{"version":"1.0","type":"rich","provider_name":"Acast","provider_url":"https://acast.com","height":250,"width":700,"html":"<iframe src=\"https://embed.acast.com/$/5b69f70c0a0eca0c20692176/6a72bdbd35f6dd01fb07101b?\" frameBorder=\"0\" width=\"700\" height=\"250\"></iframe>","title":"Why Pitch Counts Are Failing Baseball","thumbnail_width":200,"thumbnail_height":200,"thumbnail_url":"https://open-images.acast.com/shows/5b69f70c0a0eca0c20692176/1785904504481-dee078dc-6f40-48dd-8897-72bd44b0d022.jpeg?height=200","description":"<p>What if baseball’s most trusted pitching limit is more habit than science?</p><p><br></p><p> Travis Sawchik, baseball analytics writer and author of <em>Big Data Baseball</em> and <em>The MVP Machine</em>, breaks down why pitch counts can miss the real stress on a pitcher’s arm, how workload units and acute-to-chronic ratios offer a better view of fatigue, and why teams may need to rethink how they build pitching capacity.</p><p><br></p><p>The conversation also covers MLB trade deadline strategy, the Dodgers’ title odds, the Brewers’ risk calculus, when teams should chase variance instead of average gains, Baker Mayfield’s recent production compared with Patrick Mahomes, the Ravens’ coaching changes, Saquon Barkley’s workload, and college football playoff storylines.</p>","author_name":"The Wharton School"}