Introduction to Stuff+

Baseball is a sport that adopted the use of Data and Analytics prior to almost any major sport in America. The famous movie and book "Moneyball," does a good job depicting the Oakland Atheltics and President of Baseball Operations Billy Beane and his adoption of analytics in the modern game of baseball. The edges that were exploited back then using analytics are nowhere to be found in the modern game as they have been priced out, however there is always innovation in the sport, and recently the adoption of stuff+ models being used to evaluate pitchers at the highest level. With the introduction of Hawkeye and Edgertronic Cameras in the sport, teams are able to acquire even more data. These high speed cameras allow teams access to finite data points, showing more than just a pitches velocity, but also tracking its movement and flight profiles. Access to a pitches horizontal movement, induced vertical movement, release height, distance from the plate the pitch is released (effective velocity) are all variables that can be evaluated toward determining whether or not a pitch is affective or not. Previous evaluation techniques were limited toward outcomes based on what occurred during an at bat. Moving to a per individual pitch evaluation method is superiors in a few ways. Firstly, there are many more data points to evaluate from. An individual at bat in 2018 averaged 3.89 pitcher per plate appearance, whereas evaluating based off an individual pitches characteristics will give you more data points at a 1:3.89 ratio. More data means more actionable trends for organizations to use in a shorter period of time, and being ahead of the rest of the league in evaluation is a key to an organizations success. The other advantage to this is the amount of luck thats involved in the sport meaning evaluation on the outcome of an individual at bat may stabilize even later due to outlier outcomes in the sample. For example a batter could go 4 for 4 on a day and not hit one baseball hard yet luck out on hits finding holes in the defense. On the other hand, a batter could have 0 hits on the day yet hit every ball over 100mph. This is an extreme outcome on either end of the spectrum however it illustrates the volatility on making conclusions based on the outcome of an at bat when you can make determinations on the quality of each individual pitch. This is where stuff+ models come into play and why they are revolutionizing the way we evaluate pitchers at any level.