In this episode, Jack, Josh & Marek explore the evolution of pitch modeling in baseball, covering key metrics like 'Stuff' and the shift to component-based approaches. They discuss how advanced models predict pitching success and how insights can be applied to both pitchers and hitters. The conversation also touches on the 'Big 3' of hitting analysis, the development of a matchup model tailored to hitters, and the limitations of current models, emphasizing the need for continuous improvement in player evaluation. This podcast offers a unique look into how Driveline combines research, analytics, and practical application under one roof to push baseball development forward. Whether you're a player, coach, or analytics enthusiast, you'll gain insights into the future of baseball training and performance.

0:00 Introduction to Pitch Modeling 3:33 Understanding Pitch Modeling Basics 6:00 Historical Context and Evolution of Pitch Modeling 6:58 The Value of Stuff and Quick Reliability 11:18 Component-Based Approach to Pitch Modeling 20:04 Philosophical Shift in Pitch Analysis 22:24 Optimization and Decision-Making in Pitching 24:04 Valuing Hitters and Pitchers Equally 28:00 The Big Three in Hitting Analysis 30:14 Understanding Swing Decisions and Run Values 33:55 Individualizing Swing Decisions for Hitters 37:00 The Matchup Model: Tailoring Pitch Values to Hitters 44:02 Pitch Physics and Its Impact on Modeling 52:45 Recognizing Model Limitations and Future Directions