Two Circles / Fan Intelligence
NFL fan segmentation, Cricket Australia matchday intelligence, and cross-sport revenue drivers — built as a recruiter audition for the SVP North America. The 'I built something' email landed a positive reply within two days.
RoleAnalyst, work sample
Duration1 weekend
Year2026
StatusShipped — got a reply
The brief.
Two Circles is the analytics partner behind some of the largest sports properties in the world — NFL, Cricket Australia, F1. SVP North America Scott Tilton previously built Hookit, an AI-driven sponsorship analytics platform. This work sample was designed to land in front of a practitioner, not a recruiter.
The work.
FAN_SEGMENTATION_HEATMAP / NFLLIVE
← CasualEngagement intensitySuperfan →
SEG_A
2.4M fans · $42 LTV
2.4M fans · $42 LTV
SEG_B
820K fans · $187 LTV
820K fans · $187 LTV
SEG_C ★
94K fans · $1.2K LTV
94K fans · $1.2K LTV
How I approached it.
- Built three tabs: NFL fan segmentation (casual to superfan with LTV bands), Cricket Australia matchday intelligence (concession spend, in-venue behavior), and cross-sport revenue drivers.
- Modeled segments around engagement intensity rather than demographics — the more useful axis for sponsorship pricing.
- Used a heatmap-style segmentation grid that visually anchors the LTV story without being a stale pie chart.
The outcomes.
- Scott Tilton replied positively and forwarded the work to the hiring team.
- Now in active pipeline at Two Circles.
- The 'I built something this weekend' opening framed the entire interaction.
The stack.
Tableau
Sports analytics standard at agencies like Two Circles
Python
Synthetic data generation modeled on public benchmarks
HTML/CSS/JS
Final deliverable was an interactive HTML demo