거리 전략 분석과 공수 임계값 시각화
Stock Distance(계산 가능한 거리)가 스코어 전략의 기초가 된다.
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.).