Unified Pitch Graphs for Diagnosing Pitching Strategy

Kichang Lee; JeongGil Ko

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arXiv · 2609.03810

Unified Pitch Graphs for Diagnosing Pitching Strategy

Kichang Lee·JeongGil Ko

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Abstract

Pitching strategy in baseball is expressed through both physical execution and the ordered context in which pitches are used, yet common representations collapse pitches into discrete types or aggregate statistics. We present Unified Pitch Graphs (UPG), a hierarchical graph representation for retrospective analysis of sequential spatiotemporal events. UPG preserves each pitch as an exact event with reconstructed three-dimensional trajectory and context, connects consecutive pitches through directed sequence edges, and organizes the same events across semantic and temporal resolutions. A support-adaptive mechanism backs off from fine, long sequences when repeated evidence is insufficient, while retaining exact event lineage. We evaluate UPG on 3.94 million MLB Statcast pitches from 2021 to 2026. Nominally identical pitch sequences exhibit distinct physical executions, and ordered structure becomes increasingly evident in longer context-conditioned paths. Support-adaptive backoff increases held-out path coverage from 18.9\% to 94.9\% while improving execution reconstruction from $R^2=0.495$ to $0.685$. UPG also reliably localizes controlled execution changes that discrete pitch-mix and sequence representations cannot detect. These results demonstrate that UPG provides a traceable, multi-scale representation for identifying recurring strategy patterns without conflating retrospective associations with causal or future-performance claims.

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Kichang Lee, JeongGil Ko. 2026-09-03. Unified Pitch Graphs for Diagnosing Pitching Strategy. https://arxiv.org/abs/2609.03810

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