MLB Pitching Leaderboard + Expected Stats and Player Raters

Crosby Spencer provides the Dugout with the most in-depth pitching database on the web with a writeup explaining the nine-ways to look at pitchers and why it matters.

When looking at this leaderboard, it is admittedly overwhelming. I created this sheet, and I have been using it for about six years now I even need the color coding and the ability to sort by categories to make full use of it. Over this offseason, the Dynasty Dugout will be putting together a leaderboard that is sortable and updated throughout the season. But, for now, I wanted to allow the Dynasty Dugout community to see this leaderboard that I have found incredibly useful in mathematically spotting potentially undervalued and overvalued players. There is a lot of data here, and I am notoriously known to be long-winded, but I am going to do my best to be abnormally succinct in this article. 

The Process

On October 18, 2023, The Dynasty Dugout posted an article titled “A New Way of Looking at Expected Stats + Leaderboard”, where I explained the importance of using spray charts to accurately produce expected stats, which can be found below.

I take the outcomes of each batted ball event that occurred during a relevant timeframe and the applicable situations to generate expected stats. The timeframe here is the 2022* & 2023 seasons, and the applicable situations include the batter’s handedness, exit velocities, launch angles, the batted ball hit locations, and the player’s Schedule Factors. My Schedule Factors are an amalgamation of my Park Factors by the percentage of games that each player’s team plays in each park. Once all the aforementioned factors and data sets are known, I then run each individual player’s events over the 2022 and 2023 seasons through their current team’s Schedule Factors to generate their expected stats. This is particularly valuable for players who have changed teams, like Luis Castillo, Sonny Gray, Luke Mahle, etc., as we can see two seasons worth (Or more, if desired) of expected outcomes in their current team’s Schedule Factor environment.

*The 2022 batted ball events are manipulated to mirror the restricted shifting environment of 2023.

The SGP Values

My SGP values differ from traditional SGP values as I use the average player’s value at each position instead of the leaguewide replacement level player’s value. This allows the SGP values to be 1. Include position scarcity, and 2. It eliminates the disadvantage of pitchers having two ratio categories that unfairly reduce their values when compared to hitters. My process allows for player values to be fairly compared across positions and across hitting and pitching. This sheet is based on a twelve-team, 5x5 league.

The Color Coding

I use color coding to quickly spot areas of excellence, concern, and possible areas of further investigation. Not all categories use the full spectrum of color coding (I won’t bore you with the reasoning) but there is a tab on the sheet that explains the color meanings. The actual stat categories are in black, and the expected stat categories are in blue. 

The Column Guide- Values

ATV= Actual Total Value (Includes W’s and SV’s)

AKEW= Actual K’s, ERA & WHIP Value (Does not include W’s and SV’s)

pATV= Prorated (33 Starts) Actual Total Value (Includes W’s and SV’s)

pAKEW= Prorated (33 Starts) Actual K’s, ERA & WHIP Value (Does not include W’s and SV’s)

xTV= Expected Total Value (Includes W’s and SV’s)

xKEW= Expected K’s, ERA & WHIP value (Does not include W’s and SV’s)

pxTV= Prorated (33 Starts) Expected Total Value (Includes W’s and SV’s)

pxKEW= Prorated (33 Starts) Expected K’s, ERA & WHIP Value (Does not include W’s and SV’s)

xbfVAL= This my personal Expected per Batter Faced Value equation which is an expansion of K%-BB%, to include expected H% and expected HR%

This leaderboard is like having nine-player raters. The typical player rater just has the total value of the pitcher (That is how this leaderboard is sorted). However, taking the 2022 season as an example, you could find what the value of Kyle Wright and Julio Urias was when their inflated win totals were not included; that value can be found in the AKEW column.

The xKEW, pxKEW, and xbfVAL are the best tools to judge a pitcher’s values and skills. The xKEW shows the expected value of the pitcher’s K’s, ERA, and WHIP SGP’s. The pxKEW is the same as xKEW, but the SGP values are based on a prorated thirty-three start season. xbfVAL is a per batter-faced equation that is like, but more involved than, the K%-BB%. I find this helpful when looking at pitchers that have been used as spot starters, in long relief, and or have a small sample size. The long relief players can be found in the SM (Swing Man) tab, and the small sample size players (Less than one hundred batters faced over the last two seasons) can be found towards the bottom of the player tabs. I have the swingmen and small sample players sorted by xbfVAL. While we cannot assume that a player will be as effective in a starting role as they were in long relief the xbfVAL at least gives us a combined skills number to compare them to traditional starting pitchers. The xbfVAL can also help a little with small sample size players but a dive into their minor league history is warranted and necessary. 

Summary

As I wrote earlier, there is a lot of information here, and I have thrown out a number of unfamiliar terms and methods of valuing players at you. Rather than rambling on and further inundating you with information I will just make myself available for any questions. In the coming days, I will post a new hitting leaderboard along with a similar explanation.