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Sport Management

Scott Powers

Assistant Professor, Sport Analytics, Statistics

Director, Hutchinson Leadership Initiative in Sport Analytics

Public Rice profile source

Average rating

3.4

37 temporary mock ratings

Difficulty

3.2

course-linked average

Courses

6

in seeded sections

Public profile

Courses taught

SMGT 373

Sport Analytics Internship 1

Internship experience for upper-level students in sport analytics.

Sport ManagementNone3 credits
3.69.9hPowers, Scott

SMGT 374

Sport Analytics Internship 2

Internship experience for upper-level students in sport analytics. Repeatable for Credit.

Sport ManagementNone1-6 credits
4.04.1hPowers, Scott

SMGT 435

Baseball Analytics

This course is designed to allow students to learn and utilize statistical analysis and data science techniques to evaluate team and individual performances in baseball. Cross-list: SMGT 535. Mutually Exclusive: Cannot register for SMGT 435 if student has credit for SMGT 535.

Sport ManagementNone3 credits
3.27.8hPowers, Scott

SMGT 495

Independent Study

Reading or research project to be determined by discussions between student(s) and faculty member(s). Must have the approval of the Chair of the Department of Sport Management and the participating faculty member. Repeatable for Credit.

Sport ManagementNone1-3 credits
3.96.3hCrossey, Diane, Gong, Hua, Haptonstall, Clark, Powers, Scott, Rackley, Steven, Stallings, Tom, Wilka, Stephanie

SMGT 499

Teaching Practicum

Advanced teaching experience for upper level students who have demonstrated a particular aptitude and interest in an area of sport management. Students assist in conducting a course in which they have previously excelled. The student will learn techniques in course management, instruction, and evaluation. The Chair of the Department of Sport Management must approve all teaching assistants. Pre-requisites: declared Sport Management major. Student must have received at least an "A-" in the course serving as the practicum. Repeatable for Credit.

Sport ManagementNone1-3 credits
4.05.3hCrossey, Diane, Gong, Hua, Haptonstall, Clark, Powers, Scott, Rackley, Steven, Stallings, Tom, Wilka, Stephanie

SMGT 535

Baseball Analytics

This course is designed to allow students to learn and utilize statistical analysis and data science techniques to evaluate team and individual performances in baseball. Cross-list: SMGT 435. Mutually Exclusive: Cannot register for SMGT 535 if student has credit for SMGT 435.

Sport ManagementNone3 credits
3.09.3hPowers, Scott

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