Age-Related Stamina Curve

Overview

This pillar analyzes historical performance degradation in classical chess tournaments, specifically contrasting players over 35 against rising juniors in late-stage rounds. It identifies profitable trading opportunities where cumulative fatigue causes calculation errors that markets overlook.

What It Does

It segments tournament performance into early and late phases, tracking Average Centipawn Loss (ACPL) and blunder rates as the event progresses. By correlating age with accuracy dips in moves 40+ and rounds 9+, it creates a dynamic 'Stamina Coefficient' for specific matchups.

Why It Matters

Prediction markets often price matches based on static Elo ratings, ignoring the physiological toll of multi-week events. Older players typically suffer a measurable decline in precision during the final days, creating a statistically significant edge for bettors backing younger opponents.

How It Works

The system ingests PGN data from Super GM tournaments, filtering for games lasting over 4 hours. It compares a player's baseline accuracy against their performance in the final third of a tournament schedule, adjusting for rest days.

Methodology

Uses Stockfish evaluations to calculate ACPL (Average Centipawn Loss) deltas. Formula compares `Metric_Early (Rounds 1-4)` vs `Metric_Late (Rounds 9+)`. Applies an `Age_Decay` weight for players >35, specifically in games following rounds that exceeded 50 moves.

Edge & Advantage

Provides a distinct edge in 'Round 10+' betting scenarios by fading aging favorites who are statistically likely to blunder due to exhaustion.

Key Indicators

• Late-Round ACPL Delta

  high

  The increase in engine error rate in the final 30% of a tournament

• Marathon Recovery Factor

  medium

  Performance drop in games immediately following a 5+ hour match

• Time Trouble Blunder Rate

  high

  Frequency of errors committed when clock is under 5 minutes

Data Sources

• The Week in Chess (TWIC)

  Comprehensive database of historical tournament PGNs

• Lichess Opening Explorer

  Granular move time and accuracy data

Example Questions This Pillar Answers

• → Who will win the Round 13 match: Carlsen vs Nakamura?
• → Will the FIDE Candidates Tournament winner be under 25 years old?
• → Will Player X commit a blunder (200+ cp loss) in the final round?

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