AFL/VFL Performance Analyst — Video, Data & Development

Hawthorn Football Club Limited; City of Monash; On-site; AUD 65,000 - 90,000; Full time

Job summary

Hawthorn Football Club Limited is seeking an entry-level football performance analysis/ video coding analyst to support AFL/VFL development pathways. You will work with AFL coaches to identify priorities, produce data-driven insights, and maintain organized development records.

Proficiency in Sportscode/Hudl, Champion Data, and data visualization tools (Tableau/Power BI/Shiny) will be valued, along with experience handling large datasets in Python or R.

Qualifications

• Entry level experience in football performance analysis or video coding.
• Understanding AFL–VFL talent pathway.
• Proficient in Sportscode/Hudl, Champion Data, and presentation tools.
• Comfort with large datasets using Python or R scripting.

Responsibilities

• Lead the analysis of AFL-listed players at Box Hill VFL games, capturing, live-coding, packaging match vision and data for AFL Development Coaches and player review.
• Work alongside AFL development coaches to identify review priorities, communicate practical insights, whilst maintaining an organised record of player development themes.
• Support the AFL analysis team with ad-hoc projects, data preparation, clip generation, and presentations, including attending AFL training sessions and department meetings as required.
• Manage secure, well-structured analysis databases and vision archives while driving continuous improvements to development workflows.

Skills

Football analysis

Video coding

Python

R scripting

Data visualisation

Communication skills

Multidisciplinary teamwork

Tools

Sportscode/Hudl

Champion Data

Tableau

Power BI

Shiny

Job description

Hawthorn Football Club Limited is seeking an entry-level football performance analysis/ video coding analyst to support AFL/VFL development pathways. You will work with AFL coaches to identify priorities, produce data-driven insights, and maintain organized development records.

Proficiency in Sportscode/Hudl, Champion Data, and data visualization tools (Tableau/Power BI/Shiny) will be valued, along with experience handling large datasets in Python or R.