Squash Club Analytics: Court Utilization and Revenue Tracking

2026-07-20 · 7 min read

Most squash clubs know peak hours are full — they feel it. What they don't know: Tuesday's actual utilization rate, revenue per court-hour, or which members are drifting. Here's what analytics reveals.

You run Wednesday evenings and Saturday mornings and the courts fill every time. But Tuesday at 11am — that's the question mark. You know roughly how busy peak is because you feel it. You don't actually know Tuesday's utilization rate, the revenue per court-hour across the week, or which membership tier is generating the most bookings. That's running on instinct when the data is there to be used.

The utilization gap most squash clubs can't see

The Racquet Sports Institute benchmarks a viable squash club at 100–150 active players per court.^[1] England currently sits at roughly 63 active players per court — below the threshold where a standalone squash facility reaches commercial sustainability.^[1] In the US, only 73 squash facilities have 8 or more courts, the minimum RSI identifies for standalone viability at competitive programming levels.^[1]

The problem isn't just underutilization. It's that most clubs don't know what their number is until the consequences show up in membership renewals or a cashflow squeeze. Court utilization tracking is the difference between making programming decisions on real data and making them on feel.

The core of how Orhuk approaches this: the [squash club management software guide](/blog/squash-club-management-software-guide) covers the full operational stack — analytics sits inside the same system that handles scheduling, billing, and waivers, so the data comes from actual bookings rather than manual entry.

The six KPIs squash clubs should track

A well-configured analytics dashboard surfaces these numbers in real time — not at the end of the month from a spreadsheet export.

Court Occupancy Rate. Booked court-hours divided by available court-hours, expressed as a percentage. Above 70% is generally considered healthy for a squash facility; below 50% indicates significant unused capacity.^[3] Track this by court and by time block — an aggregate club number hides the problem courts and the empty hours.

RevPAH (Revenue Per Available Hour). Total court revenue divided by total available hours. Industry metrics benchmarks $50/hour as a healthy threshold; below $25/hour typically indicates pricing or utilization problems worth addressing.^[3] This number is more actionable than raw occupancy because it captures what underpriced off-peak slots are actually costing you.

Sessions Per Member Per Month. The engagement metric that predicts churn. Members who drop below two sessions per month are at elevated cancellation risk; members above eight sessions are your anchor base. Track this by membership tier to see which tier is driving real engagement and which is collecting dues without building loyalty.

No-Show Rate. Booked courts that go unoccupied because a player didn't cancel. Every no-show inflates your occupancy figure while generating no revenue and blocking a waitlisted player. See [squash club no-show cancellation policy](/blog/squash-club-no-show-cancellation-policy) for how clubs enforce these rates down automatically.

Revenue Per Member. CourtReserve benchmarks the median for racquet clubs at $142/month across their platform data.^[5] Clubs generating under $100/month per member typically have either underpriced memberships or members who are paying dues but not booking — analytics diagnoses which.

Active Members Per Court. The RSI standard for top-performing squash facilities is over 60 active members per court, alongside $60+ per court-hour in revenue.^[1] A declining trend here, combined with flat membership revenue, usually means engagement is hollowing out before it shows in financials.

What peak-hour data reveals — and what it misses

Most squash operators already know peak hours are full. That part is visible without analytics. What's harder to see: the contribution margin difference between a peak-hour member booking and an off-peak guest booking, the share of off-peak courts occupied by complimentary passes versus paying players, and whether the waitlist is capturing cancelled demand or just filling up as theater.

The RSI documents a cautionary case from padel's European expansion: venues built to 80–90% peak occupancy watched overall utilization collapse to 7–8% after the market overbuilt.^[2] The operators who had granular weekday and morning utilization tracking saw the shift before it became a survival problem. The ones running on peak-hour feel saw it in their revenue numbers months later.

Off-peak hours below 25% utilization represent a programming opportunity — not just a pricing problem. Coaching clinics, junior programs, and corporate social sessions fill off-peak time with full-price bookings and often convert casual players into members.

Revenue analytics: linking court hours to actual income

The RSI benchmark for a well-programmed squash facility is over €100,000 per court per year in revenue; underperforming facilities come in below €30,000.^[1] That's a 3x range explained almost entirely by programming depth — not court quality or location.

Court rentals typically account for 55–70% of revenue at 3–4 court clubs and drop to 25–35% at 10+ court facilities as coaching, events, and retail scale up.^[1] Top-programmed facilities generate roughly 40% of total revenue from non-rental programming. If your analytics show you at 75% court-rental dependence, that's a lever worth pulling.

Dynamic pricing amplifies revenue analytics when both are connected. Anolla's platform data shows a 22–25% increase in court utilization when dynamic pricing is enabled alongside utilization tracking — though Anolla notes this figure comes from data-driven simulations rather than published operator case studies.^[4] The pricing lever is useful only if you can see which time blocks it's actually affecting.

See [squash court peak pricing strategy](/blog/squash-court-peak-pricing-strategy) for the specific pricing differential structures — 25–40% off-peak discounts — that shift demand without reducing peak revenue.

Member engagement analytics: catching churn early

Research across fitness club operators finds that members visiting at least twice a week are significantly less likely to cancel than those visiting once a week or less, and that the first 90 days represent the highest-leverage retention window — with many clubs seeing roughly half of new member churn concentrated in this period.^[3] A 5% improvement in retention rate can translate to a 25–95% increase in profitability, compounding as members renew rather than replace.^[1]

Analytics surfaces the early signals: session frequency declining month over month, no bookings in the last 21 days, membership plan downgrades. None of these require a separate retention tool if booking and membership data are already integrated — the platform that handles bookings can flag the same members who haven't been on court in three weeks.

The connection between utilization data and member retention is direct. A club tracking sessions per member can trigger a re-engagement sequence before a member decides to lapse. A club tracking only membership revenue sees the churn 30 days after the fact, in a renewal that doesn't arrive.

See [squash club membership pricing guide](/blog/squash-club-membership-pricing-guide) for how tier structure affects engagement patterns — which membership levels attract high-frequency players and which attract infrequent members paying for access they rarely use.

What squash analytics software should do — and what operators compare

Orhuk surfaces court utilization, revenue by period, member activity, and booking patterns in one dashboard — the same system that handles court scheduling, membership billing, and waivers. For squash clubs that don't want to reconcile data from three tools, consolidation matters. Orhuk's free plan includes core analytics; the Pro plan ($19.99/month) adds more granular reporting. AI-assisted setup gets most clubs live the same day they sign up.

Anolla offers AI-driven analytics with a dynamic pricing engine built in — loyalty tracking, demand forecasting, and a free tier with a 30-day full trial. The platform positions its accuracy and scheduling improvement figures as data-driven benchmarks rather than independently audited results.^[4]

CourtReserve has the deepest reporting of any racquet sports platform — detailed revenue analysis, utilization dashboards, and a free court revenue calculator. It starts at $159/month and serves 2,300+ clubs, though squash operators note that squash-specific features are secondary to the tennis/pickleball core.

Courtr positions as a "club intelligence platform" for racquet sports specifically — churn prediction, engagement scores, and community health metrics. Pricing runs $49/month (up to 4 courts) to $499/month (multiple locations).

When evaluating any platform: verify whether it breaks utilization down by court and time block (not just total club occupancy), whether it flags individual member engagement decline, and whether it exports raw data to CSV. A dashboard showing only aggregate numbers won't surface the patterns worth acting on.

If you're running squash courts alongside other facility offerings, the [squash club management software guide](/blog/squash-club-management-software-guide) covers how analytics integrates with the full platform stack operators need.

Related guides

- [Squash Club Management Software: The 2026 Operator Guide](/blog/squash-club-management-software-guide) - [Squash Court Peak Pricing Strategy: Fill Every Hour (2026)](/blog/squash-court-peak-pricing-strategy) - [Squash Club Membership Pricing: Tiers & Strategy (2026)](/blog/squash-club-membership-pricing-guide) - [Squash Club No-Show Policy: Standards and How to Enforce It](/blog/squash-club-no-show-cancellation-policy)

Sources

[1] Racquet Sports Institute — Economies of Scale in Racquet Sports Facilities (racquetsports.institute/post/economies-of-scale-in-racquet-sports-facilities) [2] Racquet Sports Institute — Squash: A Tale of Three Trajectories (racquetsports.institute/post/squash-three-trajectories) [3] EZFacility — Sports Facility Management Metrics & KPIs Guide (ezfacility.com/blog/sports-facility-management-metrics/) [4] Anolla — Best Squash Booking Software in 2026 (anolla.com/en/best-squash-software) [5] CourtReserve — 12 Free Tools for Racquet & Paddle Sports Club Operators (courtreserve.com/12-free-racquet-club-tools/)

Frequently Asked Questions

What analytics should a squash club track?

The most important metrics are court occupancy rate (target above 70%), revenue per available hour (RevPAH), sessions per member per month, no-show rate, and revenue per member. Together these give a complete operational picture — not just total bookings. Platforms like Orhuk surface these in one dashboard alongside the same system that handles court scheduling and membership billing, so the data comes from actual bookings without manual entry.

What is a good court utilization rate for a squash club?

Above 70% occupancy is generally considered healthy for a squash facility; below 50% indicates significant unused capacity. The Racquet Sports Institute benchmarks a viable squash club at 100–150 active members per court — a ratio that supports enough bookings to cover fixed costs at most facility sizes. Tracking this by court and by time block, not just as an aggregate number, is what reveals which courts and hours are underperforming.

Which squash club management software has the best analytics?

Orhuk includes court utilization, revenue, and member activity tracking built into the same system that handles scheduling and billing — free to start, with AI setup live the same day. Anolla offers AI-driven analytics with a dynamic pricing engine and a 30-day free trial. CourtReserve has the most detailed reporting of any racquet sports platform, starting at $159/month. Courtr is a racquet-sport-specific analytics platform ($49–$499/month) focused on churn prediction and player engagement scoring.