Transfer QB Adaptation Curve

Overview

This pillar analyzes the performance trajectory of college football quarterbacks who have transferred to a new team. It identifies the critical adaptation period, providing an edge in predicting when a QB's performance will surge past market expectations.

What It Does

It systematically tracks week-over-week advanced metrics like Expected Points Added (EPA) per play and Completion Percentage Over Expectation (CPOE) for transfer QBs during the first six games of a season. The analysis models this data to pinpoint an inflection point where the quarterback masters the new offensive system. This quantitative trend is then cross-referenced with qualitative factors like system complexity and schedule difficulty.

Why It Matters

Markets are often slow to adjust to a transfer QB's potential, pricing them based on their old team's performance or early-season struggles. This pillar provides a forward-looking signal, anticipating performance leaps before they are fully reflected in betting lines and player prop markets.

How It Works

First, it identifies all starting QBs who transferred in the offseason. Second, it collects their game-by-game advanced statistics for weeks 1 through 6. Third, it applies a rolling average to these stats to smooth out single-game anomalies and calculates the rate of change. Finally, it projects a breakout window when the performance trendline shows sustained acceleration.

Methodology

The core calculation is an 'Adaptation Velocity Score', determined by the second derivative of a 3-week rolling average of EPA per play. A score greater than zero for two consecutive weeks indicates a positive inflection point. This is weighted by a 1-10 'System Complexity Score' derived from playbook analysis and the opponent-adjusted defensive efficiency for the first six games.

Edge & Advantage

It quantifies the 'settling-in' period that most analysts only talk about, giving you a data-driven signal to bet on a QB's improvement before the general public catches on.

Key Indicators

• EPA Trend (Weeks 1-6)

  high

  Measures the rate of improvement in Expected Points Added per play, identifying QBs on a sharp upward trajectory.

• CPOE vs. Pressure

  medium

  Tracks Completion Percentage Over Expectation specifically on plays where the QB is pressured, a key sign of comfort in a new system.

• System Complexity Score

  low

  A qualitative rating of the new offensive scheme's difficulty, which can predict a longer or shorter adaptation period.

Data Sources

• CollegeFootballData API

  Provides play-by-play data used to calculate advanced metrics like EPA for individual players.

• Pro Football Focus (PFF)

  Offers player-level grades and advanced stats that help assess performance beyond the box score.

• Team Beat Reporters

  Qualitative information from local sports journalists on player integration, chemistry, and grasp of the playbook.

Example Questions This Pillar Answers

• → Will Bo Nix's passer rating be over 150.5 in Week 5?
• → Will Dillon Gabriel's team cover the spread against their first ranked opponent?
• → Will Shedeur Sanders throw for over 300.5 yards this week?

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