Chapter 28 Further Reading: Career Paths in Sports Analytics

Career Development Books

Sports-Specific

  • "The MVP Machine" by Ben Lindbergh and Travis Sawchik - Behind-the-scenes look at how analytics has transformed player development. Excellent for understanding how analytics integrates with coaching.

  • "Moneyball" by Michael Lewis - The classic that introduced sports analytics to mainstream audiences. Essential background for understanding the field's origins.

  • "The Signal and the Noise" by Nate Silver - While broader than sports, Silver's chapter on baseball forecasting provides valuable perspective on prediction and uncertainty.

  • "Astroball" by Ben Reiter - Documents the Houston Astros' analytics-driven rebuild. Shows how analytics departments function within organizations.

General Career Development

  • "So Good They Can't Ignore You" by Cal Newport - Argues for skill development over "following passion." Highly applicable to building sports analytics careers.

  • "Range" by David Epstein - Makes the case for diverse skill sets over early specialization. Relevant for career changers.

  • "Designing Your Life" by Bill Burnett and Dave Evans - Practical framework for career planning that applies well to non-traditional paths like sports analytics.

  • "Never Eat Alone" by Keith Ferrazzi - Networking strategies that work in any industry, including sports.

Industry Resources

Job Boards and Career Sites

  • TeamWork Online (teamworkonline.com) - Primary job board for sports industry positions
  • Sports Business Journal Careers - Senior-level positions and industry news
  • Work In Sports (workinsports.com) - Entry-level and internship postings
  • LinkedIn - Professional networking and job alerts

Professional Organizations

  • Sports Analytics Society - Professional organization for sports analysts
  • SABR (Society for American Baseball Research) - Analytics-focused baseball organization with transferable content
  • Sports Data Analytics Association - Academic and industry connections

Conferences and Events

  • MIT Sloan Sports Analytics Conference - Premier annual conference
  • SABR Analytics Conference - Baseball-focused with broader applications
  • Carnegie Mellon Sports Analytics Conference - Academic perspective
  • Hashtag Sports - Digital and fan engagement focus

Online Learning

Technical Skills

Python Programming: - DataCamp - Python for Data Science track - Coursera - Python for Everybody (University of Michigan) - Real Python (realpython.com) - Free tutorials

SQL: - Mode Analytics SQL Tutorial - SQLZoo - Interactive exercises - PostgreSQL Tutorial (postgresqltutorial.com)

Machine Learning: - Fast.ai - Practical Deep Learning - Coursera - Machine Learning (Stanford/Andrew Ng) - Kaggle Learn - Free micro-courses

Statistics: - Khan Academy - Statistics and Probability - Coursera - Statistics with R (Duke) - OpenIntro Statistics - Free textbook

Sports Analytics Specific

  • nflfastR Tutorial - NFL analytics in R
  • cfbfastR Tutorial - College football data in R
  • Sports Analytics Course (Coursera) - University of Michigan
  • Open Source Football - Community tutorials and guides

Blogs and Websites

Industry Analysis

  • Open Source Football (opensourcefootball.com) - Community analytics blog
  • Football Outsiders (footballoutsiders.com) - Advanced NFL analysis
  • ESPN Stats & Information - Official ESPN analytics coverage
  • The Athletic - Premium sports journalism with analytics focus
  • FiveThirtyEight Sports - Data journalism

Technical Tutorials

  • Towards Data Science - Data science tutorials (Medium)
  • Analytics Vidhya - Machine learning content
  • KDnuggets - Data science news and tutorials

Career Advice

  • Sports Business Classroom - Industry career guidance
  • The Sports MBA - Career resources
  • Business of College Sports - College athletics focus

Podcasts

Sports Analytics

  • Effectively Wild (FanGraphs) - Baseball analytics discussions
  • PFF Forecast - Football analytics from PFF
  • Sports Analytics Podcast - Industry interviews and insights
  • Statistically Speaking - Academic sports analytics

Career Development

  • How I Built This (NPR) - Entrepreneurship stories
  • The Knowledge Project - Deep interviews on expertise
  • Masters of Scale - Business scaling lessons

Academic Resources

Research Papers

Key foundational papers in sports analytics:

  • Burke, B. (2019). "DeepQB" - Neural network quarterback evaluation
  • Lock, D., & Nettleton, D. (2014). "Win Probability in the NFL" - Win probability modeling
  • Yam, D., & Lopez, M. (2019). "Fourth Down Decision Making" - Decision analysis

Access through: - Google Scholar - SSRN (Social Science Research Network) - MIT Sloan Sports Analytics Conference Proceedings

Academic Programs

Graduate Programs in Sports Analytics: - Syracuse University (MS in Applied Data Science with Sports Analytics focus) - Columbia University (Sports Management with Analytics) - Northwestern University (Sports Analytics Certificate) - Ohio University (Sports Administration) - University of Michigan (Sport Management)

Online Certificates: - edX/MITx Analytics Edge - Coursera Sports Analytics Specialization - DataCamp Data Scientist Track

Tools and Platforms

Data Sources

Free: - College Football Data API (collegefootballdata.com) - Pro Football Reference (pro-football-reference.com) - Sports Reference (sports-reference.com) - nflfastR/cfbfastR (R packages)

Paid/Professional: - Sportradar - Stats Perform - Pro Football Focus (PFF) - Catapult/Player tracking services

Analysis Tools

Free/Open Source: - Python (pandas, scikit-learn, matplotlib) - R (tidyverse, nflfastR) - PostgreSQL - Jupyter Notebooks

Commercial: - Tableau - Power BI - MATLAB - SAS

Networking Resources

Online Communities

  • Twitter/X Sports Analytics - Follow #sportsanalytics, #NFLanalytics, #CFBanalytics
  • Reddit r/sportsanalytics - Discussion forum
  • Sports Analytics Discord - Real-time community chat
  • LinkedIn Groups - Sports Analytics Professionals, Football Analytics

Building Your Brand

  • Medium - Publishing platform for analysis
  • Substack - Newsletter platform
  • GitHub - Code portfolio
  • Personal website - Central hub for work

Interview Preparation

Technical Interview Resources

  • LeetCode - Coding practice
  • HackerRank - SQL and Python challenges
  • Cracking the Coding Interview - Technical interview guide
  • Storytelling with Data - Visualization principles

Behavioral Interview Resources

  • STAR Method guides - Various online resources
  • Glassdoor - Company-specific interview experiences
  • Indeed Interview Guide - General preparation tips

Inspiration and Motivation

Success Stories

Follow these professionals on social media for career insights: - Industry leaders sharing their journeys - Analysts at various career stages - Content creators in sports analytics space

Industry News

  • Sports Business Journal
  • The Athletic (Business section)
  • Front Office Sports

Month 1-3: Foundation

  • Complete Python basics
  • Learn SQL fundamentals
  • Start statistics review
  • Follow industry on social media

Month 4-6: Sports Focus

  • Learn sports-specific metrics
  • Complete first portfolio project
  • Attend virtual conference/meetup
  • Begin networking outreach

Month 7-9: Portfolio Building

  • Complete 2-3 portfolio projects
  • Start blog/writing
  • Conduct informational interviews
  • Update LinkedIn and resume
  • Active applications
  • Interview preparation
  • Continue networking
  • Keep building skills

Final Advice from the Field

"The best investment you can make is in yourself. Every hour spent learning a new skill or building a project is an hour invested in your future." - Sports Analytics Director

"Don't wait until you feel ready. Start building, start sharing, start connecting. You'll never feel 100% ready, but action creates momentum." - NFL Team Analyst

"This field rewards curiosity and persistence. The people who succeed are the ones who genuinely love solving problems with data—and who keep going when it gets hard." - VP of Football Research