Try Conversion Rate Regression

Overview

This pillar analyzes the quality and repeatability of a rugby team's try-scoring methods. It identifies teams that are overperforming due to luck versus those with a sustainable process, offering a predictive edge in points-based markets.

What It Does

Using statistical regression, this pillar models a team's scoring efficiency based on how they create opportunities. It distinguishes between tries from sustained, high-pressure attacks inside the opponent's 22-meter line and volatile tries from long-range breakaways or turnovers. This process generates an 'Expected Tries' (xT) metric to highlight teams due for positive or negative regression.

Why It Matters

Teams relying heavily on unpredictable, opportunistic tries are poor bets to continue their high scoring. This analysis provides a forward-looking measure of scoring potential, allowing you to fade overperforming teams and back underperforming ones before the market adjusts.

How It Works

First, we analyze play-by-play data from a team's recent matches, categorizing each try's origin as either 'sustained pressure' or 'opportunistic'. We then calculate key efficiency metrics like points per red zone entry. Finally, a regression model compares a team's actual try count to their expected count based on the quality of their scoring chances, flagging significant deviations.

Methodology

Tries are classified based on origin: 'Sustained' if resulting from 5 or more phases inside the opponent's 22m line; 'Opportunistic' if from an intercept, turnover, or kick return originating behind the team's own 40m line. A linear regression model, using a 10-game rolling window, predicts future tries based on the historical ratio of sustained vs. opportunistic opportunities. The model is: Predicted Tries = β₀ + β₁(Sustained Opportunities) + β₂(Opportunistic Opportunities) + ε.

Edge & Advantage

This pillar quantifies the quality of a team's scoring process, not just the outcome. This identifies overvalued and undervalued teams in the points markets before simple form guides can.

Key Indicators

• Points Per Red Zone Entry

  high

  Measures a team's clinical finishing ability once they get deep into opposition territory.

• Try Source Ratio

  high

  The ratio of tries scored from sustained, structured play versus opportunistic, broken-field play.

• Expected Tries (xT) vs Actual

  medium

  The difference between how many tries a team was expected to score based on their process versus how many they actually scored.

Data Sources

• Opta Sports

  Provides detailed, timestamped play-by-play data for major professional rugby competitions, essential for categorizing try origins.

• League-Specific Data Feeds

  Direct data feeds from leagues like Premiership Rugby or United Rugby Championship that offer granular event data.

Example Questions This Pillar Answers

• → Will Team A score over or under 2.5 tries against Team B?
• → Will the total match points in the Saracens vs. Leinster game exceed 48.5?
• → Will the Blues beat the Crusaders by more than a 7.5 point spread?

Tags