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15.S50 | January IAP 2015 | Graduate

# Poker Theory and Analytics

### Course Overview

This page focuses on the course 15.S50 Poker Theory and Analytics as it was taught by Kevin Desmond during IAP 2015 .

This course takes a broad-based look at poker theory and applications of poker analytics to investment management and trading.

MIT Sloan News published an article on how Kevin Desmond links poker strategy to risk management in this course: Game Theory: What Poker and Finance Have in Common.

### Course Outcomes

#### Course Goals for Students

- Create an environment for study of poker theory without the need for real-money wagering.
- Develop the basic foundation for decision-making in poker.
- Allow students to assess their own level of play and have a framework for improvement.
- Provide an understanding of the current poker environment and how students might leverage talent for poker in the future.

#### Possibilities for Further Study/Careers

Management and leadership positions, finance, trade, global markets. The skills learned in this course are especially good for careers with high-pressure decision-making.

### Instructor Interview

> "I think there are a lot of ways for students to extract the benefits from poker without the need to risk money…"

—Kevin Desmond

In the following pages, Kevin Desmond describes various aspects of how he taught 15.S50 Poker Theory and Analytics.

- Instructor Background and Motivation for Teaching the Course
- Gameplay, Connections and Contributors
- Challenges and Learning Opportunities

### Curriculum Information

#### Prerequisites

Permission of the instructor

#### Requirements Satisfied

Graduate subject credit

#### Offered

Offered during IAP when an instructor is available to teach the course

### Assessment

The students’ grades were based on the following activities:

- 1/3 Gameplay: cash-in 1+ or play 10+ Daily Turbos
- 1/3 Casework: pass all three cases
- 1/3 Attendance: attend at least 8 of 11 lectures

#### Instructor Insights on Assesment

Assessment in this course was an interesting puzzle. Poker is inherently a game where the results are not perfectly correlated with skill, but it is not in line with MIT’s academic standards for course credit to be determined probabilistically. However, gameplay was an important learning tool and the students needed to be incentivized to play their best. The solution was to split into two leagues, one for credit, and one for prizes, where students would earn credit based on volume of play, but earn prizes based on success. This would ensure every student had the capacity to earn credit in reasonable time. In addition to gameplay, the homework assignments were key to assessing the students’ understanding and ability to implement concepts taught during lectures.

### Student Information

#### Enrollment

About 150 students

#### Breakdown by Year

The breakdown of student in this course was about 60% graduate students, 40% undergrads.

#### Breakdown by Major

The graduate students were about 50% Management, 50% Engineering/Math/Science. The undergraduates were about evenly split among years and primarily from Engineering. A small number of students were visitors from other universities.

#### Typical Student Background

Students primarily had an interest in competitive games and practical applications of statistics. Some students intended to work in areas where poker knowledge was critical (trading or gaming industry), whereas other students had a more academic or recreational interest in poker. Most students had a strong background in statistics/math.

#### Ideal Class Size

The ideal class size is around 100-300 students. Since the class is heavily focused on gameplay, the goal is for students to be playing against a mix of familiar players and new opponents. By the end of the course, most students had a general level of familiarity of the different playing styles of students in the class.

### How Student Time Was Spent

During an average week, students were expected to spend between 19.5 and 24.5 hours on the course, roughly divided as follows:

#### In Class

The majority of in-class time was spent reviewing core concepts and solving example questions. Lecture attendance was mandatory for enrolled students and optional for listeners.

#### Out of Class

Outside of the classroom, a significant amount of time was spent playing poker in the online league, hosted by PokerStars. The average player played approximately 5000 hands of poker (the equivalent of about a year’s worth of live play). In addition, each of the three homework assignments required about 1-2 hours of work. For some students, about 2 hours per week was spent in review sessions.

### Course Team Roles

#### Instructor

Usually a graduate student with a background in professional poker.

#### Faculty Advisor

Faculty sponsor who generally oversees the course, but doesn’t necessarily have an active role in teaching sessions.

## Course Info

##### Instructor

- Kevin Desmond

##### Departments

- Sloan School of Management

##### As Taught In

January IAP 2015

##### Level

Graduate

##### Topics

- Business
  - Management
- Mathematics
  - Probability and Statistics

##### Learning Resource Types

theaters Lecture Videos
notes Lecture Notes
co_present Instructor Insights
assignment Problem Sets
Problem Set Solutions

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