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