Readings

Readings are due the Tuesday of each week, as we will discuss them before or as part of our lecture.

*: Please print this article and bring to class

Week 1 (Jan 26-28, review of introductory material, three types of articles)

Week 2 (Feb 2-4, baseball statistics, expected runs, runs created)

• Sabermetric Manifesto (Lahman)
• Runs created primer (Wiki)
• Sabermetric primer on runs created  (SABR.org)
• A closer look at run estimation (Hardball Times)
• Pitching and Defense* (BP)
• Pitch Framing* (Grantland)
• Bad Coaching Decision* (538)

• Review: Chapter 5 in Open Intro (no need to print out)

Week 3 (Feb 9-11, pitcher statistics, multiple regression)

• Deserved Run Average* (BP)
• Why FIP? (FanGraphs)
• Everything FIP  (BLS)
• Everything WAR (BLS)

• Review: Chapter 6 in Open Intro (no need to print out)

Week 4 (Feb 16-18, kickers, logistic regression)

• Kickers are forever* (and read footnote 5) (538)
• Kicker haters (538)
• It sucks to kick in the cold (StatsbyLopez)

• Review: Chapter 6 in Open Intro (logistic regression section)

Week 5 (Feb 23-25, expected points, NFL play-calling)

• Expected Points and EPA (Burke)
• Building an Expected Points Model (Causey)
• Operations Research in Football (Carter & Machol)
• Going for It on Fourth Down (Burke)
• Decision Theory in Football (Burke)

Week 7 (Mar 8 – 10, NBA, shot value)

• Starting Point for Analyzing Basketball Statistics (Kubatko et al)
• Demystifying basketball analytics (Partnow)
• A measure of shot quality (Narsu)
• On RPM (Wagner)
• Limits of Analytics (Partnow)

Week 8 (Mar 22 – 24, NHL, shot metrics)

• NHL stats made simple (Jen LC, part I)
• NHL stats made simple (Jen LC, part II)
• Predicting future success (JLikens)
• PDO Intro (Burtch)
• Avalanche are not a test case (Puck Daddy)
• Analytics driving NHL revolution (Parnass)
• Shot quality (EricT, optional)
• Expected goals are a better.. (DTMAboutHeart, Asmean, optional)
• Expected goals & ridge regression (Macdonald, optional)

 

Week 9 (Mar 29 – Mar 31, Stein’s paradox)

• Stein’s Paradox (Efron and Morris)

 

Week 10 (Apr 5 – 7, referee analytics)

1. Call reversals (Lopez and Davis)
2. Do tough calls favor the home team? (Lopez)
3. Referee bias (Dohmen and Sauermann)
4. Scorecasting (Wertheim, Moskowitz)

 

Week 11 (Apr 12 – 14, power rankings & paired comparisons)

1. ESPN’s BPI (ESPN Stats & Info)
2. ESPN’s FPI (ESPN Stats & Info)
3. Summary of the Bradley-Terry model (Long)
4. Bradley Terry models in R (Turner, Firth)
5. Everyone uses the same rating system (Long)
6. NFL Elo ratings (FiveThirtyEight, optional)
7. NBA Elo history (FiveThirtyEight, optional)

 

Week 11 (Apr 19 – 21, statistics in soccer)

1. Introduction to Analytics in Soccer (U of Toronto)
2. What analytics can teach us (538)
3. Expected goals 2.0 (11tegen11)
4. Best predictor for future performance (11tegen11)
5. Repeatability of finishing skill (Opta)
6. 12 shots good, 2 shots better (Power of goals)

 

Add-ons (to be added for future versions of the course)

xCommentary (Knutson)

Who actually won the Moneyball revolution?  (Slate)