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

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

21 Oct 2019arXiv:1910.12622archive 2025-07-28

Jacob Danovitch

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.

PaperPDFCode

Code

jacobdanovitch/Trouble-With-The-Curve officialmentioned in paperpytorch report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

Articles

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections