Analyze distance strategy and the thresholds between attacking and playing safe.
Stock distance—the yardage you can rely on—is the foundation of score strategy.
This dashboard visualizes four research areas for an AI-driven golf strategy model: how existing research, theory, and tools define and implement distance benchmarks, dispersion–putting causality, attack/defense thresholds, and amateur-specific models.
Whether concepts like Expected Distance and Stock Distance are established as strategy metrics.
Hypothesis: Not max distance but repeatable Stock Distance is the foundation of score strategy.
Quantitative analysis treating putting as an outcome variable.
Focus: How second-shot distance variance ties to first-putt distance and three-putt rate.
How tools (DECADE, Arccos, etc.) and theory implement a clear line.
Simulation: Many frameworks say “inside X yards aim at the pin (attack), otherwise aim at center (defense).” We look for how this threshold is implemented.
Expected-value models redefined for amateurs, not PGA benchmarks.
Challenge: PGA-based Strokes Gained is too strict for amateurs. We look for models that fix or separate putts for evaluation.
Usual: PGA Tour average. Under review: handicap-based baselines (HC 5, 10, 15…).
Models that fix putts at 2.0 or evaluate “to green” only, to measure shot skill alone.
Expected-value calculations that account for amateur “big number” from trouble (penalty risk weighting, etc.).