Welcome to my MLB article! Here I will take a data-driven approach to Baseball as it pertains to both Pitchers and Hitters alike.
I’ll be using an evaluation system that I developed over the last couple months with the goal of producing the most actionable advice possible with the help of macro and micro analytics! There’s a whole bunch of math going on, but it is all for a good cause, I promise.
As you read through this beautiful piece of work, keep in mind that MLB is a sport that thrives on variance. My article is based mostly around GPP thoughts and pivots looking to avoid the chalk and succeed when others fail.
First off, I’ll need to give a little information about my evaluator, the data points on which it reads, and how the eventual grades are derived. The entire thing is based in Microsoft Excel, using data found on FanGraphs, so literally anyone could build it (if you have more free time than you know what to do with, that is). It uses a complex set of formulas and equations to build into master sheets, which are populated with daily information, and sent to another page for daily use.
The Pitcher grades are developed for each individual pitcher, and the Stack grades are developed for each stack of 4 hitters in order on a team. The Stacks are as follows:
- ARI1 (The first 4 batters in the lineup for Arizona)
- CIN2 (The 3-6 batters in the lineup for Cincinnati)
- MIL3 (the 5-8 batters in the lineup for Milwaukee)
Each stack will have its own grade depending on how the variables shake out in the specific matchup. Speaking of variables, for Pitchers, we are dealing with 14 separate weighted variables, while Hitters run 15 separate weighted variables. The overlapping variables are as follow:
- Stadium (Where the game is played)
- Avg (The pitcher’s allowed hitting average)
- WHIP (Walks, Hits per Inning Pitched)
- GB% (The pitcher’s groundball percentage)
- HH% (The pitchers allowed Hard Hit percentage)
- HR/9 (How many HR’s the pitcher allows per 9 innings)
- K/9 (How many strikeouts the pitcher gets per 9 innings)
- wRC+ vs L (Offensive value against Lefties)
- wRC+ vs R (Offensive value against Righties)
- Team LD% (The average of a stack’s Line Drive percentage)
- Team HH% (The average of a stack’s Hard Hit percentage)
- SO% vs L (The average of a stack’s Strikeout percentage to Lefties)
- SO% vs R (The average of a stack’s Strikeout percentage to Righties)
- Total (The implied runs total for a stack)
For Hitters, we have an extra variable in Home/Away, since Away teams are guaranteed a chance at bat in the 9th inning and Home teams are not. These variables have been chosen because I believe they are actionable and show true value when deciding on where to attack in DFS. Each one is weighted with values of 3, 5, and 10 points (depending on importance and percentile) which adds up to 100. The grade that each Pitcher or Hitting Stack gets is then displayed using a formula that adds all those variables up!
Now that we have all the verbiage out of the way, let’s get down to business…