Putting Luck/Regression (SG:P vs Baseline)
Fading unsustainable putting streaks before they break.
Overview
This pillar identifies golfers with extreme recent putting performances that are likely to regress to their long-term average. It helps you bet against players who are overvalued due to a temporarily hot putter, or find value in those due for a comeback.
What It Does
The pillar establishes a baseline Strokes Gained: Putting (SG:P) for each golfer based on their last 50-75 rounds. It then compares this long-term average to their performance in the most recent round or tournament. A significant deviation flags the player as a prime candidate for regression, either positive or negative.
Why It Matters
Putting is the most volatile skill in golf, and the market often overreacts to short-term results. This pillar provides a statistical edge by quantifying the difference between a lucky streak and a genuine skill improvement, allowing for smarter bets in matchups and prop markets.
How It Works
First, we compute a player's 50-round rolling average for SG:Putting to create a stable performance baseline. Next, we record the SG:Putting from their most recent completed round. The system then calculates the variance between the two figures. Players with a variance exceeding a set threshold, like +/- 2.0 strokes, are flagged for an impending performance correction.
Methodology
The core metric is the 'Regression Index', calculated as (SG:P_Last_Round - SG:P_50_Round_Average). A positive index suggests negative regression is likely; a negative index suggests positive regression. The model also considers the percentage of putts made from over 20 feet as a secondary indicator of unsustainable luck.
Edge & Advantage
This provides a clear, data-driven signal to fade public perception, which often chases hot putting streaks that are statistically unlikely to continue.
Key Indicators
-
SG:P vs Baseline Variance
highThe difference between a player's most recent putting performance and their long-term average. The core signal for regression.
-
Long Putt Conversion Rate
mediumA player's success rate on putts from over 20 feet. An unusually high rate is a strong indicator of positive luck.
-
Three-Putt Avoidance
lowA sudden spike or drop in three-putts compared to a player's baseline. Signals performance deviation from the norm.
Data Sources
-
Official source for all Strokes Gained data and round-by-round performance metrics.
-
Provides advanced golf analytics, historical data, and predictive modeling.
Example Questions This Pillar Answers
- → Will Rory McIlroy gain strokes putting in Round 2 after gaining +3.5 in Round 1?
- → Who will win the head-to-head matchup between Player A (hot putter) and Player B (average putter)?
- → Will Player X, who lost 2.8 strokes putting yesterday, finish in the Top 20?
Tags
Use Putting Luck/Regression (SG:P vs Baseline) on a real market
Run this analytical framework on any Polymarket or Kalshi event contract.
Try PillarLab