Projections from Public Data and the 2026 Rebound of KBO Hitter Won-jun Choi

Clubs that sign hitters coming off poor seasons hope to find rebounds that public projections miss. In 2025 Won-jun Choi, an outfielder in the Korea Baseball Organization (KBO), batted .242 with a .289 on-base percentage (OBP). He then signed with KT as a free agent and in 2026 batted .356 with a .434 OBP (weighted runs created plus, wRC+, 154; league average 100). Using full-league pitch-by-pitch records, with the information set fixed at the signing date, we ask what a screen built from public data would and would not have seen. Pre-specified player-specific projections put his 2026 OBP at .316-.332, below the 2025 league OBP of .339. A state-space talent model put his 2026 talent near wRC+ 89, and pitch-level discipline features added no detectable predictive value. Among 11 hitters who slumped in 2025, he ranked last by projected level but joint first by projected bounce (projected minus 2025 OBP), as expected for the hitter with the lowest 2025 OBP. His slump combined the group's largest drop in walk rate with a mid-sized drop in batting average on balls in play (BABIP). In this cohort and the previous year's, no other slumper with next-season data rebounded by more than +.038 in OBP; Choi rebounded by +.145. His 2026 residual was the largest of 195 hitter transitions in 2023-2026. At the maximum-likelihood persistence, the 65-point gap between the signing-time forecast and his actual wRC+ splits into about 29 points of talent that the record through 2025 did not reveal (95% interval [11, 47]) and 36 points of variance. Across all models, 25-35 of his 208 hits exceeded estimated talent. The case was selected after the fact, and the analysis does not identify a causal effect of the transfer.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-03
DOI
https://doi.org/10.5281/zenodo.23910880
Primary Topic
Sports Analytics and Performance
Type
preprint
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preprint

Projections from Public Data and the 2026 Rebound of KBO Hitter Won-jun Choi

Woomin Jeong
Zenodo (CERN European Organization for Nuclear Research)
Sports Analytics and Performance
preprint

Projections from Public Data and the 2026 Rebound of KBO Hitter Won-jun Choi

Woomin Jeong
preprint en

Abstract

Clubs that sign hitters coming off poor seasons hope to find rebounds that public projections miss. In 2025 Won-jun Choi, an outfielder in the Korea Baseball Organization (KBO), batted .242 with a .289 on-base percentage (OBP). He then signed with KT as a free agent and in 2026 batted .356 with a .434 OBP (weighted runs created plus, wRC+, 154; league average 100). Using full-league pitch-by-pitch records, with the information set fixed at the signing date, we ask what a screen built from public data would and would not have seen. Pre-specified player-specific projections put his 2026 OBP at .316-.332, below the 2025 league OBP of .339. A state-space talent model put his 2026 talent near wRC+ 89, and pitch-level discipline features added no detectable predictive value. Among 11 hitters who slumped in 2025, he ranked last by projected level but joint first by projected bounce (projected minus 2025 OBP), as expected for the hitter with the lowest 2025 OBP. His slump combined the group's largest drop in walk rate with a mid-sized drop in batting average on balls in play (BABIP). In this cohort and the previous year's, no other slumper with next-season data rebounded by more than +.038 in OBP; Choi rebounded by +.145. His 2026 residual was the largest of 195 hitter transitions in 2023-2026. At the maximum-likelihood persistence, the 65-point gap between the signing-time forecast and his actual wRC+ splits into about 29 points of talent that the record through 2025 did not reveal (95% interval [11, 47]) and 36 points of variance. Across all models, 25-35 of his 208 hits exceeded estimated talent. The case was selected after the fact, and the analysis does not identify a causal effect of the transfer.

Zenodo (CERN European Organization for Nuclear Research)
Sports Analytics and Performance
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