Chapter 10: Further Reading and Resources

Academic Papers

Field Goal Analysis

  1. "The Determinants of NFL Field Goal Success" - Berry & Berry (2015) - Statistical analysis of FG make probability - Weather, distance, and situational factors - Foundation for probability modeling

  2. "Kicker Evaluation Using Expected Points" - Burke (2013) - Expected points framework for kicker assessment - Field goals over expected methodology - Career value estimation

  3. "The Effect of Temperature on Football Kicking Distance" - Cross (2012) - Physics of kicking in different conditions - Temperature and air density impacts - Applications for game strategy

Fourth Down Decision Analysis

  1. "Going for Three: Predicting the Likelihood of Field Goal Success" - Bilder & Loughin (1998) - Early work on FG probability modeling - Distance-based prediction framework - Statistical methodology foundations

  2. "It's Fourth Down and What Does the Bellman Equation Say?" - Romer (2006) - Landmark paper on fourth-down decision-making - Dynamic programming approach - Evidence of systematic conservatism

  3. "Fourth Down Decisions: Is the Math Wrong?" - Carter & Machol (1978) - Early quantitative fourth-down analysis - Expected value calculations - Historical context for modern work

Punting and Kickoffs

  1. "The Expected Points and Win Probability of Punts" - Yurko et al. (2019) - Comprehensive punt valuation - Net punting vs gross punting - Field position expected points

  2. "Optimal Kickoff Strategies in Professional Football" - Maddox (2020) - Touchback vs return analysis - Expected starting position models - Rule change impact analysis

Books

Sports Analytics Foundations

  1. "Mathletics: How Gamblers, Managers, and Sports Enthusiasts Use Mathematics" - Wayne Winston - Chapter on football special teams - Expected points introduction - Practical applications

  2. "The Hidden Game of Football" - Carroll, Palmer & Thorn

    • Pioneer work in football analytics
    • Expected points development
    • Special teams valuation concepts

  3. "Football Analytics with Python and R" - Eric Eager & George Chahrouri

    • Modern computational approaches
    • Code examples for special teams metrics
    • Data sources and manipulation

Decision Theory

  1. "Thinking, Fast and Slow" - Daniel Kahneman

    • Cognitive biases in decision-making
    • Risk aversion and probability assessment
    • Applications to coaching decisions

  2. "The Signal and the Noise" - Nate Silver

    • Chapter on sports prediction
    • Probability thinking frameworks
    • Model building best practices

Online Resources

Data Sources

  1. cfbfastR (R Package)

    • https://cfbfastR.sportsdataverse.org/
    • College football play-by-play data
    • Expected points and win probability
    • Special teams play identification

  2. collegefootballdata.com API

    • https://collegefootballdata.com/
    • Historical game data
    • Play-by-play access
    • Advanced statistics

  3. Sports Reference - College Football

    • https://www.sports-reference.com/cfb/
    • Historical kicking statistics
    • Punting records and averages
    • Team special teams rankings

Analytics Websites

  1. Football Outsiders

    • https://www.footballoutsiders.com/
    • Special teams DVOA methodology
    • Weekly analysis and rankings
    • Historical special teams data

  2. The Athletic - College Football

    • Premium analytics content
    • Fourth-down analysis articles
    • Special teams feature pieces

  3. ESPN's Stats & Info

    • Expected points explanations
    • Fourth-down decision analysis
    • Win probability applications

Research Blogs

  1. Ben Baldwin's Football Analytics

    • https://rbsdm.com/
    • Fourth-down decision models
    • Expected points methodology
    • Open-source code and data

  2. Michael Lopez's Statistical Research

    • NFL competition committee work
    • Special teams research
    • Rule change analysis

  3. Football Perspective

    • https://www.footballperspective.com/
    • Historical kicking analysis
    • Fourth-down tendencies
    • Statistical deep dives

Video Resources

Educational Content

  1. StatsbyLopez YouTube Channel

    • Expected points explained
    • Win probability tutorials
    • NFL analytics methodology

  2. MIT Sloan Sports Analytics Conference

    • Annual special teams presentations
    • Research paper discussions
    • Industry practitioner talks

  3. Coursera: Sports Analytics

    • University-level courses
    • Statistical methods for sports
    • Project-based learning

Software and Tools

Analysis Packages

  1. nflfastR / cfbfastR

    • R packages for football data
    • EPA and WPA calculations
    • Play-by-play parsing

  2. nfl_data_py / cfb_data_py

    • Python equivalents
    • Pandas integration
    • Visualization support

  3. sportsdataverse

    • Multi-sport data ecosystem
    • Standardized data formats
    • Cross-sport analysis tools

Visualization Tools

  1. Matplotlib/Seaborn

    • Python visualization libraries
    • Field goal charts
    • Decision boundary plots

  2. ggplot2

    • R visualization package
    • Publication-quality graphics
    • Special teams visualizations

  3. Plotly

    • Interactive visualizations
    • Dashboard creation
    • Hover data and animations

Professional Resources

Industry Publications

  1. Football Analytics Summit Proceedings

    • Annual conference papers
    • Industry best practices
    • Emerging methodologies

  2. Journal of Quantitative Analysis in Sports

    • Peer-reviewed research
    • Methodological advances
    • Applied sports statistics

  3. Big Data Bowl Competition Papers

    • NFL-sponsored research
    • Tracking data applications
    • Special teams innovations

Career Development

  1. Sports Analytics Career Guide - Alamar

    • Industry overview
    • Required skills
    • Career pathways

  2. Analytics Job Boards

    • TeamWork Online
    • Sports Business Solutions
    • LinkedIn Sports Analytics

Practice Datasets

Publicly Available

  1. Kaggle NFL Data

    • https://www.kaggle.com/datasets
    • Play-by-play datasets
    • Special teams subset available

  2. GitHub Football Data Repositories

    • Community-maintained datasets
    • Historical play-by-play
    • Cleaned and processed data

  3. Lee Sharpe's NFL Data

    • https://github.com/leesharpe/nfldata
    • Game-level data
    • Team statistics
    • Historical records

Beginner Level

  1. Start with Chapter 10 content
  2. Read Winston's "Mathletics" football chapter
  3. Explore cfbfastR documentation
  4. Practice basic probability calculations

Intermediate Level

  1. Read Romer (2006) on fourth-down decisions
  2. Work through Football Analytics with Python/R
  3. Build field goal probability models
  4. Create fourth-down decision tools

Advanced Level

  1. Study academic papers on special teams
  2. Contribute to open-source projects
  3. Attend analytics conferences
  4. Develop novel methodologies

Community Resources

Online Communities

  1. r/NFLstatheads (Reddit)

    • Community discussion
    • Methodology debates
    • Resource sharing

  2. Sports Analytics Twitter

    • @benaborowitz
    • @EaglesXOs
    • @maborowitz
    • @SethWalder

  3. Discord Analytics Servers

    • Real-time discussion
    • Code sharing
    • Job opportunities

Conferences and Events

  1. MIT Sloan Sports Analytics Conference

    • Annual March event
    • Research presentations
    • Networking opportunities

  2. SABR Analytics Conference

    • Baseball focus with football content
    • Multi-sport analytics
    • Academic presentations

  3. Sports Analytics World Series

    • Global events
    • Industry practitioners
    • Educational workshops

Chapter-Specific Resources

Field Goal Modeling

  • Burke's Expected Points articles
  • Weather impact research
  • Kicker evaluation methodologies

Punting Analysis

  • Net vs gross punting debates
  • Hang time studies
  • Field position value research

Fourth Down Decisions

  • Romer's original paper
  • EdjSports' fourth-down bot
  • Baldwin's decision models

Coverage Units

  • PFF grading methodology
  • Tackle rate analysis
  • Return prevention research

Citation Guidelines

When using these resources in academic work:

APA Format Example:
Romer, D. (2006). Do firms maximize? Evidence from professional
football. Journal of Political Economy, 114(2), 340-365.

Chicago Format Example:
Romer, David. "Do Firms Maximize? Evidence from Professional
Football." Journal of Political Economy 114, no. 2 (2006): 340-365.

Updates and Corrections

This resource list was compiled in 2024. For the most current resources: - Check package documentation for version updates - Follow key researchers on social media - Attend annual conferences for latest research - Monitor academic journals for new publications

Special teams analytics is an evolving field. Stay current by engaging with the community and regularly reviewing new publications.