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Math behind Moneyball

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Page d'accueilScience des donnéesAnalyse des données

Math behind Moneyball

University of Houston System

À propos de ce cours : Learn how probability, math, and statistics can be used to help baseball, football and basketball teams improve, player and lineup selection as well as in game strategy.

Créé par :  University of Houston System
University of Houston System
  • Professor Wayne Winston

    Enseigné par :  Professor Wayne Winston, Visiting Professor

    Bauer College of Business
NiveauDébutant
Langue
English
Comment réussirRéussissez tous les devoirs notés pour terminer le cours.
Notes des utilisateurs
4.5 étoiles
Note moyenne des utilisateurs 4.5Voir ce que disent les étudiants
Programme de cours
SEMAINE 1
Before you start...
1 vidéo, 1 lecture
  1. Vidéo: All you will learn
  2. Reading: Suggested Textbooks (Not Required)
Module 1
You will learn how to predict a team’s won loss record from the number of runs, points, or goals scored by a team and its opponents. Then we will introduce you to multiple regression and show how multiple regression is used to evaluate baseball hitters. Excel data tables, VLOOKUP, MATCH, and INDEX functions will be discussed.
11 vidéos, 22 lectures
  1. Reading: Download Excel Files (Important!)
  2. Vidéo: 1.1 Introduction
  3. Reading: Excel Files
  4. Reading: Recommended reading
  5. Vidéo: 1.2 Pythagorean Theorem
  6. Reading: Excel file
  7. Reading: Recommended reading
  8. Vidéo: 1.3 Ten runs = One win
  9. Vidéo: Homework Problems 1 and 2
  10. Reading: Excel file
  11. Reading: Excel file
  12. Reading: Recommended reading
  13. Vidéo: 1.4 Runs created
  14. Reading: Excel Files
  15. Reading: Recommended reading
  16. Vidéo: 1.5 Runs Created Per Game
  17. Reading: Homework Problem 3
  18. Reading: Excel Files
  19. Reading: Recommended reading
  20. Vidéo: 1.6 Multiple Regression 1
  21. Reading: Excel Files
  22. Reading: Recommended reading
  23. Vidéo: 1.7 Multiple Regression 2
  24. Reading: Excel Files
  25. Reading: Recommended reading
  26. Vidéo: 1.8 Linear Weights
  27. Reading: Excel Files
  28. Reading: Recommended reading
  29. Vidéo: 1.9 On Base Percentage + Slugging Percentage
  30. Reading: Excel Files
  31. Reading: Recommended reading
  32. Vidéo: 1.10 Barry Bonds Runs per Game
  33. Reading: Homework Problems 4
Noté: Test Questions 1 and 2
Noté: Test Question 3
Noté: Test Question 4
SEMAINE 2
Module 2
You will concentrate on learning important Excel tools including Range Names, Tables, Conditional Formatting, PivotTables, and the family of COUNTIFS, SUMIFS, and AVERAGEIFS functions. You will concentrate on learning important Excel tools including Range Names, Tables, Conditional Formatting, PivotTables, and the family of COUNTIFS, SUMIFS, and AVERAGEIFS functions.
10 vidéos, 23 lectures
  1. Reading: Download Excel Files (Important!)
  2. Reading: Excel Files
  3. Reading: Recommended Reading
  4. Vidéo: 2.1 Excel Range Names
  5. Reading: Excel Files
  6. Reading: Recommended Reading
  7. Vidéo: 2.2 Excel Tables
  8. Reading: Excel Files
  9. Reading: Recommended Reading
  10. Vidéo: 2.3 Conditional Formatting: Top Bottom Rules
  11. Reading: Excel Files
  12. Reading: Recommended Reading
  13. Vidéo: 2.4 Conditional Formatting: Data Bars
  14. Reading: Excel Files
  15. Reading: Recommended Reading
  16. Vidéo: 2.5 Conditional Formatting: The Formula Option
  17. Reading: Excel Files
  18. Reading: Recommended Reading
  19. Vidéo: 2.6 COUNTIF and COUNTIFS functions
  20. Reading: Excel Files
  21. Reading: Recommended Reading
  22. Vidéo: 2.7 SUMIF and SUMIFS Functions
  23. Reading: Excel Files
  24. Reading: Recommended Reading
  25. Vidéo: 2.8 AVERAGEIF and AVERAGEIFS Functions
  26. Reading: Homework Problem 5
  27. Reading: Excel Files
  28. Reading: Recommended Reading
  29. Vidéo: 2.9 PivotTables I
  30. Reading: Excel Files
  31. Reading: Recommended Reading
  32. Vidéo: 2.10 PivotTables II
  33. Reading: Homework Problem 6
Noté: Test Question 5
Noté: Test Question 6
SEMAINE 3
Module 3
You will learn how Monte Carlo simulation works and how it can be used to evaluate a baseball team’s offense and the famous DEFLATEGATE controversy.
6 vidéos, 10 lectures
  1. Reading: Download Excel Files (Important!)
  2. Reading: Excel Files
  3. Reading: Recommended Reading
  4. Vidéo: 3.1 Monte Carlo Simulation I
  5. Reading: Excel Files
  6. Vidéo: 3.2 Monte Carlo Simulation Part II
  7. Reading: Excel Files
  8. Vidéo: 3.3 Monte Carlo Simulation Part III
  9. Reading: Excel Files
  10. Vidéo: 3.4 Baseball Monte Carlo simulation
  11. Reading: Excel Files
  12. Reading: Recommended Reading
  13. Vidéo: 3.5 Resampling
  14. Reading: Excel Files
  15. Vidéo: 3.6 Deflategate
  16. Reading: Homework Problem 8
Noté: Test Question 7
Noté: Test Question 8
SEMAINE 4
Module 4
You will learn how to evaluate baseball fielding, baseball pitchers, and evaluate in game baseball decision-making. The math behind WAR (Wins above Replacement) and Park Factors will also be discussed. Modern developments such as infield shifts and pitch framing will also be discussed.
13 vidéos, 27 lectures
  1. Reading: Download Excel Files (Important!)
  2. Reading: Excel Files
  3. Reading: Recommended Reading
  4. Vidéo: 4.1 Bunting and Expected Runs
  5. Reading: Excel Files
  6. Reading: Recommended reading
  7. Vidéo: 4.2 Base Stealing
  8. Reading: Homework Problem 9
  9. Reading: Excel Files
  10. Reading: Recommended Reading
  11. Vidéo: 4.3 Range Factor
  12. Reading: Excel Files
  13. Vidéo: 4.4 UZR (Ultimate Zone Rating) and Fielding
  14. Reading: Homework Problem 10
  15. Reading: Homework Problem 11
  16. Vidéo: 4.5 Introduction to Fan Graphs
  17. Reading: Excel Files
  18. Reading: Recommended Reading
  19. Vidéo: 4.6 DIPS (Defense Independent Pitching Statistics)
  20. Reading: Homework Problem 12
  21. Reading: Excel Files
  22. Reading: Recommended Reading
  23. Vidéo: 4.7 Win Probability Added
  24. Reading: Excel Files
  25. Reading: Recommended Reading
  26. Vidéo: 4.8 Runs above Average
  27. Reading: Excel Files
  28. Reading: Recommended Reading
  29. Vidéo: 4.9 WAR (Wins above Replacement)
  30. Reading: Homework Problem 13
  31. Reading: Excel Files
  32. Vidéo: 4.10 What Makes your Team Win?
  33. Reading: Excel Files
  34. Vidéo: 4.11 Defensive Shifts
  35. Reading: Excel Files
  36. Vidéo: 4.12 Catcher Framing
  37. Reading: Excel Files
  38. Reading: Recommended Reading
  39. Vidéo: 4.13 Park Factors
  40. Reading: Homework Problem 14
Noté: Test Question 9
Noté: Test Questions 10&11
Noté: Test Question 12
Noté: Test Question 13
Noté: Test Question 14
SEMAINE 5
Module 5
You will learn basic concepts involving random variables (specifically the normal random variable, expected value, variance and standard deviation.) You will learn how regression can be used to analyze what makes NFL teams win and decode the NFL QB rating system. You will also learn that momentum and the “hot hand” is mostly a myth. Finally, you will use Excel text functions and the concept of Expected Points per play to analyze the effectiveness of a football team’s play calling.
11 vidéos, 23 lectures
  1. Reading: Download Excel Files (Important!)
  2. Reading: Excel Files
  3. Reading: Recommended Reading
  4. Vidéo: 5.1 Random Variables
  5. Reading: Excel Files
  6. Reading: Recommended Reading
  7. Vidéo: 5.2 The Normal Random Variable
  8. Reading: Excel Files
  9. Reading: Recommended Reading
  10. Vidéo: 5.3 Streakiness
  11. Reading: Excel Files
  12. Vidéo: 5.4 What makes NFL teams win?
  13. Reading: Homework Problem 15
  14. Reading: Excel Files
  15. Vidéo: 5.5 Deconstructing the NFL QB rating
  16. Reading: Homework Problem 16
  17. Reading: Excel Files
  18. Reading: Recommended Reading
  19. Vidéo: 5.6 Football States and Values
  20. Reading: Excel Files
  21. Reading: Recommended Reading
  22. Vidéo: 5.7 Football Decision Making
  23. Reading: Homework Problem 17
  24. Reading: Excel Files
  25. Vidéo: 5.8 The Belichick Decision
  26. Reading: Homework Problem 18
  27. Reading: Excel Files
  28. Reading: Recommended Reading
  29. Vidéo: 5.9 Text functions and Analyzing NFL plays
  30. Reading: Excel Files
  31. Vidéo: 5.10 Texans 1st and 10 Play Selection
  32. Reading: Excel Files
  33. Vidéo: 5.11 STDEVIF and Too Many Field Goal Attempts
  34. Reading: Homework Problem 19
Noté: Test Question 15
Noté: Test Question 16
Noté: Test Question 17
Noté: Test Question 18
Noté: Test Question 19
SEMAINE 6
Module 6
You will learn how two-person zero sum game theory sheds light on football play selection and soccer penalty kick strategies. Our discussion of basketball begins with an analysis of NBA shooting, box score based player metrics, and the Four Factor concept which explains what makes basketball teams win.
7 vidéos, 16 lectures
  1. Reading: Download Excel Files (Important!)
  2. Reading: Excel Files
  3. Reading: Recommended Reading
  4. Vidéo: 6.1 Game Theory Part I
  5. Reading: Excel Files
  6. Vidéo: 6.2 Game Theory Part II
  7. Reading: Homework Problem 20
  8. Reading: Excel Files
  9. Vidéo: 6.3 Basketball Shot Selection
  10. Reading: Excel Files
  11. Reading: Recommended Reading
  12. Vidéo: 6.4 Effective Field Goal Percentage (EFG)
  13. Reading: Homework Problem 21
  14. Reading: Excel Files
  15. Vidéo: 6.5 Hollinger Team Metrics
  16. Reading: Excel Files
  17. Reading: Recommended Reading
  18. Vidéo: 6.6 Four Factors
  19. Reading: Homework Problem 22
  20. Reading: Excel Files
  21. Reading: Recommended Reading
  22. Vidéo: 6.7 Basketball Box Score Models
  23. Reading: Homework Problem 23
Noté: Test Question 20
Noté: Test Question 21
Noté: Test Question 22
Noté: Test Question 23
SEMAINE 7
Module 7
You will learn about advanced basketball concepts such as Adjusted plus minus, ESPN’s RPM, SportVu data, and NBA in game decision-making.
8 vidéos, 13 lectures
  1. Reading: Download Excel Files (Important!)
  2. Reading: Excel Files
  3. Vidéo: 7.1 Extracting Lineup data and Computing raw + -
  4. Reading: Excel Files
  5. Vidéo: 7.2 Computing Pairs Lineup Statistics
  6. Reading: Excel Files
  7. Vidéo: 7.3 Adjusted + -
  8. Reading: Homework Problem 24
  9. Reading: Excel Files
  10. Vidéo: 7.4 ESPM RPM (Real Plus Minus)
  11. Reading: Homework Problem 25
  12. Reading: Excel Files
  13. Vidéo: 7.5 How Analytics Helped the Mavs beat the Heat
  14. Reading: Excel Files
  15. Vidéo: 7.6 SportsVu data
  16. Reading: Homework Problem 26
  17. Reading: Excel Files
  18. Vidéo: 7.7 In Game Basketball Decision-Making
  19. Reading: Excel Files
  20. Vidéo: 7.8 Hack a Jordan (or Dwight)
  21. Reading: Homework Problem 27
Noté: Test 24
Noté: Test 25
Noté: Test 26
Noté: Test 27
SEMAINE 8
Module 8
You will learn how to use game results to rate sports teams and set point spreads. Simulation of the NCAA basketball tournament will aid you in filling out your 2016 bracket. Final 4 is in Houston!
7 vidéos, 18 lectures
  1. Reading: Download Excel Files (Important!)
  2. Reading: Excel Files
  3. Reading: Recommended Reading
  4. Vidéo: 8.1 Rating NFL teams
  5. Reading: Homework Problem 28
  6. Reading: Excel Files
  7. Reading: Recommended Reading
  8. Vidéo: 8.2 Computing Strength of Schedule
  9. Reading: Homework Problem 29
  10. Reading: Excel Files
  11. Reading: Recommended Reading
  12. Vidéo: 8.3 Rating NFL Offenses and Defenses
  13. Reading: Homework Problem 30
  14. Reading: Excel Files
  15. Reading: Recommended Reading
  16. Vidéo: 8.4 Multiplicative Rating Models for Soccer
  17. Reading: Homework Problem 31
  18. Reading: Excel Files
  19. Vidéo: 8.5 Regularization
  20. Reading: Excel Files
  21. Reading: Recommended Reading
  22. Vidéo: 8.6 Simulating the NCAA Tournament
  23. Reading: Excel Files
  24. Vidéo: 8.7 NCAA Props Bets
  25. Reading: Homework Problem 32
Noté: Test 28
Noté: Test 29
Noté: Test 30
Noté: Test 31
Noté: Test 32
SEMAINE 9
Module 9
You will learn how to rate NASCAR drivers and get an introduction to sports betting concepts such as the Money line, Props Bets, and evaluation of gambling betting systems.
10 vidéos, 19 lectures
  1. Reading: Download Excel Files (Important!)
  2. Reading: Excel Files
  3. Reading: Recommended Reading
  4. Vidéo: 9.1 Method of Maximum Likelihood
  5. Reading: Excel Files
  6. Reading: Recommended Reading
  7. Vidéo: 9.2 Rating Teams Based on Wins and Losses
  8. Reading: Homework Problem 33
  9. Reading: Excel Files
  10. Vidéo: 9.3 Simulating the NFL Playoffs
  11. Reading: Excel Files
  12. Vidéo: 9.4 Rating NASCAR Drivers
  13. Reading: Excel Files
  14. Vidéo: 9.5 How Good are NFL Point Spreads
  15. Reading: Excel Files
  16. Vidéo: 9.6 Relating the Money Line to Point Spreads
  17. Reading: Recommended Reading
  18. Reading: Homework Problem 34
  19. Reading: Excel Files
  20. Vidéo: 9.7 How Can you tell if a Betting System is Successful?
  21. Reading: Homework Problem 35
  22. Reading: Excel Files
  23. Reading: Recommended Reading
  24. Vidéo: 9.8 Props Bets I
  25. Reading: Excel Files
  26. Vidéo: 9.9 Props Bet II
  27. Reading: Excel Files
  28. Vidéo: 9.10 Props Bet III
  29. Reading: Homework Problem 36
Noté: Test 33
Noté: Test 34
Noté: Test 35
Noté: Test 36
SEMAINE 10
Module 10
You will learn how Kelly Growth can optimize your sports betting, how regression to the mean explains the SI cover jinx and how to optimize a daily fantasy sports lineup. We close with a discussion of golf analytics.
7 vidéos, 14 lectures
  1. Reading: Download Excel Files (Important!)
  2. Reading: Excel Files
  3. Reading: Recommended Reading
  4. Vidéo: 10.1 Kelly Growth Part I
  5. Reading: Excel Files
  6. Vidéo: 10.2 Kelly Growth Part II
  7. Reading: Excel Files
  8. Vidéo: 10.3 Kelly Growth Part III
  9. Reading: Homework Problem 37
  10. Reading: Excel Files
  11. Reading: Recommended Reading
  12. Vidéo: 10.4 Regression to the Mean
  13. Reading: Homework Problem 38
  14. Reading: Excel Files
  15. Vidéo: 10.5 Daily Fantasy Sports Part I
  16. Reading: Excel Files
  17. Vidéo: 10.6 Daily Fantasy Sports Part II
  18. Reading: Homework Problem 39
  19. Reading: Excel Files
  20. Vidéo: 10.7 Golf Analytics
  21. Reading: Homework Problem 40
Noté: Test 37
Noté: Test 38
Noté: Test 39
Noté: Test 40
SEMAINE 11
Final Exam
Final exam has 10 questions. Please download and open Excel files before taking the exam. You will be referred to Excel files during the exam. Each question is wort 1 point. You need to answer 6 questions or more correctly to pass the exam.
1 lecture
  1. Reading: Download Excel Files
Noté: Final Exam

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Créateurs
University of Houston System
The University of Houston System’s four universities and six regional campuses comprise the only comprehensive higher education system serving the world’s energy capital and the Gulf Coast region. Among institutions nationwide, the UH System remains a model of diversity and a reflection of the city it serves.
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Notation et examens
Note moyenne 4.5 sur 5 sur 37 notes
Javier Ochoa

Excellent course if you like statistics, probabilities, and how to linh sport with math. Well explained. Maybe it needs more "movement" on forums

Michael Sweet

This is one of the very the best classes I've ever taken. It provided the tools in Excel and the methods to model various sports outcomes so that I can start creating my own models. The examples were wide ranging and interesting. I thoroughly enjoyed listening to Professor Winston and appreciated all the additional references he pointed out during the lectures. I would love to see a second course in sports analytics . I do wish this course was called "Introduction to Sports Analytics", or "Sports Analytics I" so it would be easier to find. It seems like this course should have many more reviews than it does. Also, some of the course data may need updated. Highly recommended to anyone interested in sportsbetting or fantasy sports.

SP

Great course, however very heavy emphasis on Baseball and NFL. Resultantly some of the assessment questions proved impossible given the knowledge needed about the sport.

B

Wow, this is quite the crash course in sports analytics and Excel tricks! I was familiar with most of the concepts, but enjoyed seeing how easily all of these advanced stats could be calculated, and learned some really useful Excel functionality (what-if analysis, solver). The amount of material that is covered is really impressive!

Biggest problem with this course: it doesn't turn up when you search for "sports analytics" in Coursera's search - luckily for me mooclist.com knows about it



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