DingerZone vs Hit or Not

DingerZone empowers youth baseball players to perfect their swing with cutting-edge AI and personalized coaching. Designed for players, parents, and coaches, our app combines computer vision, expert analysis, and team collaboration to elevate performance on the diamond. Key Features: AI Swing Analysis: Upload swing videos to receive instant, detailed feedback powered by advanced computer vision. Get actionable insights on form, mechanics, and recommended drills to boost performance. Player Profiles: Parents can create accounts and add child players, managing their swing videos and progress in one secure place. Team Collaboration: Players can join teams, allowing coaches to access videos for a set time, fostering targeted feedback and team improvement. Personalized Drills: Receive tailored drill recommendations based on AI analysis to address specific areas of improvement. Secure Subscriptions: Manage subscriptions seamlessly with Stripe, unlocking premium features like unlimited video uploads and advanced analytics. User-Friendly Design: Built with React Native for a smooth, intuitive experience on iOS devices. Whether you’re a young athlete aiming for the next level, a parent tracking your child’s progress, or a coach guiding a team, DingerZone delivers the tools to succeed. Our AWS-powered backend ensures fast, reliable video processing and secure data storage, so you can focus on the game. Download DingerZone today and start swinging for the fences!

The Hit or Not app is designed to contribute to coach, player, and fan evaluations of plate appearances (PA) in baseball. The app also works great for batting cage competitions. To make this app work, I take all available data from the 2023-2026 NCAA Division 1 baseball seasons, and 2022-2026 MLB seasons.For each 1 mph increment in exit velocity (EV) and 1° increment in launch angle (LA), I count all instances of outs, singles (1b), doubles (2b), triples (3b) and home runs (hr). The user also has the option to select an outfield direction for the hit. I do not provide the option to choose an infield direction, because NCAA data for hit direction on ground balls is too inaccurate. When the user selects 'MLB', they can make an additional choice to evaluate hits in any of the 30 MLB parks. With these counts based on user input of League, hit Direction, Park, EV, and LA, I compute the mean batting average (AVG) and slugging percentage (SLG). These values of AVG and SLG are equivalent to 'expected stats (xBA or xSLG) for balls in play (not including strikeouts). For both counts and percentages, I apply 9-cell neighborhood averaging around each {EV,LA} pair to account for the average Trackman/Hawkeye errors in EV and LA observations. Similarly, the hit Direction bins are sampled with 5° overlap. When the user taps the 'Calculate' button, the app selects randomly from the distribution of out, 1b, 2b, 3b, and hr counts and displays an outcome that simulates some of the randomness in baseball, while respecting the statistics of the user's inputs for League, hit Direction, Park, EV, and LA. The user can tap the 'Calculate' button as many times as they like, with each tap representing a reroll of the dice. We often use this feature when players or coaches challenge a HitOrNot result during an indoor scrimmage. The heat map screen takes the same data used in the dashboard, and plots the user selected grid as a heatmap. This tool allows users to interrogate the differences in {EV,LA} outcomes for different Leagues, hit Directions, and Parks. The about screen allows users to update the data in the map to the most recent week of NCAA and MLB play. Thank you to Joe Haumacher, Kyle Bonicki, Scott Bradley, and the Princeton University Baseball Team.