Second Half Adjustment History

Overview

This pillar analyzes the historical performance of college football coaching staffs, specifically rating their ability to make effective halftime adjustments. It's valuable for identifying teams that consistently overperform or underperform after the break, creating opportunities in live betting markets.

What It Does

It systematically compares a team's first half performance against its second half performance across key metrics like scoring, efficiency, and yardage. The pillar aggregates this data over multiple seasons, weighting recent games more heavily, to generate a 'Coach Adjustment Rating'. This score reveals which teams get better and which teams falter after halftime.

Why It Matters

Live betting markets often overreact to first half results without pricing in a coaching staff's proven ability to adapt. This pillar provides a data-driven edge by identifying predictable second half momentum shifts that the public and betting lines may miss, leading to profitable in-game wagers.

How It Works

First, the system ingests play-by-play data for every game. It then calculates first half vs. second half differentials for scoring margin and Expected Points Added (EPA) per play. These differentials are adjusted for opponent strength and then combined into a single, rolling 'Coach Adjustment Rating' for each team's staff.

Methodology

The core calculation is the 'Adjustment Delta', derived from (2nd Half EPA/play - 1st Half EPA/play) + (2nd Half Scoring Margin - 1st Half Scoring Margin). This delta is calculated for each game over a rolling 15-game window, adjusted for the opponent's defensive and offensive ratings. The final rating is a weighted average, emphasizing conference games and recent performance.

Edge & Advantage

This provides a specific edge in live trading by isolating the impact of coaching, a qualitative factor that is notoriously difficult for standard models to price correctly.

Key Indicators

• 2nd Half Scoring Margin

  high

  The average difference between points scored and points allowed in the second half compared to the first.

• 3rd Quarter EPA Differential

  high

  Measures the change in Expected Points Added per play immediately following halftime, indicating the initial impact of adjustments.

• Coach Adjustment Rating

  high

  A composite score (0-100) representing a staff's historical ability to improve team performance after halftime.

Data Sources

• College Football Data API

  Provides historical and live play-by-play data, drive results, and team statistics for CFB.

• SportsDataIO

  Offers real-time sports data feeds, including live scores and advanced metrics necessary for in-game analysis.

Example Questions This Pillar Answers

• → Will Ohio State cover the live spread of -6.5 if they are only leading by 3 at halftime?
• → Will the second half total for the Alabama vs. Georgia game go over 27.5 points?
• → Which team is more likely to win if tied at halftime, Team A (high adjustment rating) or Team B (low rating)?

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