Part-Time AFL Development Analyst | Data & Player Growth

Comunidad Lift

Melbourne

Hybrid

AUD 41,000 - 69,000

Part time

3 days ago
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Benefits offered by this job

State-of-the-art gym facilities
Weekly Pilates classes
Parental Leave Policy
Professional development opportunities
One Club memberships to Hawthorn games

Job summary

Hawthorn Football Club is seeking a part‑time Football Performance Analyst to deliver match‑day vision and data, supporting AFL development coaches and players transitioning from VFL to AFL. You will collaborate with the VFL Analyst and contribute to broader AFL analysis projects.

Ideal candidates will have entry‑level experience in football performance analysis or video coding, with proficiency in Sportscode/Hudl, data visualization tools, and Python or R for large datasets.

Qualifications

  • Entry level experience in football performance analysis or video coding.
  • Solid understanding of AFL‑VFL talent pathway.

Responsibilities

  • Lead AFL-listed player analysis at Box Hill VFL games, live-code match vision and data for coaches and reviews.
  • Identify review priorities with development coaches and maintain organized records of player development themes.
  • Support ad-hoc projects, data prep, clip generation, and presentations including training sessions and department meetings.
  • Manage secure analysis databases and vision archives, driving improvements to development workflows.

Skills

Football performance analysis
Video coding
Strong communication

Tools

Sportscode/Hudl
Champion Data
Tableau
Power BI
Shiny
Python
R

Job description

Hawthorn Football Club is seeking a part‑time Football Performance Analyst to deliver match‑day vision and data, supporting AFL development coaches and players transitioning from VFL to AFL. You will collaborate with the VFL Analyst and contribute to broader AFL analysis projects.

Ideal candidates will have entry‑level experience in football performance analysis or video coding, with proficiency in Sportscode/Hudl, data visualization tools, and Python or R for large datasets.

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