Every baseball family wonders where their player really stands. DiamondEdge AI answers that question with data. Our ML model — trained on 23 years of NCAA draft outcomes — predicts advancement probability, benchmarks players against real draft picks, and generates an AI scouting report with specific improvement targets. Validated against 2024 MLB draft results. Built for coaches, scouts, and baseball families.
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Maker
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Built this as a baseball dad who got tired of guessing. I started with 23 years of NCAA draft outcomes and built a machine learning model that predicts advancement probability for amateur baseball players at any level. Then I validated it against real 2024 MLB draft picks. Nick Kurtz, drafted 4th overall by the Oakland Athletics, scored 93%. Players who went undrafted scored significantly lower. The model works.
What DiamondEdge AI gives you that nothing else does at the amateur level is an advancement probability score, a percentile benchmark showing exactly how your player compares to players who actually got drafted stat by stat, and an AI scouting report with specific improvement targets.
Beta access is completely free right now. If you are a coach, scout, travel ball organization, or baseball family I would love your feedback. Happy to answer any questions about the model, the data, or the product.