During the 2018 MLB regular season, 75 pitchers combined to earn $203,818,000 million dollars in salary. $139,415,000 million dollars of the salary was never truly earned by the 75 pitchers because they were unable to pitch due to a throwing related injury. A similar scenario happens each year, and when it comes to running a business, MLB Organizations continue to pay for MLB pitchers who are unable to fulfill 100% of their contract demands.. Can any of the unfulfilled contracts be avoided or managed differently?
Delivery Value System (DVS) completed a major data re-collection and database expansion in the Fall of 2018. This expansion increased the number of professional and college pitchers in our database to over 1200, including every MLB pitcher on an opening day 2018 roster. With the recent database expansion, the DVS Model continues to prove a pitcher’s mechanics significantly influence their time to a major injury.
In this article, we provide a complete summary of all the data that was collected from over 50 professional pitchers throughout the course of the Inaugural USPBL season. Our hypothesis was that as pitchers spent more time exposed to the DVS Arm Care System, The USPBL Throwing Program, and our pitching methodology that is designed to improve a DVS Score, their Shoulder Range-of-Motion Patterns would become less injurious.
The probability of injury occurring to a MLB Pitcher in future inning totals is now available to MLB Organizations looking to make short and long-term decisions regarding the value of their MLB pitcher. As part of Delivery Value System’s ongoing research to combat the rising injury trends among MLB pitchers within baseball, DVS created the DVS Forecaster, which encapsulates the power of the DVS Model into web-based software. The DVS Forecaster can be accessed on-demand by any MLB organization, and will be made available to MLB Organizations through an annual licensed subscription.
Baseball pitching imposes significant stress on the upper extremity and can lead to injury. Many studies have attempted to predict injury through pitching mechanics, most of which have used laboratory setups that are often not practical for population-based analysis. Read about how our initial study sought to predict injury risk in professional baseball pitchers using a statistical model based on video analysis evaluating delivery mechanics in a large population.