Positional Switch Adaptation

Overview

This pillar analyzes how a rugby player's performance metrics change after a permanent positional switch. It's valuable for identifying mispriced player proposition markets before the general public adjusts to the player's new role.

What It Does

It establishes a baseline of a player's key statistics in their original position over a significant period. Then, it tracks these same metrics, plus new role-specific ones, in their new position. The pillar calculates the rate of adaptation and projects future performance by comparing the player's output to their old self and the league average for the new role.

Why It Matters

A player's value and statistical output can change dramatically with a new role. This pillar provides a data-driven edge by quantifying the adaptation process, revealing whether a player is thriving or struggling before their market price fully reflects the change.

How It Works

First, the system identifies a player who has made at least three consecutive starts in a new position. It then pulls their per-80-minute stats from the previous season in their old role to create a baseline. Performance data from the new position is collected and compared against both the baseline and the average stats for that position, generating an adaptation score.

Methodology

The core calculation is the Positional Adaptation Score (PAS). PAS is derived by comparing per-80-minute metrics (e.g., tackles, meters carried, lineout takes) from the last 10 games in the old position against the first 5-10 games in the new position. The formula is: PAS = ( (NewStat_p80 / OldStat_p80) + (NewStat_p80 / LeagueAvg_p80) ) / 2, creating a blended score of self-improvement and positional fit.

Edge & Advantage

This provides a quantitative edge over qualitative 'eye-test' analysis, allowing you to find value in player prop positions while the market is still pricing them based on their old position.

Key Indicators

• Positional Adaptation Score (PAS)

  high

  A composite score measuring how a player's statistical output in a new role compares to their previous role and the league average.

• Work Rate Change

  high

  The percentage change in key effort stats like tackles, ruck arrivals, and ball carries per 80 minutes.

• Skill Usage Shift

  medium

  Tracks the frequency change of role-specific skills, such as kicking from hand for a new fly-half or lineout takes for a new lock.

Data Sources

• Opta Sports

  Provides detailed player performance data and event tracking for major professional rugby leagues.

• ItsRugby

  A comprehensive database for player statistics, match results, and positional history across global competitions.

• League Official Websites

  Official team sheets and basic match statistics from leagues like the URC, Premiership Rugby, and Top 14.

Example Questions This Pillar Answers

• → Will Player X score over 4.5 tries this season after moving from centre to wing?
• → Will Player Y's tackle completion rate be over 90% in his first five starts at flanker?
• → Will Team Z's lineout success rate change by more than 5% with their primary lock now playing at No. 8?

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