Further Reading: Rushing and Running Game Analysis

Foundational Resources

Academic Papers

  1. "The Value of an Elite Running Back" - Football Outsiders Research - Analyzes replacement-level theory applied to RBs - Quantifies marginal value of rushing production - Discusses roster construction implications

  2. "Yards After Contact as a Predictor of Future Performance" - Studies YAC stability year-over-year - Compares YAC to YPC predictive value - Establishes portable skill framework

  3. "Expected Rushing Yards: A New Framework" - Sports Analytics Conference - Details methodology for expected rushing models - Feature selection for pre-snap predictions - Validation and calibration approaches

  4. "Success Rate vs. EPA: Which Better Predicts Rushing Performance?" - Comparative analysis of efficiency metrics - Split-half reliability testing - Recommendations for different use cases

Books

  1. "Football Analytics: Unlocking Performance" - Chapter on running game analysis - Blocking metrics and attribution - Team-level rushing evaluation

  2. "The Hidden Game of Football" by Carroll, Palmer, and Thorn - Historical perspective on rushing value - Early efficiency metrics - Context-adjusted statistics

  3. "Mathletics" by Wayne Winston - Sports analytics methodology - Statistical thinking applied to football - Expected value frameworks

Online Resources

Data Sources

  1. cfbfastR (College Football) - R package for college football play-by-play - Pre-calculated EPA and success rate - Historical data back to 2003 - GitHub: github.com/sportsdataverse/cfbfastR

  2. nflfastR (NFL Reference) - R package for NFL play-by-play - Expected yards models - Comprehensive rushing metrics - GitHub: github.com/nflverse/nflfastR

  3. College Football Reference - Traditional rushing statistics - Player and team records - Historical comparisons

  4. Pro Football Focus (PFF) - Yards before contact data - Blocking grades - Premium rushing metrics

  5. Sports Info Solutions (SIS) - Broken tackle data - Missed tackle rates - Charting-based metrics

Tutorials and Guides

  1. "Calculating Rush Yards Over Expected" - Open Source Football - Step-by-step RYOE implementation - Feature engineering examples - Model evaluation techniques - URL: opensourcefootball.com

  2. "Understanding Success Rate" - Football Outsiders - Conceptual explanation - Historical development - Application examples

  3. "YAC Analysis in Python" - Sports Analytics Tutorial - Python implementation - Visualization techniques - Comparative analysis code

  4. "Building an Expected Rushing Model" - Kaggle Notebook - Full ML pipeline - Feature importance analysis - Model comparison

Tools and Libraries

Python Packages

# Core data manipulation
import pandas as pd
import numpy as np

# Statistical analysis
from scipy import stats
import statsmodels.api as sm

# Machine learning for expected models
from sklearn.linear_model import LinearRegression, Ridge
from sklearn.ensemble import RandomForestRegressor, GradientBoostingRegressor
from sklearn.model_selection import cross_val_score

# Visualization
import matplotlib.pyplot as plt
import seaborn as sns

# Sports-specific
# pip install sportsdataverse  # College football data
# pip install nfl-data-py       # NFL data wrapper

R Packages

# College football data
install.packages("cfbfastR")

# NFL reference data
install.packages("nflfastR")

# Data manipulation
install.packages("tidyverse")

# Visualization
install.packages("ggplot2")
install.packages("gt")  # Tables

Advanced Topics

Expected Rushing Models

  1. Linear Models - Simple: Box count adjustment only - Intermediate: Gap, formation, down/distance - Paper: "A Linear Approach to Expected Rushing Yards"

  2. Machine Learning Approaches - Random Forest for expected yards - XGBoost implementations - Neural network approaches - Paper: "Machine Learning for Pre-Snap Rushing Predictions"

  3. Bayesian Methods - Hierarchical models for RB evaluation - Uncertainty quantification - Prior information incorporation

Blocking Analysis

  1. Zone Blocking Metrics - Movement and displacement measurement - Zone vs. gap scheme efficiency - Resource: Football Outsiders Zone Blocking Analysis

  2. Individual Lineman Grading - PFF methodology overview - Win rate calculations - Attribution challenges

  3. Tracking Data Applications - Pre-snap alignment analysis - Block quality from player movement - Next Gen Stats rushing metrics

Situational Analysis Deep Dives

  1. Short Yardage Analytics - Formation tendencies - Personnel grouping impact - Success rate by play type

  2. Goal Line Rushing - TD rate by distance - Formation analysis - Personnel optimization

  3. Late Game Rushing - Clock management value - Win probability impact - Efficiency changes with lead

Research Questions for Further Study

RB Evaluation

  1. How stable is RYOE year-over-year compared to YPC?
  2. What is the optimal workload for RB efficiency?
  3. How does age affect rushing metrics differently?
  4. Can we predict breakout seasons from advanced metrics?

Blocking and Attribution

  1. What percentage of rushing success is attributable to blocking vs. RB skill?
  2. How do zone vs. gap schemes affect RYOE?
  3. Can we isolate individual lineman impact on rushing?
  4. How does tight end blocking affect outside run success?

Scheme Analysis

  1. Which formations produce highest RYOE?
  2. How does pre-snap motion affect rushing success?
  3. What is the optimal run/pass balance for rushing efficiency?
  4. How do RPOs affect pure rushing metrics?

Situational Deep Dives

  1. Is short-yardage ability a persistent skill?
  2. How does game script affect RB efficiency metrics?
  3. What is the value of late-game rushing reliability?
  4. How do weather conditions affect rushing metrics?

Video Resources

YouTube Channels

  1. Brett Kollmann - Film breakdown including rushing analysis
  2. JT O'Sullivan - QB School (includes run game concepts)
  3. Baldy Breakdowns - Brian Baldinger's analysis

Courses and Lectures

  1. MIT Sloan Sports Analytics Conference - Rushing analytics presentations
  2. Coursera Sports Analytics - General methodology
  3. StatsBomb Conference - Soccer parallels (expected goals → expected yards)

Community and Forums

Online Communities

  1. r/NFLstatheads - Reddit community for football analytics
  2. r/CFBAnalysis - College football analytics discussion
  3. Football Outsiders Forums - FO methodology discussion
  4. Fantasy Football Analytics - Applied rushing metrics

Twitter/X Accounts to Follow

  1. @benbbaldwin - nflfastR creator
  2. @thomasmock - Sports data visualization
  3. @PFF - Pro Football Focus
  4. @SethWalder - ESPN analytics
  5. @CamPen66 - Expected rushing models

Conferences

  1. MIT Sloan Sports Analytics Conference - Annual, March
  2. SABR Analytics Conference - Baseball-focused but relevant methods
  3. Carnegie Mellon Sports Analytics Conference - Academic focus
  4. Great Lakes Analytics Conference - Regional, applied focus

Practice Datasets

Public Datasets

  1. cfbfastR Play-by-Play - 2000-present college football - Includes EPA, success rate - Free access via R/Python

  2. NFL Play-by-Play (nflfastR) - 1999-present NFL data - Pre-calculated metrics - Ideal for model training

  3. Kaggle NFL Big Data Bowl - Tracking data samples - Annual competitions - Creative feature engineering

Sample Projects

  1. Build an RYOE Model - Start with box count only - Add features incrementally - Compare to published models

  2. RB Consistency Study - Calculate success rate by week - Analyze variance patterns - Identify reliable backs

  3. Blocking Attribution Analysis - Compare YBC across teams for same RB - Study backs who changed teams - Quantify line contribution

Citation Format

When referencing rushing analytics in academic or professional work:

Traditional metrics:
- Yards per carry (YPC)
- Rushing yards per game

Advanced metrics:
- Success rate (Football Outsiders, 2003)
- Yards after contact (Pro Football Focus)
- Rush Yards Over Expected (RYOE) - Baldwin et al.
- Expected Points Added (EPA) - Burke, 2014

Beginner (Weeks 1-4)

  1. Read Football Outsiders success rate methodology
  2. Calculate basic rushing stats in Python
  3. Understand YPC limitations
  4. Practice with cfbfastR data

Intermediate (Weeks 5-8)

  1. Implement YAC calculations
  2. Build simple expected rushing model
  3. Study blocking metrics
  4. Analyze situational splits

Advanced (Weeks 9-12)

  1. Build ML-based RYOE model
  2. Create attribution framework
  3. Develop composite evaluation system
  4. Publish analysis on personal blog

Expert (Ongoing)

  1. Incorporate tracking data
  2. Build real-time systems
  3. Develop novel metrics
  4. Contribute to open-source projects