Programming for Sports Performance

Unit code: SES6003 | Study level: Postgraduate
(One credit point is usually equivalent to one hour of study per week)
Online Self-Paced


Sport scientists and analysts deal with a variety of large and complex datasets on a daily basis. These datasets may include, for example, athlete tracking data, daily wellness questionnaire responses, race performance data and skilled performance during team-sport matches or training sessions.

In this unit students will learn a programming language (the R environment) to solve complex sport performance questions. The R environment allows for the analysis, modelling, visualisation and communication of sport performance data, in a reproducible and time-efficient manner. This unit will give students exposure to how programming languages can be used to analyse, visualise and communicate sport performance data.

Students will learn how to write code in R, to analyse common sports performance datasets and communicate results by creating interactive visualisations and reports. Students will develop R programming skills that will enable them to work with different data types, to help answer specific sport performance questions and communicate results in a visual, reproducible and time-efficient manner. Students will understand how other programming languages, including Python and SQL, may be advantageous for different sport data situations and complement programming in R.

Learning Outcomes

On successful completion of this unit, students will be able to:

  1. Compose R code to probe and assess different sports performance data types;
  2. Compute statistical analysis to interrogate sport performance questions;
  3. Interpret results and translate into recommendations for coaches, athletes and performance staff;
  4. Devise interactive visualisations and generate reproducible reports; and,
  5. Reflect on what programming language is appropriate for different sport performance situations.

Study as a single unit

This unit can be studied on its own, without enrolling in a full degree.

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For Melbourne campuses

Assessment type: Project
Grade: Pass/Fail
Students will be given different datasets and asked to import, analyse summary statistics along with code.
Assessment type: Report
Grade: Pass/Fail
Students will be given a dataset and asked to produce results and visualisations, along with a written report
Assessment type: Case Study
Grade: Pass/Fail
Students will be given an unseen dataset and specific sport performance problem, then asked to import, analyse, visualise and communicate findings

Required reading

Selected readings will be made available via the unit VU Collaborate site.

As part of a course

This unit is studied as part of the following course(s):

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