Written By: Luke Smailes

Last Spring, we debuted Weighted Wins Above Average (wWAA) in conjunction with our partners at D1 Baseball/D1 Softball. wWAA takes hitting and baserunning production for position players and pitching production for pitchers and scales those components by the quality of opponent that each player played against. That total production, which is originally displayed in terms of runs, is compared to the production of the average D1 player before finally being converted to wins.

By using the Pythagenpat formula, which is a modified version of Bill James’ Pythagorean formula, we can derive that a win in D1 baseball is worth 12.3 runs while a win in D1 softball is worth 11.9 runs. This formula creates a scalar to go from runs above average (or above replacement) to wins above average (or above replacement) very easily.

Then, last month, we debuted Defensive Runs Saved (DRS) for college baseball and softball, and this gave us a defensive measurement, conveniently displayed in terms of runs, to add to wWAA to make it much more comprehensive. We did this, but we also changed how we’re displaying a player’s total production, moving from “above average” to “above replacement”. 

In Major League Baseball analysis, Wins Above Replacement (WAR) has become the most popular metric that attempts to boil a player’s total contribution (including hitting, baserunning, defense, and pitching) to his team in a single value. Rather than compare players to the average player in MLB, the metric, which is most prominently calculated by FanGraphs (fWAR), Baseball Reference (bWAR), and Baseball Prospectus (WARP), compares each player to the theoretical “replacement-level” player. The idea is to measure how much more (or less) productive the player is compared to the player that would be “readily available” to replace them, which for the purposes of MLB, is something like a Triple-A player. 

With wWAA, a lot of the work to construct had already been done. The mechanics of the hitting, baserunning, and pitching components don’t change, but with WAR we’re adding fielding (DRS) and comparing each collegiate player to replacement level. 

So, what exactly is replacement level in D1 baseball & softball? It’s not an objective calculation. FanGraphs believes that a team full of “freely available” players would win 29.7% of their games, or about 48 per each 162-game MLB regular season. Our approach wasn’t to theorize what a full team of replacement level players would produce before working backwards to calculate what that looks like at the player level. Rather we theorized that a replacement level player in college baseball and softball is someone who plays no more than one quarter of their team’s games in a season. These are players who have established themselves as D1 players, yet still sat on the bench for at least three quarters of their team’s season. Though not always true for all teams and situations, the assumption is that had these players performed better in their small samples of opportunity, they would have played more and thus not wound up in this bucket of players. 

In D1 baseball, 25% of a team’s season was 14 games on average, while in softball that total was 13 games, and these become our cutoff points.

To provide some additional context, these players hit .191/.305/.277 with a .285 wOBA and pitched to a 6.64 FIP in D1 baseball. In D1 softball, they hit .156/.247/.203 with a .221 wOBA and pitched to a 5.19 FIP. For the average D1 team, this is the kind of production that’s available on the bench, and thus becomes how a replacement level player is represented empirically. 

Let’s take a look at what this concept looks like in practice. Here’s the 2023 WAR overall leaders starting with baseball. Note that oWAR is offensive WAR, dWAR is defensive WAR, and pWAR is pitching WAR.

D1 Baseball 2023
Rank Player School Pos oWAR dWAR pWAR WAR
1 Dylan Crews LSU CF 6.8 0.3 0 7.1
2 Jac Caglianone Florida 1B/P 4.4 0 2.6 7.0
3 Nolan Schanuel Florida Atlantic 1B 6.4 0.1 0 6.5
4 Caden Grice Clemson 1B/P 3.3 0.3 2.7 6.3
5 Brock Wilken Wake Forest 3B 5.8 0.5 0 6.3
6 Paul Skenes LSU P 0 0 6.2 6.2
7 Wyatt Langford Florida LF 5.7 0.4 0 6.1
8 Kyle Teel Virginia C 4.4 1.4 0 5.8
9 J.J. Wetherholt West Virginia 2B 5 0.7 0 5.7
10 Cam Fisher Charlotte RF 5.4 0.1 0 5.5

 

We see that LSU ace and #1 overall pick Paul Skenes is the sole pitcher-only to crack the top-10, but two-way players Jac Caglianone and Olerud winner Caden Grice also saw time on the mound.

Let’s drill down to highlight some of the top arms of 2023:

D1 Baseball 2023
Rank Player School WAR
1 Paul Skenes LSU 6.2
2 Rhett Lowder Wake Forest 4.8
3 Tanner Hall Southern Miss 4.4
4 Nico Zeglin Long Beach State 4.3
5 Seth Keener Wake Forest 3.9
6 Diego Barrera Loyola Marymount 3.8
7 Grant Rogers McNeese 3.7
8 Matt Ager UC Santa Barbara 3.6
9 Luke Holman Alabama 3.6
10 Brandon Sproat Florida 3.4

 

In D1 softball, Valerie Cagle raked in multiple player of the year awards (D1 and USA Softball), and for good reason. WAR really does a nice job of putting her season in perspective. 

D1 Softball 2023
Rank Player School Pos oWAR dWAR pWAR WAR
1 Valerie Cagle Clemson 1B/P 5.8 0.3 7.2 13.3
2 Montana Fouts Alabama P 0 0 9.4 9.4
3 Maddie Penta Auburn P 0 0 8.6 8.6
4 Kiki Milloy Tennessee CF 7.2 0.5 0 7.7
5 Kathryn Sandercock Florida State P 0 0 7.7 7.7
6 Kayla Beaver Central Arkansas P 0 0 7.4 7.4
7 Taylor Roby Louisville DH/P 4.6 0 2.5 7.1
8 Skylar Wallace Florida SS 6.7 0.3 0 7.0
9 Sydney Nester Marshall P 0 0 6.9 6.9
10 Myka Sutherlin Cal State Fullerton P 0 0 6.6 6.6

 

Had Cagle never picked up a bat, she would have finished with the seventh best overall WAR in 2023. Had she never pitched, she still would have been a top-30 player. Together she was just under four wins better than Montana Fouts, the nation’s second best player. If Clemson swapped Cagle for a replacement level player, the 49-12 Tigers would have theoretically lost 13 more games and finished 36-25.

You can see that given a pitcher’s ability to pitch such a large portion of their team’s innings over the course of a season, they dominate the top-10 in softball. Kiki Milloy and Skylar Wallace are the only two everyday position players to crack the list, while Cagle and Louisville’s Taylor Roby represented the pair of two-way players.

Let’s also isolate D1 softball’s top-10 position players:

D1 Softball 2023
Rank Player School Pos oWAR dWAR WAR
1 Kiki Milloy Tennessee CF 7.2 0.5 7.7
2 Skylar Wallace Florida SS 6.7 0.3 7.0
3 Jayda Coleman Oklahoma CF 6.2 0.3 6.5
4 Taryn Kern Indiana 2B 6.2 0 6.2
5 Erin Coffel Kentucky SS 5.9 0.2 6.2
6 Valerie Cagle Clemson 1B 5.8 0.3 6.1
7 Rachel Becker Oklahoma State 2B 5.5 0.4 5.9
8 Maya Brady UCLA SS 5.5 0.1 5.6
9 Alex Honnold Missouri CF 5.2 0.3 5.5
10 Sydney McKinney Wichita State SS 5.2 0.3 5.5

Note: Cagle’s 6.1 WAR listed here doesn’t include her pitching contribution

An important reminder is that these values are still scaled by strength of schedule, as this feature was carried over from the construction of wWAA. More specifically, it uses RPI to put each player on an even playing field. Because of the talent disparities between all of the 300+ teams in both sports, a characteristic of collegiate baseball and softball that’s not reflected in MLB, it’s one of the main differences in the construction of our version of WAR compared to the metrics leveraged in MLB. 

Wins Above Replacement is certainly not the end all be all when it comes to descriptive stats or metrics for evaluation. Our goal was simply to compose a version of the comprehensive metric that’s been popularized at the MLB level, and bring it to college baseball and softball – adjusting for strength of schedule and finally including defensive components for the first time.