenano01 23 189000000 17.196
2206 Nolan Arenado Arenado 2015 665 616 34 42 177 11 4 0.287 0.323 4.500 6.33 5.09 6.64 arenano01 9777 2019 8 32500000 before arenano01 24 189000000 17.196
2207 Nolan Arenado Arenado 2016 696 618 68 41 182 8 2 0.294 0.362 5.000 5.87 5.38 6.33 arenano01 9777 2019 8 32500000 before arenano01 25 189000000 17.196
2208 Nolan Arenado Arenado 2017 680 606 62 37 187 6 4 0.309 0.373 5.700 6.74 5.93 6.83 arenano01 9777 2019 8 32500000 before arenano01 26 195000000 16.667
2209 Nolan Arenado Arenado 2018 673 590 73 38 175 6 3 0.297 0.374 5.800 6.36 6.20 6.65 arenano01 9777 2019 8 32500000 before arenano01 27 197000000 16.497
2210 Nolan Arenado Arenado 2019 662 588 62 41 185 8 4 0.315 0.379 6.100 7.26 6.13 6.58 arenano01 9777 2019 8 32500000 after arenano01 28 206000000 15.777
2211 Nolan Arenado Arenado 2020 201 182 15 8 46 4 0 0.253 0.303 1.000 1.47 2.83 3.69 arenano01 9777 2019 8 32500000 after arenano01 29 208000000 15.625
2212 Nolan Arenado Arenado 2021 653 593 50 34 151 7 3 0.255 0.312 4.000 3.97 4.34 4.20 arenano01 9777 2019 8 32500000 after arenano01 30 210000000 15.476
2213 Nolan Arenado Arenado 2022 620 557 52 30 163 4 7 0.293 0.358 7.300 7.74 7.60 8.53 arenano01 9777 2019 8 32500000 after arenano01 31 230000000 14.130
2214 Nolan Arenado Arenado 2023 612 560 41 26 149 8 3 0.266 0.315 2.633 2.37 3.14 2.67 arenano01 9777 2019 8 32500000 after arenano01 32 233000000 13.948
2215 Nolan Arenado Arenado 2024 635 578 44 16 157 7 5 0.272 0.325 3.137 2.52 3.63 3.24 arenano01 9777 2019 8 32500000 after arenano01 33 237000000 13.713
6200 Mookie Betts Betts 2014 213 189 21 5 55 0 2 0.291 0.368 1.800 2.28 2.37 2.84 bettsmo01 13611 2021 12 30416667 before bettsmo01 21 189000000 16.093
6201 Mookie Betts Betts 2015 654 597 46 18 174 6 2 0.291 0.341 4.800 6.13 5.14 6.25 bettsmo01 13611 2021 12 30416667 before bettsmo01 22 189000000 16.093
6202 Mookie Betts Betts 2016 730 672 49 31 214 7 2 0.318 0.363 8.300 9.52 8.49 9.27 bettsmo01 13611 2021 12 30416667 before bettsmo01 23 189000000 16.093
6203 Mookie Betts Betts 2017 712 628 77 24 166 5 2 0.264 0.344 5.300 6.35 5.55 6.43 bettsmo01 13611 2021 12 30416667 before bettsmo01 24 195000000 15.598
6204 Mookie Betts Betts 2018 614 520 81 32 180 5 8 0.346 0.438 10.400 10.68 8.14 8.78 bettsmo01 13611 2021 12 30416667 before bettsmo01 25 197000000 15.440
6205 Mookie Betts Betts 2019 706 597 97 29 176 9 3 0.295 0.391 6.600 7.27 6.44 6.87 bettsmo01 13611 2021 12 30416667 before bettsmo01 26 206000000 14.765
6206 Mookie Betts Betts 2020 246 219 24 16 64 1 2 0.292 0.366 2.900 3.58 7.23 9.06 bettsmo01 13611 2021 12 30416667 before bettsmo01 27 208000000 14.623
6207 Mookie Betts Betts 2021 550 466 68 23 123 5 11 0.264 0.367 3.900 3.98 4.37 4.64 bettsmo01 13611 2021 12 30416667 after bettsmo01 28 210000000 14.484
6208 Mookie Betts Betts 2022 639 572 55 35 154 4 8 0.269 0.340 6.600 6.72 6.34 6.88 bettsmo01 13611 2021 12 30416667 after bettsmo01 29 230000000 13.225
6209 Mookie Betts Betts 2023 693 584 96 39 179 5 8 0.307 0.408 8.258 8.31 8.90 8.96 bettsmo01 13611 2021 12 30416667 after bettsmo01 30 233000000 13.054
6210 Mookie Betts Betts 2024 516 450 61 19 130 4 1 0.289 0.372 4.385 4.76 4.78 4.99 bettsmo01 13611 2021 12 30416667 after bettsmo01 31 237000000 12.834
7244 Xander Bogaerts Bogaerts 2013 50 44 5 1 11 1 0 0.250 0.320 0.100 0.34 0.51 0.74 bogaexa01 12161 2023 11 25454545 before bogaexa01 20 178000000 14.300
7245 Xander Bogaerts Bogaerts 2014 594 538 39 12 129 7 8 0.240 0.297 0.100 0.74 1.58 2.07 bogaexa01 12161 2023 11 25454545 before bogaexa01 21 189000000 13.468
7246 Xander Bogaerts Bogaerts 2015 654 613 32 7 196 3 3 0.320 0.355 4.600 4.34 5.18 4.86 bogaexa01 12161 2023 11 25454545 before bogaexa01 22 189000000 13.468
7247 Xander Bogaerts Bogaerts 2016 719 652 58 21 192 3 6 0.294 0.356 4.900 3.84 5.26 4.51 bogaexa01 12161 2023 11 25454545 before bogaexa01 23 189000000 13.468
7248 Xander Bogaerts Bogaerts 2017 635 571 56 10 156 2 6 0.273 0.343 3.200 2.25 3.78 3.04 bogaexa01 12161 2023 11 25454545 before bogaexa01 24 195000000 13.054
7249 Xander Bogaerts Bogaerts 2018 580 513 55 23 148 6 6 0.288 0.360 4.900 4.90 5.23 5.31 bogaexa01 12161 2023 11 25454545 before bogaexa01 25 197000000 12.921
7250 Xander Bogaerts Bogaerts 2019 698 614 76 33 190 6 2 0.309 0.384 6.800 6.30 6.59 6.24 bogaexa01 12161 2023 11 25454545 before bogaexa01 26 206000000 12.357
7251 Xander Bogaerts Bogaerts 2020 225 203 21 11 61 1 0 0.300 0.364 1.900 1.55 4.97 4.24 bogaexa01 12161 2023 11 25454545 before bogaexa01 27 208000000 12.238
7252 Xander Bogaerts Bogaerts 2021 603 529 62 23 156 7 5 0.295 0.370 5.200 5.01 5.58 5.58 bogaexa01 12161 2023 11 25454545 before bogaexa01 28 210000000 12.121
7253 Xander Bogaerts Bogaerts 2022 631 557 57 15 171 7 10 0.307 0.377 6.100 5.90 6.08 6.24 bogaexa01 12161 2023 11 25454545 before bogaexa01 29 230000000 11.067
7254 Xander Bogaerts Bogaerts 2023 665 596 56 19 170 6 7 0.285 0.350 4.419 4.39 4.57 4.64 bogaexa01 12161 2023 11 25454545 after bogaexa01 30 233000000 10.925
7255 Xander Bogaerts Bogaerts 2024 463 428 28 11 113 6 1 0.264 0.307 2.024 1.21 2.52 1.83 bogaexa01 12161 2023 11 25454545 after bogaexa01 31 237000000 10.740
8788 Alex Bregman Bregman 2016 217 201 15 8 53 1 0 0.264 0.313 1.000 1.99 1.63 2.80 bregmal01 17678 2025 3 40000000 before bregmal01 22 189000000 21.164
8789 Alex Bregman Bregman 2017 626 556 55 19 158 7 7 0.284 0.352 3.500 4.02 4.01 4.44 bregmal01 17678 2025 3 40000000 before bregmal01 23 195000000 20.513
8790 Alex Bregman Bregman 2018 705 594 96 31 170 3 12 0.286 0.394 7.600 7.90 7.31 7.88 bregmal01 17678 2025 3 40000000 before bregmal01 24 197000000 20.305
8791 Alex Bregman Bregman 2019 690 554 119 41 164 8 9 0.296 0.423 8.400 8.89 7.95 9.17 bregmal01 17678 2025 3 40000000 before bregmal01 25 206000000 19.417
8792 Alex Bregman Bregman 2020 180 153 24 6 37 1 2 0.242 0.350 0.900 1.12 2.35 2.68 bregmal01 17678 2025 3 40000000 before bregmal01 26 208000000 19.231
8793 Alex Bregman Bregman 2021 400 348 44 12 94 4 4 0.270 0.355 2.000 2.13 2.55 2.44 bregmal01 17678 2025 3 40000000 before bregmal01 27 210000000 19.048
8794 Alex Bregman Bregman 2022 656 548 87 23 142 10 11 0.259 0.366 5.500 4.57 5.59 4.88 bregmal01 17678 2025 3 40000000 before bregmal01 28 230000000 17.391
8795 Alex Bregman Bregman 2023 724 622 92 25 163 2 8 0.262 0.363 4.345 4.87 4.57 5.19 bregmal01 17678 2025 3 40000000 before bregmal01 29 233000000 17.167
8796 Alex Bregman Bregman 2024 634 581 44 26 151 4 5 0.260 0.315 4.127 4.12 4.81 4.94 bregmal01 17678 2025 3 40000000 before bregmal01 30 237000000 16.878
10084 Kris Bryant Bryant 2015 650 559 77 26 154 5 9 0.275 0.369 6.100 5.31 6.23 5.80 bryankr01 15429 2022 7 26000000 before bryankr01 23 189000000 13.757
10085 Kris Bryant Bryant 2016 699 603 75 39 176 3 18 0.292 0.385 7.900 7.30 7.95 7.61 bryankr01 15429 2022 7 26000000 before bryankr01 24 189000000 13.757
10086 Kris Bryant Bryant 2017 665 549 95 29 162 6 15 0.295 0.409 6.700 5.65 6.64 5.88 bryankr01 15429 2022 7 26000000 before bryankr01 25 195000000 13.333
10087 Kris Bryant Bryant 2018 457 389 48 13 106 3 17 0.272 0.374 2.400 2.27 2.84 2.58 bryankr01 15429 2022 7 26000000 before bryankr01 26 197000000 13.198
10088 Kris Bryant Bryant 2019 634 543 74 31 153 2 15 0.282 0.382 4.700 4.44 5.13 4.74 bryankr01 15429 2022 7 26000000 before bryankr01 27 206000000 12.621
10089 Kris Bryant Bryant 2020 147 131 12 4 27 0 4 0.206 0.293 0.400 0.52 1.24 1.44 bryankr01 15429 2022 7 26000000 before bryankr01 28 208000000 12.500
10090 Kris Bryant Bryant 2021 586 513 62 25 136 2 9 0.265 0.353 3.600 3.29 3.99 3.45 bryankr01 15429 2022 7 26000000 before bryankr01 29 210000000 12.381
10091 Kris Bryant Bryant 2022 181 160 17 5 49 2 2 0.306 0.376 0.600 0.44 1.03 0.83 bryankr01 15429 2022 7 26000000 after bryankr01 30 230000000 11.304
10092 Kris Bryant Bryant 2023 335 300 29 10 70 0 6 0.233 0.313 -1.204 -1.03 -0.39 -0.50 bryankr01 15429 2022 7 26000000 after bryankr01 31 233000000 11.159
10093 Kris Bryant Bryant 2024 155 133 13 2 29 1 8 0.218 0.323 -0.763 -0.74 NA NA bryankr01 15429 2022 7 26000000 after NA NA 237000000 10.970
11475 Miguel Cabrera Cabrera 2003 346 314 25 12 84 1 2 0.268 0.325 0.800 0.60 1.00 0.77 cabremi01 1744 2016 8 31000000 before cabremi01 20 117000000 26.496
11476 Miguel Cabrera Cabrera 2004 685 603 68 33 177 8 6 0.294 0.366 2.300 3.45 2.65 3.55 cabremi01 1744 2016 8 31000000 before cabremi01 21 120500000 25.726
11477 Miguel Cabrera Cabrera 2005 685 613 64 33 198 6 2 0.323 0.385 5.100 5.18 5.41 5.93 cabremi01 1744 2016 8 31000000 before cabremi01 22 128000000 24.219
11478 Miguel Cabrera Cabrera 2006 676 576 86 26 195 4 10 0.339 0.430 6.300 5.78 6.84 6.34 cabremi01 1744 2016 8 31000000 before cabremi01 23 136500000 22.711
11479 Miguel Cabrera Cabrera 2007 680 588 79 34 188 7 5 0.320 0.401 5.000 3.24 5.30 3.94 cabremi01 1744 2016 8 31000000 before cabremi01 24 148000000 20.946
11480 Miguel Cabrera Cabrera 2008 684 616 56 37 180 9 3 0.292 0.349 2.600 2.71 3.22 3.34 cabremi01 1744 2016 8 31000000 before cabremi01 25 155000000 20.000
11481 Miguel Cabrera Cabrera 2009 685 611 68 34 198 1 5 0.324 0.396 5.100 5.09 5.46 5.42 cabremi01 1744 2016 8 31000000 before cabremi01 26 162000000 19.136
11482 Miguel Cabrera Cabrera 2010 648 548 89 38 180 8 3 0.328 0.420 6.100 6.47 5.85 6.31 cabremi01 1744 2016 8 31000000 before cabremi01 27 170000000 18.235
11483 Miguel Cabrera Cabrera 2011 688 572 108 30 197 5 3 0.344 0.448 6.600 7.62 6.18 7.15 cabremi01 1744 2016 8 31000000 before cabremi01 28 178000000 17.416
11484 Miguel Cabrera Cabrera 2012 697 622 66 44 205 6 3 0.330 0.393 7.300 7.14 7.20 7.32 cabremi01 1744 2016 8 31000000 before cabremi01 29 178000000 17.416
11485 Miguel Cabrera Cabrera 2013 652 555 90 44 193 2 5 0.348 0.442 8.600 7.49 8.10 8.09 cabremi01 1744 2016 8 31000000 before cabremi01 30 178000000 17.416
11486 Miguel Cabrera Cabrera 2014 685 611 60 25 191 11 3 0.313 0.371 5.200 5.07 5.57 5.46 cabremi01 1744 2016 8 31000000 before cabremi01 31 189000000 16.402
11487 Miguel Cabrera Cabrera 2015 511 429 77 18 145 2 3 0.338 0.440 4.600 4.93 5.01 5.25 cabremi01 1744 2016 8 31000000 before cabremi01 32 189000000 16.402
11488 Miguel Cabrera Cabrera 2016 679 595 75 38 188 5 4 0.316 0.393 4.800 5.07 5.12 5.68 cabremi01 1744 2016 8 31000000 after cabremi01 33 189000000 16.402
11489 Miguel Cabrera Cabrera 2017 529 469 54 16 117 3 3 0.249 0.329 -0.200 -0.93 1.34 1.14 cabremi01 1744 2016 8 31000000 after cabremi01 34 195000000 15.897
11490 Miguel Cabrera Cabrera 2018 157 134 22 3 40 1 0 0.299 0.395 0.700 0.23 1.32 0.87 cabremi01 1744 2016 8 31000000 after cabremi01 35 197000000 15.736
11491 Miguel Cabrera Cabrera 2019 549 493 48 12 139 5 3 0.282 0.346 -0.300 0.00 1.06 1.41 cabremi01 1744 2016 8 31000000 after cabremi01 36 206000000 15.049
11492 Miguel Cabrera Cabrera 2020 231 204 24 10 51 2 1 0.250 0.329 0.300 0.09 2.51 2.52 cabremi01 1744 2016 8 31000000 after cabremi01 37 208000000 14.904
11493 Miguel Cabrera Cabrera 2021 526 472 40 15 121 9 5 0.256 0.316 -0.700 -0.56 0.68 0.92 cabremi01 1744 2016 8 31000000 after cabremi01 38 210000000 14.762
11494 Miguel Cabrera Cabrera 2022 433 397 28 5 101 5 3 0.254 0.305 -1.500 -1.14 -0.75 -0.58 cabremi01 1744 2016 8 31000000 after cabremi01 39 230000000 13.478
11495 Miguel Cabrera Cabrera 2023 370 334 31 4 86 3 2 0.257 0.322 -0.790 -0.39 NA NA cabremi01 1744 2016 8 31000000 after NA NA 233000000 13.305
16690 Carlos Correa Correa 2015 432 387 40 22 108 4 1 0.279 0.345 3.400 4.76 3.61 4.93 correca01 14162 2022 6 33333333 before correca01 20 189000000 17.637
16691 Carlos Correa Correa 2016 660 577 75 20 158 3 5 0.274 0.361 5.200 7.01 5.54 7.00 correca01 14162 2022 6 33333333 before correca01 21 189000000 17.637
16692 Carlos Correa Correa 2017 481 422 53 24 133 4 2 0.315 0.391 5.100 6.68 5.30 6.98 correca01 14162 2022 6 33333333 before correca01 22 195000000 17.094
16693 Carlos Correa Correa 2018 468 402 53 15 96 11 2 0.239 0.323 1.600 3.05 2.13 3.66 correca01 14162 2022 6 33333333 before correca01 23 197000000 16.920
16694 Carlos Correa Correa 2019 321 280 35 21 78 4 2 0.279 0.358 3.100 3.68 3.61 3.89 correca01 14162 2022 6 33333333 before correca01 24 206000000 16.181
16695 Carlos Correa Correa 2020 221 201 16 5 53 1 3 0.264 0.326 0.800 1.66 3.21 4.50 correca01 14162 2022 6 33333333 before correca01 25 208000000 16.026
16696 Carlos Correa Correa 2021 640 555 75 26 155 6 4 0.279 0.366 5.800 7.24 6.19 8.83 correca01 14162 2022 6 33333333 before correca01 26 210000000 15.873
16697 Carlos Correa Correa 2022 590 522 61 22 152 4 3 0.291 0.366 4.400 5.31 4.98 5.86 correca01 14162 2022 6 33333333 after correca01 27 230000000 14.493
16698 Carlos Correa Correa 2023 580 514 59 18 118 3 4 0.230 0.312 1.139 1.40 1.56 1.92 correca01 14162 2022 6 33333333 after correca01 28 233000000 14.306
16699 Carlos Correa Correa 2024 367 319 40 14 99 4 3 0.310 0.388 4.276 3.65 3.97 3.83 correca01 14162 2022 6 33333333 after correca01 29 237000000 14.065
20229 Rafael Devers Devers 2017 240 222 18 10 63 0 0 0.284 0.338 0.800 0.93 1.36 1.57 deverra01 17350 2023 10 31400000 before deverra01 20 195000000 16.103
20230 Rafael Devers Devers 2018 490 450 38 21 108 2 0 0.240 0.298 1.000 0.23 1.85 1.20 deverra01 17350 2023 10 31400000 before deverra01 21 197000000 15.939
20231 Rafael Devers Devers 2019 702 647 48 32 201 2 4 0.311 0.361 5.900 5.37 5.85 5.93 deverra01 17350 2023 10 31400000 before deverra01 22 206000000 15.243
20232 Rafael Devers Devers 2020 248 232 13 11 61 0 3 0.263 0.310 0.500 0.69 2.72 3.07 deverra01 17350 2023 10 31400000 before deverra01 23 208000000 15.096
20233 Rafael Devers Devers 2021 664 591 62 38 165 4 7 0.279 0.352 4.700 3.67 4.95 3.99 deverra01 17350 2023 10 31400000 before deverra01 24 210000000 14.952
20234 Rafael Devers Devers 2022 614 555 50 27 164 3 6 0.295 0.358 4.900 4.45 5.19 4.89 deverra01 17350 2023 10 31400000 before deverra01 25 230000000 13.652
20235 Rafael Devers Devers 2023 656 580 62 33 157 3 11 0.271 0.351 3.130 3.49 3.57 3.98 deverra01 17350 2023 10 31400000 after deverra01 26 233000000 13.476
20236 Rafael Devers Devers 2024 601 525 67 28 143 6 3 0.272 0.354 4.128 3.66 4.82 4.36 deverra01 17350 2023 10 31400000 after deverra01 27 237000000 13.249
31959 Vladimir Guerrero Jr Guerrero Jr 2019 514 464 46 15 126 2 2 0.272 0.339 0.400 2.09 1.38 2.86 guerrvl02 19611 2026 14 35714286 before guerrvl02 20 206000000 17.337
31960 Vladimir Guerrero Jr Guerrero Jr 2020 243 221 20 9 58 0 2 0.262 0.329 0.200 0.57 2.58 3.07 guerrvl02 19611 2026 14 35714286 before guerrvl02 21 208000000 17.170
31961 Vladimir Guerrero Jr Guerrero Jr 2021 698 604 86 48 188 2 6 0.311 0.401 6.700 6.68 7.02 7.11 guerrvl02 19611 2026 14 35714286 before guerrvl02 22 210000000 17.007
31962 Vladimir Guerrero Jr Guerrero Jr 2022 706 638 58 32 175 4 6 0.274 0.339 2.800 4.01 3.43 4.38 guerrvl02 19611 2026 14 35714286 before guerrvl02 23 230000000 15.528
31963 Vladimir Guerrero Jr Guerrero Jr 2023 682 602 67 26 159 4 9 0.264 0.345 0.984 1.97 1.43 2.36 guerrvl02 19611 2026 14 35714286 before guerrvl02 24 233000000 15.328
31964 Vladimir Guerrero Jr Guerrero Jr 2024 697 616 72 30 199 4 5 0.323 0.396 5.459 6.18 5.69 6.53 guerrvl02 19611 2026 14 35714286 before guerrvl02 25 237000000 15.069
33724 Bryce Harper Harper 2012 597 533 56 22 144 3 2 0.270 0.340 4.400 5.18 4.86 5.51 harpebr03 11579 2019 13 25384615 before harpebr03 19 178000000 14.261
33725 Bryce Harper Harper 2013 497 424 61 20 116 4 5 0.274 0.368 4.100 3.73 4.53 4.16 harpebr03 11579 2019 13 25384615 before harpebr03 20 178000000 14.261
33726 Bryce Harper Harper 2014 395 352 38 13 96 1 1 0.273 0.344 1.600 1.02 2.19 1.88 harpebr03 11579 2019 13 25384615 before harpebr03 21 189000000 13.431
33727 Bryce Harper Harper 2015 654 521 124 42 172 4 5 0.330 0.460 9.300 9.74 8.90 9.57 harpebr03 11579 2019 13 25384615 before harpebr03 22 189000000 13.431
33728 Bryce Harper Harper 2016 627 506 108 24 123 10 3 0.243 0.373 2.900 1.53 3.50 2.51 harpebr03 11579 2019 13 25384615 before harpebr03 23 189000000 13.431
33729 Bryce Harper Harper 2017 492 420 68 29 134 3 1 0.319 0.413 4.800 4.80 4.92 5.06 harpebr03 11579 2019 13 25384615 before harpebr03 24 195000000 13.018
33730 Bryce Harper Harper 2018 695 550 130 34 137 9 6 0.249 0.393 3.500 1.79 4.34 2.75 harpebr03 11579 2019 13 25384615 before harpebr03 25 197000000 12.886
33731 Bryce Harper Harper 2019 682 573 99 35 149 4 6 0.260 0.372 4.500 4.43 4.94 4.53 harpebr03 11579 2019 13 25384615 after harpebr03 26 206000000 12.323
33732 Bryce Harper Harper 2020 244 190 49 13 51 2 2 0.268 0.420 1.600 1.95 4.34 5.17 harpebr03 11579 2019 13 25384615 after harpebr03 27 208000000 12.204
33733 Bryce Harper Harper 2021 599 488 100 35 151 4 5 0.309 0.429 6.600 5.86 7.76 6.37 harpebr03 11579 2019 13 25384615 after harpebr03 28 210000000 12.088
33734 Bryce Harper Harper 2022 426 370 46 18 106 7 3 0.286 0.364 2.400 2.54 3.18 3.26 harpebr03 11579 2019 13 25384615 after harpebr03 29 230000000 11.037
33735 Bryce Harper Harper 2023 546 457 80 21 134 4 5 0.293 0.401 3.304 3.69 3.82 4.27 harpebr03 11579 2019 13 25384615 after harpebr03 30 233000000 10.895
33736 Bryce Harper Harper 2024 631 550 76 30 157 2 2 0.285 0.373 5.187 4.80 5.83 5.61 harpebr03 11579 2019 13 25384615 after harpebr03 31 237000000 10.711
40042 Derek Jeter Jeter 1995 51 48 3 0 12 0 0 0.250 0.294 -0.400 -0.34 NA NA jeterde01 826 2001 10 18900000 before NA NA NA NA
40043 Derek Jeter Jeter 1996 654 582 48 10 183 9 9 0.314 0.370 2.200 3.29 1.85 2.84 jeterde01 826 2001 10 18900000 before jeterde01 22 NA NA
40044 Derek Jeter Jeter 1997 748 654 74 10 190 2 10 0.291 0.370 4.000 4.96 3.80 4.96 jeterde01 826 2001 10 18900000 before jeterde01 23 NA NA
40045 Derek Jeter Jeter 1998 694 626 57 19 203 3 5 0.324 0.384 6.200 7.53 5.01 7.39 jeterde01 826 2001 10 18900000 before jeterde01 24 NA NA
40046 Derek Jeter Jeter 1999 739 627 91 24 219 6 12 0.349 0.438 7.400 8.00 6.87 9.37 jeterde01 826 2001 10 18900000 before jeterde01 25 NA NA
40047 Derek Jeter Jeter 2000 679 593 68 15 201 3 12 0.339 0.416 3.700 4.57 3.50 4.24 jeterde01 826 2001 10 18900000 before jeterde01 26 NA NA
40048 Derek Jeter Jeter 2001 686 614 56 21 191 1 10 0.311 0.377 4.200 5.19 4.00 4.86 jeterde01 826 2001 10 18900000 after jeterde01 27 NA NA
40049 Derek Jeter Jeter 2002 730 644 73 18 191 3 7 0.297 0.373 5.200 3.67 5.09 3.70 jeterde01 826 2001 10 18900000 after jeterde01 28 NA NA
40050 Derek Jeter Jeter 2003 542 482 43 10 156 1 13 0.324 0.393 4.100 3.57 4.14 3.55 jeterde01 826 2001 10 18900000 after jeterde01 29 117000000 16.154
40051 Derek Jeter Jeter 2004 721 643 46 23 188 2 14 0.292 0.352 4.700 4.24 4.96 4.43 jeterde01 826 2001 10 18900000 after jeterde01 30 120500000 15.685
40052 Derek Jeter Jeter 2005 752 654 77 19 202 3 11 0.309 0.389 4.400 3.80 4.85 3.99 jeterde01 826 2001 10 18900000 after jeterde01 31 128000000 14.766
40053 Derek Jeter Jeter 2006 715 623 69 14 214 4 12 0.343 0.417 6.100 5.55 6.52 6.08 jeterde01 826 2001 10 18900000 after jeterde01 32 136500000 13.846
40054 Derek Jeter Jeter 2007 714 639 56 12 206 2 14 0.322 0.388 3.600 3.94 4.35 4.30 jeterde01 826 2001 10 18900000 after jeterde01 33 148000000 12.770
40055 Derek Jeter Jeter 2008 668 596 52 11 179 4 9 0.300 0.363 3.400 2.98 3.87 3.45 jeterde01 826 2001 10 18900000 after jeterde01 34 155000000 12.194
40056 Derek Jeter Jeter 2009 716 634 72 18 212 1 5 0.334 0.406 6.700 6.55 6.68 6.42 jeterde01 826 2001 10 18900000 after jeterde01 35 162000000 11.667
40057 Derek Jeter Jeter 2010 739 663 63 10 179 3 9 0.270 0.340 2.300 1.74 2.99 2.78 jeterde01 826 2001 10 18900000 after jeterde01 36 170000000 11.118
41552 Aaron Judge Judge 2016 95 84 9 4 15 1 1 0.179 0.263 -0.200 -0.29 0.38 0.38 judgeaa01 15640 2023 9 40000000 before judgeaa01 24 189000000 21.164
41553 Aaron Judge Judge 2017 678 542 127 52 154 4 5 0.284 0.422 8.300 7.99 8.51 8.13 judgeaa01 15640 2023 9 40000000 before judgeaa01 25 195000000 20.513
41554 Aaron Judge Judge 2018 498 413 76 27 115 5 4 0.278 0.392 5.100 5.87 4.93 5.90 judgeaa01 15640 2023 9 40000000 before judgeaa01 26 197000000 20.305
41555 Aaron Judge Judge 2019 447 378 64 27 103 1 3 0.272 0.381 4.600 5.61 4.61 5.51 judgeaa01 15640 2023 9 40000000 before judgeaa01 27 206000000 19.417
41556 Aaron Judge Judge 2020 114 101 10 9 26 0 2 0.257 0.336 1.000 1.14 1.57 1.77 judgeaa01 15640 2023 9 40000000 before judgeaa01 28 208000000 19.231
41557 Aaron Judge Judge 2021 633 550 75 39 158 5 3 0.287 0.373 5.500 6.07 5.92 6.51 judgeaa01 15640 2023 9 40000000 before judgeaa01 29 210000000 19.048
41558 Aaron Judge Judge 2022 696 570 111 62 177 5 6 0.311 0.425 11.400 10.53 9.63 10.33 judgeaa01 15640 2023 9 40000000 before judgeaa01 30 230000000 17.391
41559 Aaron Judge Judge 2023 458 367 88 37 98 3 0 0.267 0.406 5.326 4.46 5.73 5.41 judgeaa01 15640 2023 9 40000000 after judgeaa01 31 233000000 17.167
41560 Aaron Judge Judge 2024 704 559 133 58 180 2 9 0.322 0.458 11.211 10.83 9.35 10.03 judgeaa01 15640 2023 9 40000000 after judgeaa01 32 237000000 16.878
47214 Francisco Lindor Lindor 2015 438 390 27 12 122 7 1 0.313 0.353 4.000 3.99 4.14 4.04 lindofr01 12916 2021 10 34100000 before lindofr01 21 189000000 18.042
47215 Francisco Lindor Lindor 2016 684 604 57 15 182 15 5 0.301 0.358 5.500 5.10 6.06 5.75 lindofr01 12916 2021 10 34100000 before lindofr01 22 189000000 18.042
47216 Francisco Lindor Lindor 2017 723 651 60 33 178 3 4 0.273 0.337 5.700 5.71 5.97 6.15 lindofr01 12916 2021 10 34100000 before lindofr01 23 195000000 17.487
47217 Francisco Lindor Lindor 2018 745 661 70 38 183 3 8 0.277 0.352 7.700 7.16 7.39 7.18 lindofr01 12916 2021 10 34100000 before lindofr01 24 197000000 17.310
47218 Francisco Lindor Lindor 2019 654 598 46 32 170 6 3 0.284 0.335 4.700 4.83 5.09 5.32 lindofr01 12916 2021 10 34100000 before lindofr01 25 206000000 16.553
47219 Francisco Lindor Lindor 2020 266 236 24 8 61 2 4 0.258 0.335 1.800 1.31 4.98 4.11 lindofr01 12916 2021 10 34100000 before lindofr01 26 208000000 16.394
47220 Francisco Lindor Lindor 2021 524 452 58 20 104 3 5 0.230 0.322 2.700 3.04 3.24 3.42 lindofr01 12916 2021 10 34100000 after lindofr01 27 210000000 16.238
47221 Francisco Lindor Lindor 2022 706 630 59 26 170 7 10 0.270 0.339 6.800 5.56 6.60 6.10 lindofr01 12916 2021 10 34100000 after lindofr01 28 230000000 14.826
47222 Francisco Lindor Lindor 2023 687 602 66 31 153 7 12 0.254 0.336 6.022 6.01 6.35 6.43 lindofr01 12916 2021 10 34100000 after lindofr01 29 233000000 14.635
47223 Francisco Lindor Lindor 2024 689 618 56 33 169 3 12 0.273 0.344 7.767 6.88 7.06 6.84 lindofr01 12916 2021 10 34100000 after lindofr01 30 237000000 14.388
49044 Manny Machado Machado 2012 202 191 9 7 50 1 0 0.262 0.294 1.300 1.60 1.92 2.27 machama01 11493 2019 11 31818182 before machama01 19 178000000 17.875
49045 Manny Machado Machado 2013 710 667 29 14 189 3 2 0.283 0.314 5.000 5.86 5.33 6.08 machama01 11493 2019 11 31818182 before machama01 20 178000000 17.875
49046 Manny Machado Machado 2014 354 327 20 12 91 2 3 0.278 0.324 2.300 2.19 2.58 2.46 machama01 11493 2019 11 31818182 before machama01 21 189000000 16.835
49047 Manny Machado Machado 2015 713 633 70 35 181 4 4 0.286 0.359 6.600 7.49 6.81 7.61 machama01 11493 2019 11 31818182 before machama01 22 189000000 16.835
49048 Manny Machado Machado 2016 696 640 48 37 188 5 3 0.294 0.343 6.300 7.34 6.63 7.62 machama01 11493 2019 11 31818182 before machama01 23 189000000 16.835
49049 Manny Machado Machado 2017 690 630 50 33 163 9 1 0.259 0.310 2.400 3.82 3.01 4.34 machama01 11493 2019 11 31818182 before machama01 24 195000000 16.317
49050 Manny Machado Machado 2018 709 632 70 37 188 5 2 0.297 0.367 6.300 6.13 6.61 6.52 machama01 11493 2019 11 31818182 before machama01 25 197000000 16.151
49051 Manny Machado Machado 2019 661 587 65 32 150 3 6 0.256 0.334 3.200 2.56 3.76 3.34 machama01 11493 2019 11 31818182 after machama01 26 206000000 15.446
49052 Manny Machado Machado 2020 254 224 26 16 68 4 0 0.304 0.370 2.600 3.15 6.63 8.27 machama01 11493 2019 11 31818182 after machama01 27 208000000 15.297
49053 Manny Machado Machado 2021 640 564 63 28 157 11 2 0.278 0.347 4.400 5.04 4.77 5.62 machama01 11493 2019 11 31818182 after machama01 28 210000000 15.152
49054 Manny Machado Machado 2022 644 578 63 32 172 2 1 0.298 0.366 7.400 6.69 7.67 6.61 machama01 11493 2019 11 31818182 after machama01 29 230000000 13.834
49055 Manny Machado Machado 2023 601 543 50 30 140 6 2 0.258 0.319 3.476 2.88 3.90 3.40 machama01 11493 2019 11 31818182 after machama01 30 233000000 13.656
49056 Manny Machado Machado 2024 643 593 45 29 163 4 1 0.275 0.325 3.557 3.07 4.22 3.71 machama01 11493 2019 11 31818182 after machama01 31 237000000 13.425
51399 Joe Mauer Mauer 2004 122 107 11 6 33 3 1 0.308 0.369 1.200 1.40 1.73 2.04 mauerjo01 1857 2011 8 23000000 before mauerjo01 21 120500000 19.087
51400 Joe Mauer Mauer 2005 554 489 61 9 144 3 1 0.294 0.372 3.400 2.82 3.79 3.05 mauerjo01 1857 2011 8 23000000 before mauerjo01 22 128000000 17.969
51401 Joe Mauer Mauer 2006 608 521 79 13 181 7 1 0.347 0.429 5.800 5.80 6.27 6.85 mauerjo01 1857 2011 8 23000000 before mauerjo01 23 136500000 16.850
51402 Joe Mauer Mauer 2007 471 406 57 7 119 3 3 0.293 0.382 3.300 3.87 3.53 4.22 mauerjo01 1857 2011 8 23000000 before mauerjo01 24 148000000 15.541
51403 Joe Mauer Mauer 2008 633 536 84 9 176 11 1 0.328 0.413 6.400 5.58 6.04 5.67 mauerjo01 1857 2011 8 23000000 before mauerjo01 25 155000000 14.839
51404 Joe Mauer Mauer 2009 606 523 76 28 191 5 2 0.365 0.444 8.400 7.83 8.23 7.88 mauerjo01 1857 2011 8 23000000 before mauerjo01 26 162000000 14.198
51405 Joe Mauer Mauer 2010 584 510 65 9 167 6 3 0.327 0.402 5.700 5.86 5.64 5.69 mauerjo01 1857 2011 8 23000000 before mauerjo01 27 170000000 13.529
51406 Joe Mauer Mauer 2011 333 296 32 3 85 2 3 0.287 0.360 2.100 1.49 2.59 2.19 mauerjo01 1857 2011 8 23000000 after mauerjo01 28 178000000 12.921
51407 Joe Mauer Mauer 2012 641 545 90 10 174 3 2 0.319 0.416 4.600 4.42 5.06 5.00 mauerjo01 1857 2011 8 23000000 after mauerjo01 29 178000000 12.921
51408 Joe Mauer Mauer 2013 508 445 61 11 144 2 0 0.324 0.404 5.200 5.53 5.06 5.94 mauerjo01 1857 2011 8 23000000 after mauerjo01 30 178000000 12.921
51409 Joe Mauer Mauer 2014 518 455 60 4 126 2 1 0.277 0.361 1.700 1.69 2.35 2.48 mauerjo01 1857 2011 8 23000000 after mauerjo01 31 189000000 12.169
51410 Joe Mauer Mauer 2015 666 592 67 10 157 5 1 0.265 0.338 0.300 1.34 1.82 2.60 mauerjo01 1857 2011 8 23000000 after mauerjo01 32 189000000 12.169
51411 Joe Mauer Mauer 2016 576 494 79 11 129 2 1 0.261 0.363 1.000 2.24 1.89 3.02 mauerjo01 1857 2011 8 23000000 after mauerjo01 33 189000000 12.169
51412 Joe Mauer Mauer 2017 597 525 66 7 160 3 3 0.305 0.384 2.300 3.93 2.96 4.23 mauerjo01 1857 2011 8 23000000 after mauerjo01 34 195000000 11.795
51413 Joe Mauer Mauer 2018 543 486 51 6 137 3 2 0.282 0.351 1.100 1.40 2.04 2.15 mauerjo01 1857 2011 8 23000000 after mauerjo01 35 197000000 11.675
60336 Shohei Ohtani Ohtani 2018 367 326 37 22 93 1 2 0.285 0.361 2.700 2.73 3.25 3.25 ohtansh01 19755 2024 10 70000000 before ohtansh01 23 197000000 35.533
60337 Shohei Ohtani Ohtani 2019 425 384 33 18 110 4 2 0.286 0.343 1.700 2.45 2.45 2.94 ohtansh01 19755 2024 10 70000000 before ohtansh01 24 206000000 33.981
60338 Shohei Ohtani Ohtani 2020 175 153 22 7 29 0 0 0.190 0.291 0.000 0.04 1.75 1.81 ohtansh01 19755 2024 10 70000000 before ohtansh01 25 208000000 33.654
60339 Shohei Ohtani Ohtani 2021 639 537 96 46 138 2 4 0.257 0.372 5.100 4.86 5.38 5.29 ohtansh01 19755 2024 10 70000000 before ohtansh01 26 210000000 33.333
60340 Shohei Ohtani Ohtani 2022 666 586 72 34 160 3 5 0.273 0.356 3.800 3.36 4.30 3.73 ohtansh01 19755 2024 10 70000000 before ohtansh01 27 230000000 30.435
60341 Shohei Ohtani Ohtani 2023 599 497 91 44 151 3 3 0.304 0.412 6.625 6.04 6.63 6.82 ohtansh01 19755 2024 10 70000000 before ohtansh01 28 233000000 30.043
60342 Shohei Ohtani Ohtani 2024 731 636 81 54 197 5 6 0.310 0.390 9.074 9.22 8.10 8.63 ohtansh01 19755 2024 10 70000000 after ohtansh01 29 237000000 29.536
60641 Matt Olson Olson 2016 28 21 7 0 2 0 0 0.095 0.321 -0.100 -0.15 0.24 0.24 olsonma02 14344 2022 8 21000000 before olsonma02 22 189000000 11.111
60642 Matt Olson Olson 2017 216 189 22 24 49 0 5 0.259 0.352 2.100 2.92 2.68 3.43 olsonma02 14344 2022 8 21000000 before olsonma02 23 195000000 10.769
60643 Matt Olson Olson 2018 660 580 70 29 143 2 8 0.247 0.335 3.500 3.72 4.28 4.34 olsonma02 14344 2022 8 21000000 before olsonma02 24 197000000 10.660
60644 Matt Olson Olson 2019 547 483 51 36 129 1 12 0.267 0.351 3.900 4.89 4.30 5.07 olsonma02 14344 2022 8 21000000 before olsonma02 25 206000000 10.194
60645 Matt Olson Olson 2020 245 210 34 14 41 0 1 0.195 0.310 0.800 1.09 3.25 3.70 olsonma02 14344 2022 8 21000000 before olsonma02 26 208000000 10.096
60646 Matt Olson Olson 2021 673 565 88 39 153 11 9 0.271 0.371 5.000 5.82 5.29 6.24 olsonma02 14344 2022 8 21000000 before olsonma02 27 210000000 10.000
60647 Matt Olson Olson 2022 699 616 75 34 148 4 4 0.240 0.325 3.100 3.30 3.68 3.66 olsonma02 14344 2022 8 21000000 after olsonma02 28 230000000 9.130
60648 Matt Olson Olson 2023 720 608 104 54 172 4 4 0.283 0.389 6.703 7.37 7.04 8.05 olsonma02 14344 2022 8 21000000 after olsonma02 29 233000000 9.013
60649 Matt Olson Olson 2024 685 600 71 29 148 5 9 0.247 0.333 2.559 3.84 3.29 4.49 olsonma02 14344 2022 8 21000000 after olsonma02 30 237000000 8.861
65074 Buster Posey Posey 2009 17 17 0 0 2 0 0 0.118 0.118 -0.200 -0.10 0.14 0.19 poseybu01 9166 2013 9 18333333 before poseybu01 22 162000000 11.317
65075 Buster Posey Posey 2010 443 406 30 18 124 3 4 0.305 0.357 4.000 3.87 4.01 4.22 poseybu01 9166 2013 9 18333333 before poseybu01 23 170000000 10.784
65076 Buster Posey Posey 2011 185 162 18 4 46 1 4 0.284 0.368 1.800 1.31 2.10 1.85 poseybu01 9166 2013 9 18333333 before poseybu01 24 178000000 10.300
65077 Buster Posey Posey 2012 610 530 69 24 178 9 2 0.336 0.408 10.100 7.56 8.30 7.50 poseybu01 9166 2013 9 18333333 before poseybu01 25 178000000 10.300
65078 Buster Posey Posey 2013 595 520 60 15 153 7 8 0.294 0.371 6.900 5.33 6.74 5.67 poseybu01 9166 2013 9 18333333 after poseybu01 26 178000000 10.300
65079 Buster Posey Posey 2014 605 547 47 22 170 8 3 0.311 0.364 7.600 5.07 7.00 5.35 poseybu01 9166 2013 9 18333333 after poseybu01 27 189000000 9.700
65080 Buster Posey Posey 2015 623 557 56 19 177 7 3 0.318 0.379 6.800 5.94 6.90 5.96 poseybu01 9166 2013 9 18333333 after poseybu01 28 189000000 9.700
65081 Buster Posey Posey 2016 614 539 64 14 155 8 3 0.288 0.362 6.700 4.86 6.70 5.43 poseybu01 9166 2013 9 18333333 after poseybu01 29 189000000 9.700
65082 Buster Posey Posey 2017 568 494 61 12 158 5 8 0.320 0.400 4.700 3.98 4.96 4.35 poseybu01 9166 2013 9 18333333 after poseybu01 30 195000000 9.402
65083 Buster Posey Posey 2018 448 398 45 5 113 2 3 0.284 0.359 2.200 2.78 2.76 3.34 poseybu01 9166 2013 9 18333333 after poseybu01 31 197000000 9.306
65084 Buster Posey Posey 2019 445 405 34 7 104 1 4 0.257 0.320 1.800 0.78 2.55 1.63 poseybu01 9166 2013 9 18333333 after poseybu01 32 206000000 8.900
65085 Buster Posey Posey 2021 454 395 56 18 120 2 1 0.304 0.390 4.900 3.46 5.61 4.10 poseybu01 9166 2013 9 18333333 after poseybu01 34 210000000 8.730
65610 Albert Pujols Pujols 2001 676 590 69 37 194 7 9 0.329 0.403 7.200 6.59 6.52 6.11 pujolal01 1177 2012 10 24000000 before pujolal01 21 NA NA
65611 Albert Pujols Pujols 2002 675 590 72 34 185 4 9 0.314 0.394 5.400 5.53 5.38 5.66 pujolal01 1177 2012 10 24000000 before pujolal01 22 NA NA
65612 Albert Pujols Pujols 2003 685 591 79 43 212 5 10 0.359 0.439 9.500 8.65 8.17 8.47 pujolal01 1177 2012 10 24000000 before pujolal01 23 117000000 20.513
65613 Albert Pujols Pujols 2004 692 592 84 46 196 9 7 0.331 0.415 7.800 8.50 6.98 7.35 pujolal01 1177 2012 10 24000000 before pujolal01 24 120500000 19.917
65614 Albert Pujols Pujols 2005 700 591 97 41 195 3 9 0.330 0.430 7.700 8.39 7.56 8.95 pujolal01 1177 2012 10 24000000 before pujolal01 25 128000000 18.750
65615 Albert Pujols Pujols 2006 634 535 92 49 177 3 4 0.331 0.431 8.100 8.47 8.15 8.71 pujolal01 1177 2012 10 24000000 before pujolal01 26 136500000 17.582
65616 Albert Pujols Pujols 2007 679 565 99 32 185 8 7 0.327 0.429 7.700 8.74 6.90 8.07 pujolal01 1177 2012 10 24000000 before pujolal01 27 148000000 16.216
65617 Albert Pujols Pujols 2008 641 524 104 37 187 8 5 0.357 0.462 8.700 9.24 8.42 9.33 pujolal01 1177 2012 10 24000000 before pujolal01 28 155000000 15.484
65618 Albert Pujols Pujols 2009 700 568 115 47 186 8 9 0.327 0.443 8.400 9.73 8.01 9.93 pujolal01 1177 2012 10 24000000 before pujolal01 29 162000000 14.815
65619 Albert Pujols Pujols 2010 700 587 103 42 183 6 4 0.312 0.414 6.800 7.53 6.64 7.20 pujolal01 1177 2012 10 24000000 before pujolal01 30 170000000 14.118
65620 Albert Pujols Pujols 2011 651 579 61 37 173 7 4 0.299 0.366 3.900 5.27 4.23 5.66 pujolal01 1177 2012 10 24000000 before pujolal01 31 178000000 13.483
65621 Albert Pujols Pujols 2012 670 607 52 30 173 6 5 0.285 0.343 3.300 4.81 3.91 5.43 pujolal01 1177 2012 10 24000000 after pujolal01 32 178000000 13.483
65622 Albert Pujols Pujols 2013 443 391 40 17 101 7 5 0.258 0.330 0.500 1.61 1.40 2.25 pujolal01 1177 2012 10 24000000 after pujolal01 33 178000000 13.483
65623 Albert Pujols Pujols 2014 695 633 48 28 172 9 5 0.272 0.324 2.700 3.87 3.41 4.20 pujolal01 1177 2012 10 24000000 after pujolal01 34 189000000 12.698
65624 Albert Pujols Pujols 2015 661 602 50 40 147 3 6 0.244 0.307 1.600 2.98 2.57 3.79 pujolal01 1177 2012 10 24000000 after pujolal01 35 189000000 12.698
65625 Albert Pujols Pujols 2016 650 593 49 31 159 6 2 0.268 0.323 0.800 1.49 1.89 2.49 pujolal01 1177 2012 10 24000000 after pujolal01 36 189000000 12.698
65626 Albert Pujols Pujols 2017 636 593 37 23 143 4 2 0.241 0.286 -2.000 -1.92 1.04 1.19 pujolal01 1177 2012 10 24000000 after pujolal01 37 195000000 12.308
65627 Albert Pujols Pujols 2018 498 465 28 19 114 3 2 0.245 0.289 -0.300 0.27 1.02 1.19 pujolal01 1177 2012 10 24000000 after pujolal01 38 197000000 12.183
65628 Albert Pujols Pujols 2019 545 491 43 23 120 8 3 0.244 0.305 -0.600 0.33 0.95 1.50 pujolal01 1177 2012 10 24000000 after pujolal01 39 206000000 11.650
65629 Albert Pujols Pujols 2020 163 152 9 6 34 1 1 0.224 0.270 -0.200 0.01 1.13 1.32 pujolal01 1177 2012 10 24000000 after pujolal01 40 208000000 11.538
65630 Albert Pujols Pujols 2021 296 275 14 17 65 2 5 0.236 0.284 -0.200 -0.70 0.71 0.46 pujolal01 1177 2012 10 24000000 after pujolal01 41 210000000 11.429
67358 Anthony Rendon Rendon 2013 394 351 31 7 93 5 5 0.265 0.329 1.000 0.37 1.72 1.39 rendoan01 12861 2020 7 35000000 before rendoan01 23 178000000 19.663
67359 Anthony Rendon Rendon 2014 683 613 58 21 176 5 5 0.287 0.351 6.400 6.51 6.60 6.67 rendoan01 12861 2020 7 35000000 before rendoan01 24 189000000 18.519
67360 Anthony Rendon Rendon 2015 355 311 36 5 82 4 4 0.264 0.344 1.100 0.47 1.84 1.39 rendoan01 12861 2020 7 35000000 before rendoan01 25 189000000 18.519
67361 Anthony Rendon Rendon 2016 647 567 65 20 153 8 7 0.270 0.348 4.300 4.47 4.73 5.01 rendoan01 12861 2020 7 35000000 before rendoan01 26 189000000 18.519
67362 Anthony Rendon Rendon 2017 605 508 84 25 153 6 7 0.301 0.403 6.700 6.06 6.73 6.13 rendoan01 12861 2020 7 35000000 before rendoan01 27 195000000 17.949
67363 Anthony Rendon Rendon 2018 597 529 55 24 163 8 5 0.308 0.374 6.300 5.06 6.05 5.41 rendoan01 12861 2020 7 35000000 before rendoan01 28 197000000 17.766
67364 Anthony Rendon Rendon 2019 646 545 80 34 174 9 12 0.319 0.412 7.000 7.08 6.75 6.72 rendoan01 12861 2020 7 35000000 before rendoan01 29 206000000 16.990
67365 Anthony Rendon Rendon 2020 232 189 38 9 54 0 5 0.286 0.418 2.600 2.16 5.99 5.14 rendoan01 12861 2020 7 35000000 after rendoan01 30 208000000 16.827
67366 Anthony Rendon Rendon 2021 249 217 29 6 52 2 1 0.240 0.329 0.700 -0.02 1.26 0.67 rendoan01 12861 2020 7 35000000 after rendoan01 31 210000000 16.667
67367 Anthony Rendon Rendon 2022 193 166 23 5 38 2 2 0.229 0.326 0.800 0.89 1.20 1.33 rendoan01 12861 2020 7 35000000 after rendoan01 32 230000000 15.217
67368 Anthony Rendon Rendon 2023 183 148 25 2 35 4 6 0.236 0.361 0.166 0.08 0.40 0.22 rendoan01 12861 2020 7 35000000 after rendoan01 33 233000000 15.021
67369 Anthony Rendon Rendon 2024 238 206 23 0 45 4 5 0.218 0.307 -0.078 0.58 0.44 0.80 rendoan01 12861 2020 7 35000000 after rendoan01 34 237000000 14.768
69289 Alex Rodriguez Rodriguez 1994 59 54 3 0 11 1 0 0.204 0.241 -0.300 -0.25 NA NA rodrial01 1274 2001 7 25200000 before NA NA NA NA
69290 Alex Rodriguez Rodriguez 1995 149 142 6 5 33 0 0 0.232 0.264 -0.300 -0.37 NA NA rodrial01 1274 2001 7 25200000 before NA NA NA NA
69291 Alex Rodriguez Rodriguez 1996 677 601 59 36 215 7 4 0.358 0.414 9.200 9.41 7.53 7.81 rodrial01 1274 2001 7 25200000 before rodrial01 20 NA NA
69292 Alex Rodriguez Rodriguez 1997 638 587 41 23 176 1 5 0.300 0.350 4.300 5.65 4.03 5.38 rodrial01 1274 2001 7 25200000 before rodrial01 21 NA NA
69293 Alex Rodriguez Rodriguez 1998 748 686 45 42 213 4 10 0.310 0.360 7.900 8.51 7.18 9.46 rodrial01 1274 2001 7 25200000 before rodrial01 22 NA NA
69294 Alex Rodriguez Rodriguez 1999 572 502 56 42 143 8 5 0.285 0.357 4.700 4.75 4.37 4.37 rodrial01 1274 2001 7 25200000 before rodrial01 23 NA NA
69295 Alex Rodriguez Rodriguez 2000 672 554 100 41 175 11 7 0.316 0.420 9.500 10.36 8.63 9.45 rodrial01 1274 2001 7 25200000 before rodrial01 24 NA NA
69296 Alex Rodriguez Rodriguez 2001 732 632 75 52 201 9 16 0.318 0.399 7.800 8.34 6.78 7.42 rodrial01 1274 2001 7 25200000 after rodrial01 25 NA NA
69297 Alex Rodriguez Rodriguez 2002 725 624 87 57 187 4 10 0.300 0.392 10.000 8.82 8.54 8.77 rodrial01 1274 2001 7 25200000 after rodrial01 26 NA NA
69298 Alex Rodriguez Rodriguez 2003 715 607 87 47 181 6 15 0.298 0.396 9.200 8.38 8.08 7.98 rodrial01 1274 2001 7 25200000 after rodrial01 27 117000000 21.538
69299 Alex Rodriguez Rodriguez 2004 698 601 80 36 172 7 10 0.286 0.375 6.600 7.59 6.40 6.95 rodrial01 1274 2001 7 25200000 after rodrial01 28 120500000 20.913
69300 Alex Rodriguez Rodriguez 2005 715 605 91 48 194 3 16 0.321 0.421 9.100 9.36 9.48 10.19 rodrial01 1274 2001 7 25200000 after rodrial01 29 128000000 19.688
69301 Alex Rodriguez Rodriguez 2006 674 572 90 35 166 4 8 0.290 0.392 3.800 4.47 4.23 4.96 rodrial01 1274 2001 7 25200000 after rodrial01 30 136500000 18.462
69302 Alex Rodriguez Rodriguez 2007 708 583 95 54 183 9 21 0.314 0.422 9.600 9.44 9.12 9.65 rodrial01 1274 2001 7 25200000 after rodrial01 31 148000000 17.027
69303 A-Rod Rodriguez 2008 594 510 65 35 154 5 14 0.302 0.392 5.800 6.76 5.44 6.94 rodrial01 1274 2008 10 27500000 after rodrial01 32 155000000 17.742
69304 A-Rod Rodriguez 2009 535 444 80 30 127 3 8 0.286 0.402 4.100 4.15 4.27 4.42 rodrial01 1274 2008 10 27500000 after rodrial01 33 162000000 16.975
69305 A-Rod Rodriguez 2010 595 522 59 30 141 11 3 0.270 0.341 4.000 4.15 4.27 4.53 rodrial01 1274 2008 10 27500000 after rodrial01 34 170000000 16.176
69306 A-Rod Rodriguez 2011 428 373 47 16 103 3 5 0.276 0.362 4.000 4.02 4.03 4.48 rodrial01 1274 2008 10 27500000 after rodrial01 35 178000000 15.449
69307 A-Rod Rodriguez 2012 529 463 51 18 126 5 10 0.272 0.353 2.500 2.23 3.07 2.87 rodrial01 1274 2008 10 27500000 after rodrial01 36 178000000 15.449
69308 A-Rod Rodriguez 2013 181 156 23 7 38 0 2 0.244 0.348 0.600 0.01 1.12 0.67 rodrial01 1274 2008 10 27500000 after rodrial01 37 178000000 15.449
69309 A-Rod Rodriguez 2015 620 523 84 33 131 7 6 0.250 0.356 2.700 2.95 3.40 3.78 rodrial01 1274 2008 10 27500000 after rodrial01 39 189000000 14.550
69310 A-Rod Rodriguez 2016 243 225 14 9 45 3 1 0.200 0.247 -1.100 -1.18 0.55 0.56 rodrial01 1274 2008 10 27500000 after rodrial01 40 189000000 14.550
73366 Corey Seager Seager 2015 113 98 14 4 33 0 1 0.337 0.425 1.500 1.58 2.25 2.35 seageco01 13624 2022 10 32500000 before seageco01 21 189000000 17.196
73367 Corey Seager Seager 2016 687 627 54 26 193 2 4 0.308 0.365 6.900 5.19 7.03 5.88 seageco01 13624 2022 10 32500000 before seageco01 22 189000000 17.196
73368 Corey Seager Seager 2017 613 539 67 22 159 3 4 0.295 0.375 6.000 5.31 5.96 5.61 seageco01 13624 2022 10 32500000 before seageco01 23 195000000 16.667
73369 Corey Seager Seager 2018 115 101 11 2 27 1 2 0.267 0.348 0.500 0.52 0.92 0.95 seageco01 13624 2022 10 32500000 before seageco01 24 197000000 16.497
73370 Corey Seager Seager 2019 541 489 44 19 133 4 4 0.272 0.335 3.300 2.93 3.81 3.53 seageco01 13624 2022 10 32500000 before seageco01 25 206000000 15.777
73371 Corey Seager Seager 2020 232 212 17 15 65 2 1 0.307 0.358 1.800 2.08 4.41 4.95 seageco01 13624 2022 10 32500000 before seageco01 26 208000000 15.625
73372 Corey Seager Seager 2021 409 353 48 16 108 3 5 0.306 0.394 3.700 3.56 4.14 4.02 seageco01 13624 2022 10 32500000 before seageco01 27 210000000 15.476
73373 Corey Seager Seager 2022 663 593 58 33 145 5 7 0.245 0.317 4.500 3.77 4.99 4.17 seageco01 13624 2022 10 32500000 after seageco01 28 230000000 14.130
73374 Corey Seager Seager 2023 536 477 49 33 156 6 4 0.327 0.390 6.096 6.94 6.73 8.11 seageco01 13624 2022 10 32500000 after seageco01 29 233000000 13.948
73375 Corey Seager Seager 2024 533 475 53 30 132 2 3 0.278 0.353 4.544 4.96 5.09 5.31 seageco01 13624 2022 10 32500000 after seageco01 30 237000000 13.713
73631 Marcus Semien Semien 2013 71 69 1 2 18 1 0 0.261 0.268 0.200 0.55 0.59 0.94 semiema01 12533 2022 7 25000000 before semiema01 22 178000000 14.045
73632 Marcus Semien Semien 2014 255 231 21 6 54 0 1 0.234 0.300 0.500 0.75 1.21 1.42 semiema01 12533 2022 7 25000000 before semiema01 23 189000000 13.228
73633 Marcus Semien Semien 2015 601 556 42 15 143 1 1 0.257 0.310 1.400 1.73 2.42 2.76 semiema01 12533 2022 7 25000000 before semiema01 24 189000000 13.228
73634 Marcus Semien Semien 2016 621 568 51 27 135 1 0 0.238 0.300 2.100 3.52 3.04 4.29 semiema01 12533 2022 7 25000000 before semiema01 25 189000000 13.228
73635 Marcus Semien Semien 2017 386 342 38 10 85 3 2 0.249 0.325 1.700 1.84 2.11 2.25 semiema01 12533 2022 7 25000000 before semiema01 26 195000000 12.821
73636 Marcus Semien Semien 2018 703 632 61 15 161 7 1 0.255 0.318 3.900 4.42 4.63 5.34 semiema01 12533 2022 7 25000000 before semiema01 27 197000000 12.690
73637 Marcus Semien Semien 2019 747 657 87 33 187 1 2 0.285 0.369 7.600 8.49 7.16 7.95 semiema01 12533 2022 7 25000000 before semiema01 28 206000000 12.136
73638 Marcus Semien Semien 2020 236 211 25 7 47 0 0 0.223 0.305 1.200 0.37 3.46 2.42 semiema01 12533 2022 7 25000000 before semiema01 29 208000000 12.019
73639 Marcus Semien Semien 2021 724 652 66 45 173 3 3 0.265 0.334 6.600 7.10 6.84 7.77 semiema01 12533 2022 7 25000000 before semiema01 30 210000000 11.905
73640 Marcus Semien Semien 2022 724 657 53 26 163 10 4 0.248 0.304 4.200 5.54 4.70 6.07 semiema01 12533 2022 7 25000000 after semiema01 31 230000000 10.870
73641 Marcus Semien Semien 2023 753 670 72 29 185 5 5 0.276 0.348 6.306 7.37 6.71 8.00 semiema01 12533 2022 7 25000000 after semiema01 32 233000000 10.730
73642 Marcus Semien Semien 2024 718 650 64 23 154 1 3 0.237 0.308 4.164 4.12 4.92 4.81 semiema01 12533 2022 7 25000000 after semiema01 33 237000000 10.549
76657 Juan Soto Soto 2018 494 414 79 22 121 0 0 0.292 0.406 3.700 3.03 4.03 3.61 sotoju01 20123 2025 15 51000000 before sotoju01 19 197000000 25.888
76658 Juan Soto Soto 2019 659 542 108 34 153 6 3 0.282 0.401 4.900 5.04 5.25 5.41 sotoju01 20123 2025 15 51000000 before sotoju01 20 206000000 24.757
76659 Juan Soto Soto 2020 196 154 41 13 54 0 1 0.351 0.490 2.500 2.37 5.68 5.53 sotoju01 20123 2025 15 51000000 before sotoju01 21 208000000 24.519
76660 Juan Soto Soto 2021 654 502 145 29 157 5 2 0.313 0.465 6.600 7.13 7.08 8.33 sotoju01 20123 2025 15 51000000 before sotoju01 22 210000000 24.286
76661 Juan Soto Soto 2022 664 524 135 27 127 0 4 0.242 0.401 3.800 5.49 4.37 5.98 sotoju01 20123 2025 15 51000000 before sotoju01 23 230000000 22.174
76662 Juan Soto Soto 2023 708 568 132 35 156 5 2 0.275 0.410 5.534 5.46 5.79 5.75 sotoju01 20123 2025 15 51000000 before sotoju01 24 233000000 21.888
76663 Juan Soto Soto 2024 713 576 129 41 166 4 4 0.288 0.419 8.140 7.92 7.43 7.52 sotoju01 20123 2025 15 51000000 before sotoju01 25 237000000 21.519
77499 Giancarlo Stanton Stanton 2010 396 359 34 22 93 1 2 0.259 0.326 2.600 2.81 2.96 3.31 stantmi03 4949 2015 13 25000000 before stantmi03 20 170000000 14.706
77500 Giancarlo Stanton Stanton 2011 601 516 70 34 135 6 9 0.262 0.356 4.200 4.12 4.48 4.67 stantmi03 4949 2015 13 25000000 before stantmi03 21 178000000 14.045
77501 Giancarlo Stanton Stanton 2012 501 449 46 37 130 1 5 0.290 0.361 5.000 5.35 5.26 5.67 stantmi03 4949 2015 13 25000000 before stantmi03 22 178000000 14.045
77502 Giancarlo Stanton Stanton 2013 504 425 74 24 106 1 4 0.249 0.365 2.900 2.76 3.47 3.25 stantmi03 4949 2015 13 25000000 before stantmi03 23 178000000 14.045
77503 Giancarlo Stanton Stanton 2014 638 539 94 37 155 2 3 0.288 0.395 6.800 6.52 6.63 7.31 stantmi03 4949 2015 13 25000000 before stantmi03 24 189000000 13.228
77504 Giancarlo Stanton Stanton 2015 318 279 34 27 74 3 2 0.265 0.346 3.500 3.70 4.34 4.56 stantmi03 4949 2015 13 25000000 after stantmi03 25 189000000 13.228
77505 Giancarlo Stanton Stanton 2016 470 413 50 27 99 2 4 0.240 0.326 2.200 2.46 2.91 3.13 stantmi03 4949 2015 13 25000000 after stantmi03 26 189000000 13.228
77506 Giancarlo Stanton Stanton 2017 692 597 85 59 168 3 7 0.281 0.376 7.300 7.93 7.38 7.74 stantmi03 4949 2015 13 25000000 after stantmi03 27 195000000 12.821
77507 Giancarlo Stanton Stanton 2018 705 617 70 38 164 10 8 0.266 0.343 4.300 4.39 5.00 5.29 stantmi03 4949 2015 13 25000000 after stantmi03 28 197000000 12.690
77508 Giancarlo Stanton Stanton 2019 72 59 12 3 17 1 0 0.288 0.403 0.400 0.38 0.79 0.77 stantmi03 4949 2015 13 25000000 after stantmi03 29 206000000 12.136
77509 Giancarlo Stanton Stanton 2020 94 76 15 4 19 0 2 0.250 0.387 0.400 0.55 0.80 0.94 stantmi03 4949 2015 13 25000000 after stantmi03 30 208000000 12.019
77510 Giancarlo Stanton Stanton 2021 579 510 63 35 139 3 3 0.273 0.354 2.600 3.07 3.10 3.33 stantmi03 4949 2015 13 25000000 after stantmi03 31 210000000 11.905
77511 Giancarlo Stanton Stanton 2022 452 398 50 31 84 3 0 0.211 0.297 1.200 0.65 1.71 1.16 stantmi03 4949 2015 13 25000000 after stantmi03 32 230000000 10.870
77512 Giancarlo Stanton Stanton 2023 415 371 41 24 71 1 2 0.191 0.275 -0.838 -0.76 -0.47 -0.52 stantmi03 4949 2015 13 25000000 after stantmi03 33 233000000 10.730
77513 Giancarlo Stanton Stanton 2024 459 417 38 27 97 2 2 0.233 0.298 0.775 0.73 1.43 1.46 stantmi03 4949 2015 13 25000000 after stantmi03 34 237000000 10.549
79409 Dansby Swanson Swanson 2016 145 129 13 3 39 2 0 0.302 0.361 0.800 1.06 1.46 1.86 swansda01 18314 2023 7 25285714 before swansda01 22 189000000 13.379
79410 Dansby Swanson Swanson 2017 551 488 59 6 113 4 0 0.232 0.312 -0.300 -0.14 1.41 1.53 swansda01 18314 2023 7 25285714 before swansda01 23 195000000 12.967
79411 Dansby Swanson Swanson 2018 533 478 44 14 114 3 2 0.238 0.304 1.800 2.16 2.56 2.77 swansda01 18314 2023 7 25285714 before swansda01 24 197000000 12.835
79412 Dansby Swanson Swanson 2019 545 483 51 17 121 5 5 0.251 0.325 1.400 1.06 2.18 1.92 swansda01 18314 2023 7 25285714 before swansda01 25 206000000 12.275
79413 Dansby Swanson Swanson 2020 264 237 22 10 65 1 4 0.274 0.345 1.900 2.84 5.14 7.20 swansda01 18314 2023 7 25285714 before swansda01 26 208000000 12.157
79414 Dansby Swanson Swanson 2021 653 588 52 27 146 7 5 0.248 0.311 3.200 2.08 3.74 2.73 swansda01 18314 2023 7 25285714 before swansda01 27 210000000 12.041
79415 Dansby Swanson Swanson 2022 696 640 49 25 177 4 3 0.277 0.329 6.400 5.53 6.04 6.00 swansda01 18314 2023 7 25285714 before swansda01 28 230000000 10.994
79416 Dansby Swanson Swanson 2023 638 565 66 22 138 2 5 0.244 0.328 4.936 4.79 5.30 5.10 swansda01 18314 2023 7 25285714 after swansda01 29 233000000 10.852
79417 Dansby Swanson Swanson 2024 593 534 54 16 129 3 2 0.242 0.312 4.348 3.97 5.05 4.81 swansda01 18314 2023 7 25285714 after swansda01 30 237000000 10.669
79901 Fernando Tatis Jr Tatis Jr 2019 372 334 30 22 106 3 5 0.317 0.379 3.700 4.17 3.82 4.07 tatisfe02 19709 2021 14 24285714 before tatisfe02 20 206000000 11.789
79902 Fernando Tatis Jr Tatis Jr 2020 257 224 27 17 62 1 5 0.277 0.366 2.900 2.77 6.95 6.94 tatisfe02 19709 2021 14 24285714 before tatisfe02 21 208000000 11.676
79903 Fernando Tatis Jr Tatis Jr 2021 546 478 62 42 135 4 2 0.282 0.364 6.100 6.63 7.11 8.48 tatisfe02 19709 2021 14 24285714 after tatisfe02 22 210000000 11.565
79904 Fernando Tatis Jr Tatis Jr 2023 635 575 53 25 148 3 3 0.257 0.322 4.381 5.47 4.67 6.18 tatisfe02 19709 2021 14 24285714 after tatisfe02 24 233000000 10.423
79905 Fernando Tatis Jr Tatis Jr 2024 438 398 32 21 110 1 7 0.276 0.340 3.228 2.63 3.68 3.06 tatisfe02 19709 2021 14 24285714 after tatisfe02 25 237000000 10.247
80269 Mark Teixeira Teixeira 2003 589 529 44 26 137 2 14 0.259 0.331 1.700 2.69 1.91 2.62 teixema01 1281 2009 8 22500000 before teixema01 23 117000000 19.231
80270 Mark Teixeira Teixeira 2004 625 545 68 38 153 2 10 0.281 0.370 4.200 4.60 4.48 5.18 teixema01 1281 2009 8 22500000 before teixema01 24 120500000 18.672
80271 Mark Teixeira Teixeira 2005 730 644 72 43 194 3 11 0.301 0.379 5.900 7.23 6.37 7.48 teixema01 1281 2009 8 22500000 before teixema01 25 128000000 17.578
80272 Mark Teixeira Teixeira 2006 727 628 89 33 177 6 4 0.282 0.371 3.500 4.39 3.88 4.64 teixema01 1281 2009 8 22500000 before teixema01 26 136500000 16.484
80273 Mark Teixeira Teixeira 2007 575 494 72 30 151 2 7 0.306 0.400 4.300 4.59 4.52 5.03 teixema01 1281 2009 8 22500000 before teixema01 27 148000000 15.203
80274 Mark Teixeira Teixeira 2008 685 574 97 33 177 7 7 0.308 0.410 6.900 7.80 6.56 7.96 teixema01 1281 2009 8 22500000 before teixema01 28 155000000 14.516
80275 Mark Teixeira Teixeira 2009 707 609 81 39 178 5 12 0.292 0.383 5.200 5.27 5.41 5.67 teixema01 1281 2009 8 22500000 after teixema01 29 162000000 13.889
80276 Mark Teixeira Teixeira 2010 712 601 93 33 154 5 13 0.256 0.365 3.500 4.11 4.07 4.59 teixema01 1281 2009 8 22500000 after teixema01 30 170000000 13.235
80277 Mark Teixeira Teixeira 2011 684 589 76 39 146 8 11 0.248 0.341 4.300 3.41 4.51 4.19 teixema01 1281 2009 8 22500000 after teixema01 31 178000000 12.640
80278 Mark Teixeira Teixeira 2012 524 451 54 24 113 12 7 0.251 0.332 2.700 3.79 3.33 4.54 teixema01 1281 2009 8 22500000 after teixema01 32 178000000 12.640
80279 Mark Teixeira Teixeira 2013 63 53 8 3 8 1 1 0.151 0.270 -0.100 -0.22 0.29 0.28 teixema01 1281 2009 8 22500000 after teixema01 33 178000000 12.640
80280 Mark Teixeira Teixeira 2014 508 440 58 22 95 4 6 0.216 0.313 0.700 0.76 1.78 1.85 teixema01 1281 2009 8 22500000 after teixema01 34 189000000 11.905
80281 Mark Teixeira Teixeira 2015 462 392 59 31 100 5 6 0.255 0.357 2.900 3.31 3.41 3.79 teixema01 1281 2009 8 22500000 after teixema01 35 189000000 11.905
80282 Mark Teixeira Teixeira 2016 438 387 47 15 79 2 2 0.204 0.292 -1.000 -1.11 0.99 1.03 teixema01 1281 2009 8 22500000 after teixema01 36 189000000 11.905
82217 Mike Trout Trout 2011 135 123 9 5 27 1 2 0.220 0.281 0.700 0.47 1.26 1.03 troutmi01 10155 2019 12 35583333 before troutmi01 19 178000000 19.991
82218 Mike Trout Trout 2012 639 559 67 30 182 7 6 0.326 0.399 10.100 10.54 8.29 9.23 troutmi01 10155 2019 12 35583333 before troutmi01 20 178000000 19.991
82219 Mike Trout Trout 2013 716 589 110 27 190 8 9 0.323 0.432 10.200 8.90 9.24 9.80 troutmi01 10155 2019 12 35583333 before troutmi01 21 178000000 19.991
82220 Mike Trout Trout 2014 705 602 83 36 173 10 10 0.287 0.377 8.300 7.71 7.82 8.21 troutmi01 10155 2019 12 35583333 before troutmi01 22 189000000 18.827
82221 Mike Trout Trout 2015 682 575 92 41 172 5 10 0.299 0.402 9.300 9.62 8.96 9.61 troutmi01 10155 2019 12 35583333 before troutmi01 23 189000000 18.827
82222 Mike Trout Trout 2016 681 549 116 29 173 5 11 0.315 0.441 9.700 10.48 9.53 10.15 troutmi01 10155 2019 12 35583333 before troutmi01 24 189000000 18.827
82223 Mike Trout Trout 2017 507 402 94 33 123 4 7 0.306 0.442 6.800 6.92 7.02 7.29 troutmi01 10155 2019 12 35583333 before troutmi01 25 195000000 18.248
82224 Mike Trout Trout 2018 608 471 122 39 147 4 10 0.312 0.460 9.600 9.92 7.87 8.38 troutmi01 10155 2019 12 35583333 before troutmi01 26 197000000 18.063
82225 Mike Trout Trout 2019 600 470 110 45 137 4 16 0.291 0.438 8.400 7.89 8.16 8.68 troutmi01 10155 2019 12 35583333 after troutmi01 27 206000000 17.273
82226 Mike Trout Trout 2020 241 199 35 17 56 4 3 0.281 0.390 2.500 1.82 5.69 4.66 troutmi01 10155 2019 12 35583333 after troutmi01 28 208000000 17.107
82227 Mike Trout Trout 2021 146 117 27 8 39 0 2 0.333 0.466 2.300 1.81 3.64 3.21 troutmi01 10155 2019 12 35583333 after troutmi01 29 210000000 16.944
82228 Mike Trout Trout 2022 499 438 54 40 124 1 6 0.283 0.369 6.000 6.22 7.18 7.41 troutmi01 10155 2019 12 35583333 after troutmi01 30 230000000 15.471
82229 Mike Trout Trout 2023 362 308 45 18 81 2 7 0.263 0.367 2.974 2.87 3.49 3.50 troutmi01 10155 2019 12 35583333 after troutmi01 31 233000000 15.272
82230 Mike Trout Trout 2024 126 109 16 10 24 0 1 0.220 0.325 0.984 1.05 1.14 1.25 troutmi01 10155 2019 12 35583333 after troutmi01 32 237000000 15.014
82512 Trea Turner Turner 2015 44 40 4 1 9 0 0 0.225 0.295 0.000 0.29 0.48 0.79 turnetr01 16252 2023 11 27272727 before turnetr01 22 189000000 14.430
82513 Trea Turner Turner 2016 324 307 14 13 105 2 1 0.342 0.370 3.300 3.44 3.99 4.06 turnetr01 16252 2023 11 27272727 before turnetr01 23 189000000 14.430
82514 Trea Turner Turner 2017 447 412 30 11 117 1 4 0.284 0.338 2.800 3.04 3.17 3.34 turnetr01 16252 2023 11 27272727 before turnetr01 24 195000000 13.986
82515 Trea Turner Turner 2018 740 664 69 19 180 0 5 0.271 0.344 4.800 4.71 5.41 5.71 turnetr01 16252 2023 11 27272727 before turnetr01 25 197000000 13.844
82516 Trea Turner Turner 2019 569 521 43 19 155 2 3 0.298 0.353 3.600 4.04 4.06 4.34 turnetr01 16252 2023 11 27272727 before turnetr01 26 206000000 13.239
82517 Trea Turner Turner 2020 259 233 22 12 78 2 2 0.335 0.394 2.700 2.75 6.61 6.81 turnetr01 16252 2023 11 27272727 before turnetr01 27 208000000 13.112
82518 Trea Turner Turner 2021 646 595 41 28 195 4 6 0.328 0.375 6.900 6.41 7.62 6.94 turnetr01 16252 2023 11 27272727 before turnetr01 28 210000000 12.987
82519 Trea Turner Turner 2022 708 652 45 21 194 6 3 0.298 0.343 6.300 5.23 5.86 5.69 turnetr01 16252 2023 11 27272727 before turnetr01 29 230000000 11.858
82520 Trea Turner Turner 2023 691 639 45 26 170 1 6 0.266 0.320 3.807 3.38 4.08 3.93 turnetr01 16252 2023 11 27272727 after turnetr01 30 233000000 11.705
82521 Trea Turner Turner 2024 539 505 27 21 149 1 6 0.295 0.338 3.911 2.99 4.31 3.52 turnetr01 16252 2023 11 27272727 after turnetr01 31 237000000 11.507
84242 Joey Votto Votto 2007 89 84 5 4 27 0 0 0.321 0.360 -0.100 0.05 0.27 0.40 vottojo01 4314 2014 10 21800000 before vottojo01 23 148000000 14.730
84243 Joey Votto Votto 2008 589 526 59 24 156 2 2 0.297 0.368 3.600 3.31 3.97 3.87 vottojo01 4314 2014 10 21800000 before vottojo01 24 155000000 14.065
84244 Joey Votto Votto 2009 544 469 70 25 151 1 4 0.322 0.414 4.600 4.81 4.72 5.07 vottojo01 4314 2014 10 21800000 before vottojo01 25 162000000 13.457
84245 Joey Votto Votto 2010 648 547 91 37 177 3 7 0.324 0.424 6.900 6.97 6.91 6.70 vottojo01 4314 2014 10 21800000 before vottojo01 26 170000000 12.824
84246 Joey Votto Votto 2011 719 599 110 29 185 6 4 0.309 0.416 6.400 6.63 5.84 6.55 vottojo01 4314 2014 10 21800000 before vottojo01 27 178000000 12.247
84247 Joey Votto Votto 2012 475 374 94 14 126 2 5 0.337 0.474 5.300 5.90 5.59 6.70 vottojo01 4314 2014 10 21800000 before vottojo01 28 178000000 12.247
84248 Joey Votto Votto 2013 726 581 135 24 177 6 4 0.305 0.435 5.700 6.64 5.97 6.61 vottojo01 4314 2014 10 21800000 before vottojo01 29 178000000 12.247
84249 Joey Votto Votto 2014 272 220 47 6 56 2 3 0.255 0.390 0.800 1.68 1.41 2.18 vottojo01 4314 2014 10 21800000 after vottojo01 30 189000000 11.534
84250 Joey Votto Votto 2015 695 545 143 29 171 2 5 0.314 0.459 7.300 7.84 7.65 8.01 vottojo01 4314 2014 10 21800000 after vottojo01 31 189000000 11.534
84251 Joey Votto Votto 2016 677 556 108 29 181 8 5 0.326 0.434 5.200 4.22 5.65 4.98 vottojo01 4314 2014 10 21800000 after vottojo01 32 189000000 11.534
84252 Joey Votto Votto 2017 707 559 134 36 179 6 8 0.320 0.454 6.500 8.09 6.44 7.98 vottojo01 4314 2014 10 21800000 after vottojo01 33 195000000 11.179
84253 Joey Votto Votto 2018 623 503 108 12 143 3 9 0.284 0.417 3.500 3.60 4.19 4.21 vottojo01 4314 2014 10 21800000 after vottojo01 34 197000000 11.066
84254 Joey Votto Votto 2019 608 525 76 15 137 3 4 0.261 0.357 0.500 1.36 1.73 2.24 vottojo01 4314 2014 10 21800000 after vottojo01 35 206000000 10.583
84255 Joey Votto Votto 2020 223 186 37 11 42 0 0 0.226 0.354 0.500 -0.01 2.56 2.19 vottojo01 4314 2014 10 21800000 after vottojo01 36 208000000 10.481
84256 Joey Votto Votto 2021 533 448 77 36 119 4 4 0.266 0.375 3.700 3.65 3.99 3.96 vottojo01 4314 2014 10 21800000 after vottojo01 37 210000000 10.381
84257 Joey Votto Votto 2022 376 322 44 11 66 0 10 0.205 0.319 -0.900 -0.14 -0.44 0.26 vottojo01 4314 2014 10 21800000 after vottojo01 38 230000000 9.478
84258 Joey Votto Votto 2023 242 208 27 14 42 0 7 0.202 0.314 0.039 -0.08 NA NA vottojo01 4314 2014 10 21800000 after NA NA 233000000 9.356
88945 David Wright Wright 2004 283 263 14 14 77 3 3 0.293 0.332 2.300 2.15 2.75 2.66 wrighda03 3787 2007 12 13750000 before wrighda03 21 120500000 11.411
88946 David Wright Wright 2005 657 575 72 27 176 3 7 0.306 0.388 5.800 4.78 6.25 5.15 wrighda03 3787 2007 12 13750000 before wrighda03 22 128000000 10.742
88947 David Wright Wright 2006 661 582 66 26 181 8 5 0.311 0.381 4.700 4.07 5.12 4.26 wrighda03 3787 2007 12 13750000 before wrighda03 23 136500000 10.073
88948 David Wright Wright 2007 711 604 94 30 196 7 6 0.325 0.416 8.400 8.34 7.98 7.91 wrighda03 3787 2007 12 13750000 after wrighda03 24 148000000 9.291
88949 David Wright Wright 2008 736 626 94 33 189 11 4 0.302 0.390 7.000 6.85 6.56 6.78 wrighda03 3787 2007 12 13750000 after wrighda03 25 155000000 8.871
88950 David Wright Wright 2009 618 535 74 10 164 6 3 0.307 0.390 3.200 3.17 3.74 3.68 wrighda03 3787 2007 12 13750000 after wrighda03 26 162000000 8.488
88951 David Wright Wright 2010 670 587 69 29 166 12 2 0.283 0.354 3.400 2.79 3.93 3.55 wrighda03 3787 2007 12 13750000 after wrighda03 27 170000000 8.088
88952 David Wright Wright 2011 447 389 52 14 99 3 3 0.254 0.345 1.700 2.11 2.47 2.90 wrighda03 3787 2007 12 13750000 after wrighda03 28 178000000 7.725
88953 David Wright Wright 2012 670 581 81 21 178 5 3 0.306 0.391 6.600 7.06 6.58 7.48 wrighda03 3787 2007 12 13750000 after wrighda03 29 178000000 7.725
88954 David Wright Wright 2013 492 430 55 18 132 2 5 0.307 0.390 5.600 5.20 5.64 5.52 wrighda03 3787 2007 12 13750000 after wrighda03 30 178000000 7.725
88955 David Wright Wright 2014 586 535 42 8 144 5 4 0.269 0.324 1.600 2.06 2.33 2.90 wrighda03 3787 2007 12 13750000 after wrighda03 31 189000000 7.275
88956 David Wright Wright 2015 174 152 22 5 44 0 0 0.289 0.379 1.000 0.61 1.72 1.29 wrighda03 3787 2007 12 13750000 after wrighda03 32 189000000 7.275
88957 David Wright Wright 2016 164 137 26 7 31 0 0 0.226 0.350 0.700 -0.02 1.39 0.60 wrighda03 3787 2007 12 13750000 after wrighda03 33 189000000 7.275
88958 David Wright Wright 2018 3 2 1 0 0 0 0 0.000 0.333 0.000 -0.01 0.10 0.10 wrighda03 3787 2007 12 13750000 after wrighda03 35 197000000 6.980
89357 Christian Yelich Yelich 2013 273 240 31 4 69 1 1 0.288 0.370 1.800 1.57 2.36 2.11 yelicch01 11477 2020 9 27000000 before yelicch01 21 178000000 15.169
89358 Christian Yelich Yelich 2014 660 582 70 9 165 2 3 0.284 0.362 4.100 3.83 4.49 4.18 yelicch01 11477 2020 9 27000000 before yelicch01 22 189000000 14.286
89359 Christian Yelich Yelich 2015 525 476 47 7 143 0 2 0.300 0.366 2.400 3.57 3.03 4.15 yelicch01 11477 2020 9 27000000 before yelicch01 23 189000000 14.286
89360 Christian Yelich Yelich 2016 659 578 72 21 172 5 4 0.298 0.376 5.400 4.88 5.87 5.23 yelicch01 11477 2020 9 27000000 before yelicch01 24 189000000 14.286
89361 Christian Yelich Yelich 2017 695 602 80 18 170 6 6 0.282 0.369 4.600 3.69 4.93 4.20 yelicch01 11477 2020 9 27000000 before yelicch01 25 195000000 13.846
89362 Christian Yelich Yelich 2018 651 574 68 36 187 2 7 0.326 0.402 7.700 7.26 7.53 7.37 yelicch01 11477 2020 9 27000000 before yelicch01 26 197000000 13.706
89363 Christian Yelich Yelich 2019 580 489 80 44 161 3 8 0.329 0.429 7.800 6.95 7.58 6.77 yelicch01 11477 2020 9 27000000 before yelicch01 27 206000000 13.107
89364 Christian Yelich Yelich 2020 247 200 46 12 41 0 1 0.205 0.356 0.700 0.47 2.97 2.82 yelicch01 11477 2020 9 27000000 after yelicch01 28 208000000 12.981
89365 Christian Yelich Yelich 2021 475 399 70 9 99 3 3 0.248 0.362 1.500 1.30 2.09 1.94 yelicch01 11477 2020 9 27000000 after yelicch01 29 210000000 12.857
89366 Christian Yelich Yelich 2022 671 575 88 14 145 2 5 0.252 0.355 2.300 2.53 2.83 2.86 yelicch01 11477 2020 9 27000000 after yelicch01 30 230000000 11.739
89367 Christian Yelich Yelich 2023 632 550 78 19 153 1 3 0.278 0.370 4.133 3.61 4.55 4.15 yelicch01 11477 2020 9 27000000 after yelicch01 31 233000000 11.588
89368 Christian Yelich Yelich 2024 315 270 40 11 85 1 2 0.315 0.406 3.010 2.21 2.70 2.29 yelicch01 11477 2020 9 27000000 after yelicch01 32 237000000 11.392

Dollar Per WAR

In order for a team to be successful, they must properly allocate their funds efficiently, and not waste it on players who are not contributing. You want your team full of players who have highly positive WAR values. …

A study by The Paraball Notes found that based on free agent contracts signed after the 2024 season, the current dollar per war value teams would be paying is $8 million. Logically, this can’t be applied for every single season, as the luxury tax threshold increases and naturally player contracts also increase. Instead, we calculated the percentage that $8 million would be of the current luxury tax threshold, $241 million, and that means each WAR paid for by a team should take up about 3.32% of the payroll. This checks out since about half of MLB teams, using this value, ended up below and half ended up above the ~33 WAR that would be totaled in the 2024 season, multiplying 1 WAR = 3.32% of payroll. So we extrapolate the 3.32% luxury tax per WAR for every season since 2003 to assess whether a player successfully accumulated enough WAR to match their salary. If a player takes up 9.96% of their team’s luxury tax payroll, they need to accumulate 3 WAR that season to meet expectations.

WAR total data
name total_efWAR total_ebWAR total_bWAR total_fWAR total_WAR_needed total_WAR_diff_efWAR total_WAR_diff_ebWAR total_WAR_diff_bWAR total_WAR_diff_fWAR adjusted_contract_value contract_tier_efWAR contract_tier_ebWAR contract_tier_bWAR contract_tier_fWAR eWAR non_eWAR total_WAR_diff_eWAR total_WAR_diff_non_eWAR contract_tier_eWAR contract_tier_non_eWAR
A-Rod 26.15 28.25 23.09 22.60 38.05 -11.90 -9.80 -14.96 -15.45 275000000 Well Short of Expectations Well Short of Expectations Well Short of Expectations Well Short of Expectations 27.200 22.845 -10.850 -15.205 Well Short of Expectations Well Short of Expectations
Aaron Judge 15.08 15.44 15.29 16.54 10.25 4.83 5.19 5.04 6.29 80000000 Just Above Expectations Far Exceeded Expectations Far Exceeded Expectations Far Exceeded Expectations 15.260 15.915 5.010 5.665 Far Exceeded Expectations Far Exceeded Expectations
Albert Pujols 18.03 23.82 12.75 5.60 37.40 -19.37 -13.58 -24.65 -31.80 240000000 Well Short of Expectations Well Short of Expectations Well Short of Expectations Well Short of Expectations 20.925 9.175 -16.475 -28.225 Well Short of Expectations Well Short of Expectations
Alex Rodriguez 52.63 55.92 56.40 56.10 29.41 7.90 10.32 9.83 8.89 176400000 Far Exceeded Expectations Far Exceeded Expectations Far Exceeded Expectations Far Exceeded Expectations 54.275 56.250 24.865 26.840 Far Exceeded Expectations Far Exceeded Expectations
Anthony Rendon 9.29 8.16 3.69 4.19 23.64 -14.35 -15.48 -19.95 -19.45 175000000 Well Short of Expectations Well Short of Expectations Well Short of Expectations Well Short of Expectations 8.725 3.940 -14.915 -19.700 Well Short of Expectations Well Short of Expectations
Bryce Harper 29.87 29.21 23.27 23.59 20.86 9.01 8.35 2.41 2.73 152307692 Far Exceeded Expectations Far Exceeded Expectations Met Expectations Just Above Expectations 29.540 23.430 8.680 2.570 Far Exceeded Expectations Just Above Expectations
Buster Posey 43.22 35.83 32.20 41.60 22.81 20.41 13.02 9.39 18.79 165000000 Far Exceeded Expectations Far Exceeded Expectations Far Exceeded Expectations Far Exceeded Expectations 39.525 36.900 16.715 14.090 Far Exceeded Expectations Far Exceeded Expectations
Carlos Correa 10.51 11.61 10.36 9.82 12.91 -2.40 -1.30 -2.55 -3.09 100000000 Met Expectations Met Expectations Just Short of Expectations Just Short of Expectations 11.060 10.090 -1.850 -2.820 Met Expectations Just Short of Expectations
Christian Yelich 15.14 14.06 10.12 11.64 18.24 -3.10 -4.18 -8.12 -6.60 135000000 Just Short of Expectations Just Short of Expectations Well Short of Expectations Well Short of Expectations 14.600 10.880 -3.640 -7.360 Just Short of Expectations Well Short of Expectations
Corey Seager 16.81 17.59 15.67 15.14 12.59 4.22 5.00 3.08 2.55 97500000 Just Above Expectations Far Exceeded Expectations Just Above Expectations Just Above Expectations 17.200 15.405 4.610 2.815 Just Above Expectations Just Above Expectations
Dansby Swanson 10.35 9.91 8.76 9.29 6.48 3.87 3.43 2.28 2.81 50571429 Just Above Expectations Just Above Expectations Met Expectations Just Above Expectations 10.130 9.025 3.650 2.545 Just Above Expectations Just Above Expectations
David Wright 42.44 42.71 38.16 39.20 26.12 16.32 16.59 12.04 13.08 165000000 Far Exceeded Expectations Far Exceeded Expectations Far Exceeded Expectations Far Exceeded Expectations 42.575 38.680 16.455 12.560 Far Exceeded Expectations Far Exceeded Expectations
Derek Jeter 47.45 43.56 41.23 44.70 32.59 5.77 2.41 -0.22 2.71 189000000 Far Exceeded Expectations Met Expectations Met Expectations Just Above Expectations 45.505 42.965 12.915 10.375 Far Exceeded Expectations Far Exceeded Expectations
Fernando Tatis Jr 15.46 17.72 14.73 13.71 9.71 5.75 8.01 5.02 4.00 97142857 Far Exceeded Expectations Far Exceeded Expectations Far Exceeded Expectations Just Above Expectations 16.590 14.220 6.880 4.510 Far Exceeded Expectations Just Above Expectations
Francisco Lindor 23.25 22.79 21.49 23.29 18.10 5.15 4.69 3.39 5.19 136400000 Far Exceeded Expectations Just Above Expectations Just Above Expectations Far Exceeded Expectations 23.020 22.390 4.920 4.290 Just Above Expectations Just Above Expectations
Giancarlo Stanton 26.99 27.86 23.10 21.84 36.20 -9.21 -8.34 -13.10 -14.36 250000000 Well Short of Expectations Well Short of Expectations Well Short of Expectations Well Short of Expectations 27.425 22.470 -8.775 -13.730 Well Short of Expectations Well Short of Expectations
Joe Mauer 23.77 27.61 22.04 18.30 29.74 -5.97 -2.13 -7.70 -11.44 184000000 Well Short of Expectations Met Expectations Well Short of Expectations Well Short of Expectations 25.690 20.170 -4.050 -9.570 Just Short of Expectations Well Short of Expectations
Joey Votto 33.18 36.01 30.21 27.14 32.27 3.73 6.56 -2.06 -5.13 218000000 Just Above Expectations Far Exceeded Expectations Met Expectations Well Short of Expectations 34.595 28.675 2.325 -3.595 Met Expectations Just Short of Expectations
Jose Altuve 32.35 29.52 24.52 28.26 22.84 9.51 6.68 1.68 5.42 164000000 Far Exceeded Expectations Far Exceeded Expectations Met Expectations Far Exceeded Expectations 30.935 26.390 8.095 3.550 Far Exceeded Expectations Just Above Expectations
Kris Bryant 0.64 0.33 -1.33 -1.36 10.07 -6.13 -6.44 -11.40 -11.43 78000000 Well Short of Expectations Well Short of Expectations Well Short of Expectations Well Short of Expectations 0.485 -1.345 -9.585 -11.415 Well Short of Expectations Well Short of Expectations
Manny Machado 30.95 30.95 23.39 24.64 26.15 4.80 4.80 -2.76 -1.51 190909091 Just Above Expectations Just Above Expectations Just Short of Expectations Met Expectations 30.950 24.015 4.800 -2.135 Just Above Expectations Met Expectations
Marcus Semien 16.33 18.88 17.03 14.67 9.68 6.65 9.20 7.35 4.99 75000000 Far Exceeded Expectations Far Exceeded Expectations Far Exceeded Expectations Just Above Expectations 17.605 15.850 7.925 6.170 Far Exceeded Expectations Far Exceeded Expectations
Mark Teixeira 23.79 25.94 19.32 18.20 30.35 -6.56 -4.41 -11.03 -12.15 180000000 Well Short of Expectations Just Short of Expectations Well Short of Expectations Well Short of Expectations 24.865 18.760 -5.485 -11.590 Well Short of Expectations Well Short of Expectations
Matt Olson 14.01 16.20 14.51 12.36 8.13 5.88 8.07 6.38 4.23 63000000 Far Exceeded Expectations Far Exceeded Expectations Far Exceeded Expectations Just Above Expectations 15.105 13.435 6.975 5.305 Far Exceeded Expectations Far Exceeded Expectations
Miguel Cabrera 11.28 11.96 2.37 2.31 36.00 -20.72 -20.04 -33.63 -33.69 248000000 Well Short of Expectations Well Short of Expectations Well Short of Expectations Well Short of Expectations 11.620 2.340 -24.380 -33.660 Well Short of Expectations Well Short of Expectations
Mike Trout 29.30 28.71 21.66 23.15 29.24 0.06 -0.53 -7.58 -6.09 213500000 Met Expectations Met Expectations Well Short of Expectations Well Short of Expectations 29.005 22.405 -0.235 -6.835 Met Expectations Well Short of Expectations
Mookie Betts 24.39 25.47 23.77 23.14 16.14 8.25 9.33 7.63 7.00 121666667 Far Exceeded Expectations Far Exceeded Expectations Far Exceeded Expectations Far Exceeded Expectations 24.930 23.455 8.790 7.315 Far Exceeded Expectations Far Exceeded Expectations
Nolan Arenado 27.67 28.91 25.33 24.17 26.71 0.96 2.20 -1.38 -2.54 195000000 Met Expectations Met Expectations Met Expectations Just Short of Expectations 28.290 24.750 1.580 -1.960 Met Expectations Met Expectations
Rafael Devers 8.39 8.34 7.15 7.26 8.05 0.34 0.29 -0.90 -0.79 62800000 Met Expectations Met Expectations Met Expectations Met Expectations 8.365 7.205 0.315 -0.845 Met Expectations Met Expectations
Shohei Ohtani 8.10 8.63 9.22 9.07 8.90 -0.80 -0.27 0.32 0.17 70000000 Met Expectations Met Expectations Met Expectations Met Expectations 8.365 9.145 -0.535 0.245 Met Expectations Met Expectations
Trea Turner 8.39 7.45 6.37 7.72 6.99 1.40 0.46 -0.62 0.73 54545455 Met Expectations Met Expectations Met Expectations Met Expectations 7.920 7.045 0.930 0.055 Met Expectations Met Expectations
Xander Bogaerts 7.09 6.47 5.60 6.44 6.53 0.56 -0.06 -0.93 -0.09 50909091 Met Expectations Met Expectations Met Expectations Met Expectations 6.780 6.020 0.250 -0.510 Met Expectations Met Expectations

According to bWAR and fWAR, our unadjusted wins above replacement values, 16 of the mega contracts fell well short of expectations. However, according to ebWAR and efWAR, our era-adjusted wins above replacement values, only 10 of the mega contracts fell short of expectations. What does this mean? In the moment during some of those seasons, the player did not perform up to expectations. But as time has gone on, that season actually has aged well, as era-adjusted statistics indicate the talent pool was greater that season. Just 7 contracts heavily outperformed expectations from our unadjusted WAR, while 16 heavily outperformed them based on era-adjusted WAR. 5 contracts were right at expectations, 3 just short, and 4 just above for unadjusted WAR, while 6 contracts were right at expectations, 2 just short, and 1 just above for era-adjusted WAR. The cutoffs were +- >= 5 WAR over the contract duration for heavily over or underperforming, and +- 2.5 to 5 for just above or just below expectations, 0 to 2.5 for just met expectations.

Regression Models for Mega Contracts and Juan Soto

In order to quantify and observe the relationship between the many aspects of mega contracts (luxury tax %, dollar per WAR, salary) and WAR statistics, we can use linear regression models.

We will run the following regressions: Average Dollar per WAR vs Average WAR (Do better players cost more per WAR?), Average Luxury Tax Percent vs Average WAR per Year (Do stars take up significantly more of the cap?), Average Dollar per WAR vs Average Luxury Tax Percentage (Does higher cap share mean worse value?)

## 
## Call:
## lm(formula = Dollar_per_WAR ~ avg_WAR, data = war_data)
## 
## Residuals:
##       Min        1Q    Median        3Q       Max 
## -20087423 -10529038  -6477628   3285226 283699904 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 38744176    4993355   7.759 1.25e-12 ***
## avg_WAR     -6023223    1071905  -5.619 9.16e-08 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 30100000 on 149 degrees of freedom
## Multiple R-squared:  0.1749, Adjusted R-squared:  0.1693 
## F-statistic: 31.58 on 1 and 149 DF,  p-value: 9.162e-08
## 
## Call:
## lm(formula = avg_LTP_pct ~ avg_WAR_per_year, data = war_data_agg)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -5.200 -1.873  0.059  1.445 11.227 
## 
## Coefficients:
##                  Estimate Std. Error t value Pr(>|t|)    
## (Intercept)        9.8199     1.2620   7.781 1.11e-08 ***
## avg_WAR_per_year   0.9282     0.2894   3.207  0.00318 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.393 on 30 degrees of freedom
## Multiple R-squared:  0.2553, Adjusted R-squared:  0.2305 
## F-statistic: 10.29 on 1 and 30 DF,  p-value: 0.003178
## 
## Call:
## lm(formula = avg_dollar_per_WAR ~ avg_LTP_pct, data = war_data_agg)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -236454812  -49150397  -26341120   -2645598  773396660 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)
## (Intercept)  27290285  103300962   0.264    0.793
## avg_LTP_pct   3157374    7425188   0.425    0.674
## 
## Residual standard error: 159900000 on 30 degrees of freedom
## Multiple R-squared:  0.005991,   Adjusted R-squared:  -0.02714 
## F-statistic: 0.1808 on 1 and 30 DF,  p-value: 0.6737

From these regressions, we find that logically, the mega contract players who are high-WAR take up more of the luxury tax and cost more per WAR, but this is market driven, not inefficiency. For every 1 unit increase in average WAR, their cost per WAR goes down about $6 million, so the market suggests signing these mega contract players is more efficient for dollar per WAR. We will come back to this a little later.

Juan Soto’s current $8 million/WAR and ~21% luxury tax cap share (which will go down every season) are what you’d expect in the modern day market, given the historical trends for these elite players. The relationshops indicates that for 1 additional WAR a player produces, they take a little under 1% more of the luxury tax, so a guy like Soto, when his contract luxury tax percentage levels off, and averages around 17% of the tax across the duration of his contract, lines up with expectations.

There is no evidence that consuming a large share of the tax correlates with being a worse value. This suggests Soto’s deal aligns with the economics of star-level performances and contracts.

Dollar per WAR as a function of WAR

We can visualize these regressions by plotting them to see the trend. First, going by every individual season, in which a quadratic relationship is observed.

As shown in the plot, there’s a strong inverse relationship between total WAR over a contract and the dollar paid per WAR. Players who produce more WAR tend to be far more cost-efficient, with $/WAR dropping sharply as WAR increases. This means teams get significantly more value from high-WAR performers, especially over long-term deals.

For mega-contracts like Juan Soto’s, this is key: if he consistently posts high WAR, his $51 million AAV becomes more justifiable. But if his WAR dips, the cost per win quickly becomes unsustainable. In short, elite performance drives down cost per WAR, making star players a better long-term investment.

We can also check for over duration of a mega contract:

Removing the extreme outlier of Kris Bryant, whose contract was derailed by injuries, we see a clear trend: players with high total WAR deliver far better value, with significantly lower dollar per WAR.

At the far right, Alex Rodriguez’s first contract is the standout — delivering over 50 WAR at a bargain rate of under $4 million per WAR. That’s the gold standard for a mega-deal paying off. In contrast, players like Giancarlo Stanton or Christian Yelich sit higher on the chart, showing that even productive players can end up costly if WAR doesn’t accumulate as expected.

The plot highlights the reality of long-term contracts: when stars stay healthy and productive, they offer real surplus value. But when availability or performance falters, $ per WAR spikes quickly. For Juan Soto’s deal to pay off, he’ll need to land on the right side of that curve—combining consistency, durability, and elite output year after year.

Luxury Tax Percent as function of Avg WAR

These scatterplots of average luxury tax payroll percentage against average WAR per year illustrates a clear and statistically significant positive relationship between player performance and cap space allocation. The red regression line, with a slope of approximately 0.99% per WAR and a p-value of 0.0075, shows that as a player’s WAR increases, they tend to consume a larger share of a team’s luxury tax threshold. Players are visibly clustered into tiers: those producing under 3 WAR per year typically occupy less than 12% of the cap (e.g., Giancarlo Stanton, Xander Bogaerts), while stars producing between 3–6 WAR/year fall into the 12–16% range (e.g., Mike Trout, Manny Machado, Mookie Betts). A few elite players, like Aaron Judge and Alex Rodriguez, exceed 6 WAR/year and command over 20% of their team’s cap, highlighting how rare teams are willing to go that high. Notable outliers include Anthony Rendon and Miguel Cabrera, who consumed large cap shares despite modest WAR returns—likely due to injury or aging curves—while players like Matt Olson, Marcus Semien, and Fernando Tatis Jr. offered high WAR at low cap shares, reflecting team-friendly extensions. Juan Soto, projected to produce approximately 6.5 WAR per year and consume about 17% of the Mets’ luxury tax threshold when averages, would land squarely among the central cluster of modern star contracts. His placement would align closely with players like Trout, Lindor, and Machado, suggesting that Soto’s deal reflects prevailing spending norms for top-tier talent and is not an outlier in terms of efficiency or cap burden.

Dollar per WAR vs Luxury Tax %

Another regression plot we have is Dollar per WAR as a function of Luxury Tax Percentage, averaged per season of the contracts aggregated by player, as well as by individual seasons.

Those below the regression line proved their dollar per WAR production to be worth it according to their luxury tax percentage, while those above were not worth it. We see Shohei Ohtani, who won the World Series in his first year with the Dodgers, far right and below, as well as fellow Dodger Mookie Betts below. Ohtani is also without the added benefit of his pitching due to injury, so his placement in these charts would make him look even mre efficient had he been able to pitch in 2024. A declining Christian Yelich is above the regression line. The general trend shows players who take up more of the luxury tax tend to cost slightly more per unit of WAR, though it is only moderate correlation and not statistically significant, as proven by the earlier regression test. Plus, most star players today are very close to the ~ $8 million per WAR range.

Free Agent Premiums

We decided to dive deeper into the idea of free agent high WAR player premiums, and see if it extended beyond just mega contract players. Since an average player will have about 2-2.5 WAR per season, we classified high WAR players as 4 or more per season. After much data collection and analysis, this is what we found:

T-Test

## 
##  Welch Two Sample t-test
## 
## data:  dollar_per_avg_WAR by High_WAR
## t = 0.94861, df = 110.45, p-value = 0.3449
## alternative hypothesis: true difference in means between group FALSE and group TRUE is not equal to 0
## 95 percent confidence interval:
##  -393943.5 1117416.2
## sample estimates:
## mean in group FALSE  mean in group TRUE 
##             3462533             3100796

The Welch two-sample t-test reveals no statistically significant difference in average dollar per WAR between high-WAR (≥ 4 WAR) and low-WAR free agents (p = 0.601). While high-WAR players average $3.02M per WAR and low-WAR players average $2.79M per WAR, the difference of ~$231K is not significant and lies well within the 95% confidence interval (–$1.10M to +$637K). This indicates no consistent cost premium or discount based on WAR tier. Even changing our parameters, we never end up with much greater than $300K difference in high and low WAR players, indicating lack of a premium.

Regression

## 
## Call:
## lm(formula = dollar_per_avg_WAR ~ High_WAR, data = final_fa_data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -3012920 -1795866  -770501   881752 29037467 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   3462533     221213  15.652   <2e-16 ***
## High_WARTRUE  -361736     513242  -0.705    0.482    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3175000 on 251 degrees of freedom
## Multiple R-squared:  0.001975,   Adjusted R-squared:  -0.002001 
## F-statistic: 0.4968 on 1 and 251 DF,  p-value: 0.4816

The linear regression model aligns with the t-test, finding that high-WAR players cost abot $300k more per WAR on average, but again, this difference is not statistically significant (p = 0.76). The R² value is nearly zero at 0.0003, meaning that WAR classification does not explain variation in free agent contract efficiency, and teams do not reliably pay more or less per WAR based on performance tier.

Scatterplot

This plot shows that as teams spend more (luxury tax % increases), their cost per WAR also rises. Notably, the low-WAR group (red line) shows a steeper increase in $/WAR compared to the high-WAR group (blue line). This suggests that high-spending teams overpay more for lower-WAR players, while elite players remain relatively more efficient at higher payroll levels.

Boxplot

The boxplot reveals that the distributions of $/WAR for high- and low-WAR players are broadly similar, with a large overlap. The high-WAR group has a slightly higher median, but the variation is wide in both groups. This visual reinforces the statistical result that there is no clear, consistent efficiency advantage for either WAR tier. Sure, a slight premium seems to be paid for high WAR players, but it is not statistically significant.

Juan Soto’s projected average WAR far exceeds 4, and his contract’s AAV (~$44M) translates to a $/WAR around $6.9–$7.1M, depending on projections. This may seem high, but the data shows that elite free agents do not cost more per WAR in a statistically consistent way. If anything, Soto’s contract fits the observed trend: higher-WAR players remain more efficient than their lower-WAR counterparts, especially as team spending increases. Soto is not an outlier — he’s in line with how teams pay for top-tier performance.

The Juan Soto of it all

So given all of this, what can we say about Juan Soto?

Juan Soto’s contract is unprecedented in value, length, and timing. At 25 years old, he became one of the youngest players in MLB history to sign a mega contract, making his 15-year, $765M contract with the Mets a defining moment in modern baseball economics. Despite its record-breaking size, the data suggest this deal aligns with league trends, especially when benchmarked by cost-efficiency ($ per WAR) and luxury tax share.

Statistical testing found no significant premium paid for high-WAR free agents relative to lower-tier ones. Regressions and visualizations show that while high-WAR players often consume more of the luxury tax threshold, they typically provide more value per dollar than lower-WAR players. In this context, Soto’s ~$7M per WAR fits the established ~$8M market benchmark, positioning his deal as market-aligned rather than an outlier.

Still, it’s a tall order: Soto needs ~88 WAR across 15 years—or ~5.9 WAR per year—to justify the full value. Based on his pre-contract average (6.3 WAR) and ZiPS projections, that level is attainable. In fact, based on raw WAR, this contract, based on those zips projections, seems to be a great deal for the Mets. But raw WAR alone doesn’t tell the whole story—especially when comparing players across eras.

In the raw WAR plot, Soto’s projected ~$7M per WAR places him well below the regression line, meaning the Mets are expected to get strong value if he meets ZiPS projections. The trend in this plot shows a negative relationship between WAR and $/WAR — players who accumulate more WAR tend to cost less per unit of performance, and Soto fits that model well. This makes his contract look like a potential bargain.

However, the eWAR plot (era-adjusted WAR) tells a more nuanced story. When adjusting WAR to account for changes in league-wide competition over time, Soto’s projected value appears above the regression line, suggesting he may be slightly overpaid on an era-relative basis. This discrepancy reflects how eWAR compresses differences between eras, elevating past performances while slightly dampening the perceived dominance of current players.

Ultimately, these charts illustrate a key philosophical point: the way we evaluate contracts depends heavily on the lens we use. Raw WAR favors Soto in the present, while eWAR forces us to contextualize his output more historically. Still, whether by traditional or adjusted metrics, Soto stands out as an elite player — and the Mets’ investment isn’t just financial, but symbolic. It’s a bet on sustained excellence and a belief that Soto will be remembered as one of the defining players of his generation.

That’s where era-adjusted WAR (eWAR) introduces a new dimension. Players like Soto and Judge, while perhaps shy of all-time greats in traditional WAR, are elite by era-adjusted standards—often outperforming the average competition by historic margins. This raises an important philosophical question: if we judged contracts by eWAR instead of raw numbers, would we redefine what makes a contract “worth it”? Would modern greats like Soto gain the legacy recognition typically reserved for past legends?

Ultimately, Soto’s deal reflects not just the Mets’ belief in his current value, but their investment in his continued greatness—and perhaps even his place in baseball history. Whether evaluated through traditional metrics or modern adjustments, one thing is clear: Soto’s contract isn’t just a bet on talent. It’s a bet on him becoming a generational icon.

References

Major League Baseball. (n.d.). Competitive balance tax. MLB.com. Retrieved from https://www.mlb.com/glossary/transactions/competitive-balance-tax

Paraball Notes. (2024). Dollar/WAR in the 2024–2025 MLB free agency market. Retrieved from https://www.paraballnotes.com/blog/dollarwar-in-the-20242025-mlb-free-agency-market

TangoTiger. (n.d.). Stud0346. Retrieved from https://www.tangotiger.net/archives/stud0346.shtml

Baseball Reference. (n.d.). Baseball statistics and history. Retrieved from https://www.baseball-reference.com/

Eck, D. J., Yan, S., Burgos Jr., A., & Kinson, C. (n.d.). The Full House Model for cross-era comparisons of baseball players (Results and fun digressions version 2.0). University of Illinois Urbana-Champaign. Retrieved May 3, 2025, from https://eckeraadjustment.web.illinois.edu/era_adjusted_V2_I.html

Yan, S., Burgos Jr., A., Kinson, C., & Eck, D. J. (n.d.). Estimation of the MLB talent pool: Supplement to Comparing baseball players across eras via novel Full House Modeling. University of Illinois Urbana-Champaign. Retrieved May 3, 2025, from https://eckeraadjustment.web.illinois.edu/MLBeligiblepop.html

Yan, S., Burgos Jr., A., Kinson, C., & Eck, D. J. (2022). Comparing baseball players across eras via novel Full House Modeling (arXiv:2207.11332). arXiv. https://arxiv.org/abs/2207.11332

Acknowledgements

Thank you to Professor Daniel J. Eck, the University of Illinois, URES, the statistics department, my fellow undergraduate researchers Mohit Singh and Zheer Whang, and the entire Eck MLB Era-adjustment lab for allowing me to write this piece.