Forecasting Performance Escalation in Junior Male Tennis: A Bayesian Analysis of ITF Ranking Thresholds (2004–2024)
| Authors | |
|---|---|
| Year of publication | 2025 |
| Type | Appeared in Conference without Proceedings |
| Citation | |
| Description | This study was conducted to examine long-term developments in performance standards among junior male tennis players competing in the ITF World Tennis Tour Juniors from 2004 to 2024. Percentile-based thresholds (P90, P75, P50) were determined using binary logistic regression and forecasted via a Bayesian time-series model (Prophet). A sample of 8,082 players was analysed to estimate annual cut-off values and project future trajectories. Fourteen changepoints were detected in each performance tier, indicating repeated structural adjustments and confirming a non-stationary competitive environment. An exponential upward trend in performance thresholds, expressed in ITF year-end ranking points, was observed, with R2 values ranging from .811 to .835. Over the research period, the P50 cut-off rose 2.50 times, from 352.3 points in 2004 to 880.8 in 2024, while the P90 threshold increased by 2.67 times, from 572.3 to 1537.4. Year-over-year growth rates reached 21.9% for P90 and 18.5% for P50 thresholds. Analysis of Year-end Ranking 2024 further revealed that higher-ranked players participated in fewer tournaments (singles and doubles) but demonstrated greater efficiency in those events. According to the Prophet model forecasts, cut-off values are expected to reach 1766 points for P90, 1546 for P75, and 1013 for P50 by 2029. Forecasting parameters further supported sustained growth in performance standards across all tiers. To maintain 2024's efficiency, juniors would need to participate in 3.3 (P90) to 4.4 (P50) tournaments per season to achieve higher rankings strata by 2029. These findings highlight the necessity for adaptive, data-informed strategies in talent development, tournament scheduling, and performance benchmarking. By integrating historical ranking data with predictive modelling, the study offers practical tools for coaches, players, and federations to navigate a dynamically evolving junior tennis landscape. |