Ticketing & Hospitality Intelligence
Last updated: April 22, 2026
Ticketing & Hospitality Intelligence
Understand how a club, league or venue's ticketing operation is performing and where the upside is. CRED combines embedded-client benchmarks, public filings, and proprietary models to surface matchday economics, pricing dynamics, premium mix, capacity utilisation, and comparable venues.
Data strength at a glance
Rating scale: Strong — dense, fresh, validated. Solid — good coverage with known gaps. Partial — core fields only. Thin — custom work needed. None — not covered.
Industry | Overall rating | What it means here |
Sports & Sponsorship (clubs, leagues, venues) | Strong | The primary industry for this use case. Strongest in top European football leagues and North American major leagues. |
Media Rights & Entertainment | Solid | Ticketing feeds into broadcaster and streamer valuations; CRED surfaces matchday as one input. |
Talent & Athlete Representation | Solid | Ticketing performance is a signal of club health for advisors weighing player transfers or endorsement value. |
Investment & M&A Advisory (sports banking) | Solid | Matchday revenue and premium-mix are core inputs to sports valuation models. |
Core data — coverage, accuracy, recency
Values below are indicative ranges for mid-market+ accounts in developed markets. Ask your CRED account team for live coverage on your specific list, ICP or region.
Matchday economics
Field | Coverage | Accuracy | Recency | Notes |
Matchday revenue (absolute) | Strong (Big 5 + MLS) | 95%+ (public cos.) | Annual / quarterly | From public filings where available |
Revenue per match (modelled) | Solid | 85%+ | Seasonal | Derived from fixtures and season totals |
Season-ticket vs single-ticket mix | Solid | 80–90% | Seasonal | Modelled where not disclosed |
Premium / hospitality share | Solid | 80–90% | Seasonal | Higher confidence where premium is itemised |
Capacity utilisation | Strong | 90%+ | Matchday | Attendance / capacity |
Gate receipts vs broadcast vs commercial split | Strong (Big 5 + MLS) | 95%+ | Annual | Per public accounts |
Peer comparison
Field | Coverage | Accuracy | Recency | Notes |
Comparable clubs, same league | Strong | — | Seasonal | Side-by-side across tracked leagues |
Comparable clubs, cross-league | Strong | — | Seasonal | Normalised to local currency |
Multi-year trend | Strong | 95%+ | Seasonal | Typically 5 years |
Signals we fire for this use case
Signal | How it's detected | Typical latency |
Ticket-pricing change | Announcement / website scrape | Near-real-time |
Capacity expansion / renovation | Press + filings | Event-driven |
Premium tier launch | Press + social | Event-driven |
Attendance anomalies (year-over-year) | DS model | Seasonal |
New hospitality partner | Press | Event-driven |
What this use case does not cover
Individual fan identity or PoS-level transactions
Secondary-market pricing at the row/seat level (only public aggregates)
Concessions / F&B revenue below club-reported totals
Specific contractual terms of hospitality packages
Related use cases
Sponsorship ROI & brand activation
Sponsorship whitespace modelling
Commercial operations benchmarking
Financial analysis & valuation
Have a specific question about whether CRED can answer this for your team? Contact your CRED account team for a tailored review of coverage against your list or ICP.