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In baseball, a scouting report profiles a player's characteristics andtraits, usually intended for use in player valuation. This work presents afirst-of-its-kind dataset of almost 10,000 scouting reports for minor league,international, and draft prospects. Compiled from articles posted to MLB.comand Fangraphs.com, each report consists of a written description of the player,numerical grades for several skills, and unique IDs to reference their profileson popular resources like MLB.com, FanGraphs, and Baseball-Reference. With thisdataset, we employ several deep neural networks to predict if minor leagueplayers will make the MLB given their scouting report. We open-source this datato share with the community, and present a web application demonstratinglanguage variations in the reports of successful and unsuccessful prospects.

Trouble with the Curve: Predicting Future MLB Players Using Scouting Reports