Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 53 min ago
Peer-reviewedCC BY 4.0PLOS One

Prioritizing next-day readiness decline in elite female soccer using readiness, workload, and wellness data: A temporally validated and calibrated monitoring framework

  1. 1Chengdu Sport University, Chengdu, China

Abstract

Daily athlete monitoring is widely used in elite soccer, but its value depends on whether routine data can help identify athlete-days more likely to be followed by self-reported next-day readiness decline. This retrospective study evaluated a temporally validated and calibrated model for prioritizing staff-review attention in elite female soccer. Using SoccerMon data, we analyzed 14,428 eligible athlete-days from 50 players. The outcome was same-athlete next-calendar-day self-reported readiness decline ≥0.5 athlete-specific SD calculated from at least five observed readiness values strictly before the index date. Models were trained in 2020 and evaluated in a held-out 2021 test set. Adding workload and wellness to readiness improved discrimination (Model 4 vs Model 0: AUC 0.7645 vs 0.7043; PR-AUC 0.5135 vs 0.3808); paired athlete-level bootstrap ΔAUC was 0.0592 (95% CI 0.0288–0.0891). Platt recalibration reduced Brier score from 0.1924 to 0.1460 without changing ranking. Reviewing the top 20% (1,672 athlete-days) captured 881 events (46.1%) versus 36.4% for Model 0. These retrospective results support cautious staff-review prioritization rather than demonstrated improvement in athlete management or performance, and prospective implementation testing and independent external validation are required before real-world use.

Related

  1. Temporally Validated and Laboratory-Reconciled Soft Sensing of Xylene-Soluble Fraction in Industrial Polypropylene Manufacturing
    Joaquín Hernández-Fernández
    PolymersPeer-reviewedCC BYFull textMaterials & polymersEurope PMCCrossref
  2. PCAN-PIE: A Machine Learning Tool for Prioritizing Prodrug Candidates by Predicted Bioactivation
    Chloe Markey, Zachary Fralish, Hannah Lee +1
    ChemRxivPreprintCC BYFull textGeneral chemistryChemRxiv
  3. Temporally decoupled electrochemiluminescence breaks the sensitivity–portability tradeoff in water toxicity sensing
    Chuan Huang, Dan Han, Hong Yang +4
    ChemRxivPreprintCC BYFull textElectrochemistry & energyChemRxiv
  4. Emergence of Temporally Irreversible Hierarchical Solid Patterns through Information-Bearing Field Evolution and History-Dependent Growth Arrest
    Junhyung Lee
    ChemRxivPreprintCC BY-NC-NDFull textGeneral chemistryChemRxiv
  5. Physics-Guided Learning with Calibrated Uncertainty for Molecular Thermodynamics Beyond Observed Chemical Space
    Yi-Cheng Shen, Shu Wang, Shiang-Tai Lin
    ChemRxivPreprintLicence not statedGeneral chemistryChemRxiv
BibTeX
@article{long2026prioritizing,
  title = {{Prioritizing next-day readiness decline in elite female soccer using readiness, workload, and wellness data: A temporally validated and calibrated monitoring framework}},
  author = {Haojie Long and Longji Li and Lifeng Zhang},
  journal = {PLOS One},
  year = {2026},
  month = sep,
  doi = {10.1371/journal.pone.0358036},
  url = {https://doi.org/10.1371/journal.pone.0358036},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Prioritizing next-day readiness decline in elite female soccer using readiness, workload, and wellness data: A temporally validated and calibrated monitoring framework
AU  - Haojie Long
AU  - Longji Li
AU  - Lifeng Zhang
PY  - 2026
DA  - 2026/09/10
JO  - PLOS One
DO  - 10.1371/journal.pone.0358036
UR  - https://doi.org/10.1371/journal.pone.0358036
AB  - Daily athlete monitoring is widely used in elite soccer, but its value depends on whether routine data can help identify athlete-days more likely to be followed by self-reported next-day readiness decline. This retrospective study evaluated a temporally validated and calibrated model for prioritizing staff-review attention in elite female soccer. Using SoccerMon data, we analyzed 14,428 eligible athlete-days from 50 players. The outcome was same-athlete next-calendar-day self-reported readiness decline ≥0.5 athlete-specific SD calculated from at least five observed readiness values strictly before the index date. Models were trained in 2020 and evaluated in a held-out 2021 test set. Adding workload and wellness to readiness improved discrimination (Model 4 vs Model 0: AUC 0.7645 vs 0.7043; PR-AUC 0.5135 vs 0.3808); paired athlete-level bootstrap ΔAUC was 0.0592 (95% CI 0.0288–0.0891). Platt recalibration reduced Brier score from 0.1924 to 0.1460 without changing ranking. Reviewing the top 20% (1,672 athlete-days) captured 881 events (46.1%) versus 36.4% for Model 0. These retrospective results support cautious staff-review prioritization rather than demonstrated improvement in athlete management or performance, and prospective implementation testing and independent external validation are required before real-world use.
SN  - 1932-6203
ER  -