Division of Graduate Professional Studies
Rabb School of Continuing Studies
Course Syllabus
I. Course Information
1. Course Name: Special Topics in Analytics: Sports Analytics
2. Course Number: RSAN-290 1DL, Fall 2016
3. Course Start and End Dates: Sep 14, 2016 — Nov 22, 2016
4. Online Course Week: Wednesday through Tuesday
5. Instructor Contact Information
John Lynch, DCS
Email:
Phone:
You can contact me through discussion forums on our course web site: by replying to any of my posted messages, posting a new topic on the Questions and Comments forum, or posting to one of the various forums established for each class assignment. To reach me privately, please use the Private Forum. The Private Forum is the method I will use to contact you privately, and is always preferred over email.
6. Syllabus Overview
This syllabus contains all relevant information about the course: its objectives and outcomes, the grading criteria, the texts and other materials of instruction, weekly objectives, outcomes, readings, assignments, and due dates.
Consider this your roadmap for the course. Please read through the syllabus carefully and feel free to share any questions that you may have.
7. Course Description
The book Moneyball by Michael Lewis ushered in an entirely new way to think about, and evaluate, sports. Moneyball introduced the general public to the idea of using analytics to produce a more competitive sports team. Since Moneyball’s publication in 2003, fans, coaches and even players have been using analytics to come up with better strategies in every type of sport.
This course will serve as an introduction to sports analytics for students of all backgrounds. We will use the concepts from Moneyball, and similar references on sports analytics, to examine questions such as: “Who is the best QB in the NFL? Is there such a thing as home field advantage? And if so, why? Should football coaches go for it more on 4th down? How much is LeBron James worth to the Cavaliers?” This course will use very simple math and an assortment of popular readings to demonstrate the power of analytics to analyze sports. Students will not need any advanced skills above basic algebra to understand the concepts in this course though it will be helpful to have a working knowledge of Excel.
Relevant Programs
· Graduate elective course for the MS in Strategic Analytics
Prerequisites
· RSAN101 Foundations of Data Science and Analytics
8. Materials of Instruction
a. Required Texts
· Winston, W. (2009). Mathletics: How gamblers, managers, and sports enthusiasts use mathematics in Baseball, Basketball, and Football. Princeton, NJ. ISBN: 978-0-691-15458-9.
b. Optional Texts
· Alamar, B. C. (2013). Sports Analytics: A guide for coaches, managers, and other decision makers. Columbia University Press. ISBN: 978-0-231-16292-0.
· Moskowitz, T. & Wertheim, J. (2012). Scorecasting: The hidden influences behind how sports are played and games are won. Three Rivers Press. ISBN: 978-0-307-59180-7.
· Peta, J. (2014). Trading Bases: How a wall street trader made a fortune betting on baseball. NAL. ISBN: 978-0-451-41517-2.
c. Required Software
· Microsoft Excel w/ Data Analysis Tool Pack
c. Topic Notes and Assignments
· Weekly required and optional topic notes, available on the course site (in LATTE)
· Two assignments, available on the course site (in LATTE)
d. Online Course Content
This section of the course will be conducted completely online using the Brandeis LATTE site.
The site contains the course syllabus, assignments, discussion forums, links/resources to course-related professional organizations and sites, and weekly checklists, objectives, outcomes, topic notes, self-tests, and discussion questions. Access information is emailed to enrolled students before the start of the course.
9. Overall Course Outcomes
At the end of the course, students will be able to:
· Develop problem solving and critical thinking abilities as related to sports analytics
· Apply basic statistical concepts and their applications in the sports analytics world
· Utilize a broad survey of the performance analysis methods and analytics used in elite team and individual sports
· Develop the ability to recognize, formulate, and analyze the decision-making process in elite sports
· Mine websites to find data needed to make decisions
· Develop analysis and recommendations to support decisions in elite sports
10. Course Grading Criteria
· Weekly Discussions / Online Participation (30%, 3% per week)
All student participation will be done online via LATTE. Each weekly block has a page that includes "Discussion Questions". This page describes the topics for discussion related to the course materials posted that week.
To meet the minimum requirements for the Participation component of the grade, students will be expected to complete the following during weeks 1 through 10 of the course:
o Respond to discussion questions on the relevant topics each week. Post an original response to one topic by end of day Saturday, midnight EST, and to another by end of day Monday, midnight EST (if the week has two discussion questions). These posts will be evaluated using the following criteria:
o Answers all questions asked and follows all directions specified in the topic description.
o Includes shared experiences and/or related concepts to the topic notes and readings as appropriate (this is in addition to answering the question). This information is important to our discussions. Note that all sources should be cited (refer to the Research Help > Citing Sources” link in the LATTE Resources block)
o Includes references beyond the assigned readings (required for original responses - this research is critical to expanding our knowledge-base)
o Uses good grammar/spelling/format and cites sources as appropriate.
o Provides sufficient detail; original responses should include a minimum of 300 words. Some topics require lengthier responses in order to answer all of the questions.
o Post at least 2 other substantive replies to the discussions each week by end of day Tuesday, midnight EST. These messages are replies to the original response messages of others, or replies to someone else’s reply message. The assumption is that you will read through the posts of your classmates to enhance your learning; reply to those of your choice, based upon your own experiences and insights. These posts will be evaluated using the following criteria:
o Provides substantive comments (beyond an "I agree" post) with follow-on points or questions to extend the conversation. Substantive replies should include a minimum of 200 words.
o Uses good grammar/spelling/format and cites sources as appropriate.
o Uses personal experiences/research to expand on the original post or offers new insights into the discussion.
o Posting of discussion messages needs to be done in a timely manner so that others in the class have sufficient opportunity to review these and provide replies. You are required to post messages on three different days of the course week. While you may post all the required original responses and replies before the due dates, it is important for you to be involved in the discussions throughout the week.
To summarize, the online participation grade for each week is based on the following requirements:
Weekly Requirement / Portion of Weekly Participation GradePost Original response #1 by Saturday Night / 30%
Post Original response #2 by Monday Night / 30%
Post Substantive reply #1 by Tuesday Night / 15%
Post Substantive reply #2 by Tuesday Night / 15%
Post messages to the weekly discussions forum on three different days / 10%
Each week, the online participation in these discussions contributes 3% to the overall course grade. Over ten weeks, this amounts to 30% of the overall course grade.
As stated, the above criteria reflect the minimum requirements expected of each student. Only students who exceed this standard and demonstrate exceptional comprehension and application of the course subject matter can earn a grade of B+ or better. Timely participation is important to ensure that everyone has the necessary input from others to complete their own work.
· Assignments (40%)
There are 2 assignments during the semester. Each is worth 20% of the course grade. The submission of each assignment is due by Tuesday at midnight in the week it has been assigned.
· Research Paper (20%)
Concepts reviewed in the class will be demonstrated through a research project that will include analysis culminating in a comprehensive case study. Each student will write a research paper on a topic they will select during the second week of class related to Sports Analytics.
The Research Paper should address and fully answer the following questions:
1) What were the main points that the topic addresses? (This includes any relevant history and context.)
2) What were the drivers behind this topic?
3) What are the benefits and risks of this topic?
4) What solutions does the topic deliver?
5) Why should this topic be implemented or adopted at this time?
The research paper will be a minimum of 1000 words in length, double-spaced, with a font no larger than 12 pt. The research paper will be due on the last day of Week 9.
The overall grade distribution is as follows:
Percent / Component30 % / Weekly Discussions / Online participation
40 % / Assignments (2)
30 % / Research Paper
100% / Total
II. Weekly Information
On the course site, the home page contains 10 weekly blocks, one for each week of the course. Within each weekly block on the home page, you will find information and resources about the activities for each week:
· Overview: Checklist, Objectives and Outcomes
· Discussions
· Topic Notes & Other Required Readings
· Additional Readings
· Assignments / Assessments
Initially, some of these items (related to discussions, assignments or assessments) will be hidden on the course home page. As we come to the appropriate point in the course, they will become visible and available. A schedule for availability is included within this syllabus.
All of the items listed in the checklists are required for this course.
The following pages of this syllabus present a summary of the weekly objectives, outcomes, readings, assignments, and assessments.
Week 1 / Sports Analytics Overview and Basic Statistics 09/14/16—09/20/16Objectives / * Detail an understanding of the history of sports analytics
* Explain the role that analytics plays in the decision making process
* Describe basic statistical methods and tools used to support sports analytics
Outcomes / * Develop a foundation in Sports Analytics
* Describe the high-level concepts of Sports Analytics
* Identify the basic statistical methods used to provide analysis to decision-makers
Readings / * Alamar: Chapter 1
* Week 1 Topic Notes and Readings
* Week 1 Additional Readings
Assignments / Assessments / Self-Assessments / * Complete the Academic Integrity Agreement
* Introduce yourself within the Introduce Yourself forum
* Week 1 Discussion Topics (3%)
* Begin Research Paper Topic Analysis (Due Tue. Week 2)
Week 2 / Baseball Decision Making 09/21/16—09/27/16
Objectives / * Detail an understanding of baseball rules and strategy
* Perform an analysis of bunting and base-stealing strategies
* Analyze streaks
* Demonstrate the application of simulation
* Determine the win probability and player value add
Outcomes / * Identify baseball rules and strategy decisions
* Explain the impact of a player addition on win probability
* Identify statistical methods commonly used in baseball analysis
Readings / * Winston: Chapters 1-17
* Week 2 Topic Notes and Readings
* Week 2: Additional Readings
*
Assignments / Assessments / Self-Assessments / * Week 3 Discussion Topics (3%)
* Summary of proposed research topic and why you chose it. Due by Tuesday, Week 2
*
Week 3 / Basketball Decision Making 09/28/15- 10/04/16
Objectives / * Determine which basketball team is the best
* Analyze team offense to determine which team is the best
* Detail how to account for the strength of schedule or strength of field
* Demonstrate the application of statistical regression models
Outcomes / * Identify basketball principles and strategies
* Identify key metrics and analyses used to rate and rank basketball teams
* Articulate statistical methods commonly used in basketball analysis
Readings / * Winston: Chapters 28-37
* Week 3 Topic Notes and Readings
* Week 3 Additional Readings
Assignments / Assessments / Self-Assessments / * Week 3 Discussion Topics (3%)
* Assignment #1: Player contract or sponsor negotiations (part 1). Due by Tuesday Week 5
Week 4 / Football Decision Making 10/05/16—10/11/16
Objectives / * Detail an understanding of football rules and strategy
* Perform an analysis of run vs pass, or go-for-it strategies
* Determine the win probability and player value add
Outcomes / * Identify football rules and strategy decisions
* Explain the impact of a player addition on win probability
* Identify statistical methods commonly used in football analysis
Readings / * Winston: Chapters 18-27
* Week 4 Topic Notes and Readings
* Week 4 Additional Readings
Assignments / Assessments / Self-Assessments / * Week 4 Discussion Topics (3%)
Week 5 / Golf Decision Making 10/12/16—10/18/16
Objectives / * Measure golf performance
* Determine optimal golf strategies
* Demonstrate the application of simulation
Outcomes / * Identify golf rules and strategy decisions
* Explain the impact of analytics on match-play
* Identify shot selection, lay-up, and go-for-it strategies
* Identify statistical methods commonly used in golf analysis
Readings / * Every Shot Counts, chapters 5 and 8
* Week 5 Topic Notes and Readings
* Week 5 Additional Readings
* Assignment #2: Player contract or sponsor negotiations (part 2). Due by Tuesday Week 7
Assignments / Assessments / Self-Assessments / * Week 5 Discussion Topics (3%)
* Submit Assignment #1: Player contract of sponsor negotiation (part 1) (20%)
Week 6 / Fantasy Sports 10/19/16—10/25/16
Objectives / * Explain draft strategies
* Detail an understanding of daily leagues
* Describe how to account for variability
* Demonstrate how to predict player performance
Outcomes / * Describe draft strategies and impact on team performance
* Explain how to account for variability
* Demonstrate how to predict player performance
Readings / * Winston: Chapters 38-51
* Week 6 Topic Notes and Readings
o Week 6 Additional Readings
Assignments / Assessments / Self-Assessments / * Week 6 Discussion Topics (3%)
Week 7 / Data Visualization 10/26/16—11/01/16
Objectives / * Demonstrate how to visualize data to support decision making
* Explain the applicability of various software packages like Court Vision use in sports analytics
Outcomes / * Demonstrate effective data visualization techniques for presentation of sports analytics data
* Describe the capabilities and usage of sports analytics software packages
Readings / * Week 7 Topic Notes and Readings
* Week 7 Additional Readings (optional)
Assignments / Assessments / Self-Assessments / * Week 7 Discussion Topics (3%)
* Submit Assignment #2: Player contract of sponsor negotiation (part 2) (20%)
Week 8 / The Business of Sports Analytics 11/02/16—11/08/16
Objectives / * Describe the management and business of sports analytics
* Demonstrate an understanding of sports analytics on player value
Outcomes / * Explain how sports analytics impacts the business of a sports team or individual
* Describe the role that sports analytics plays in determining player value and compensation
Readings / * Week 8 Topic Notes and Readings
* Week 8 Additional Readings
Assignments / Assessments / Self-Assessments / * Week 8 Discussion Topics (3%)
* Begin to finalize Research Paper (Due Tuesday, Week 9)
Week 9 / Sports Analytics and the Media 11/09/16—11/15/16
Objectives / * Demonstrate an understanding of attitudes about sports analytics
* Detail the impact of sports analytics on sports coverage
* Explain how media coverage impacts player value
Outcomes / * Explain the difference that analytics versus experience plays in the decision making process
* Explain how sports analytics has impacted the way sports is covered and reported by the media
* Explain how positive or negative media coverage impacts a player or team
Readings / * Week 9 Topic Notes and Readings
o Week 9 Additional Readings
Assignments / Assessments / Self-Assessments / * Week 9 Discussion Topics (3%)
* Final Research Papers due (20%) Due by Tuesday, Week 9
Week 10 / Sports Analytics and Technology 11/16/16—11/22/16
Objectives / * Demonstrate an understanding of player tracking
* Describe the future of technology in sports analytics
Outcomes / * Explain how players are tracked and scored
* Describe the emerging trends in Sports Analytics
* Articulate the possible future Sports Analytics challenges
Readings / * Week 10 Topic Notes and Readings
o Week 10 Additional Readings
Assignments / Assessments / Self-Assessments / * Week 10 Discussion Topics (3%)
III. Course Policies and Procedures