
2026-08-11 · 6 min read
Most tennis clubs have a booking policy. Few enforce it consistently. Here's the five-rule software framework that stops court hogging and protects fair access for every member.
Your tennis club probably has a booking policy. It lives somewhere — on your website, in a welcome email, in the member handbook. What it doesn't have is enforcement. When a long-tenured member books Court 1 every Tuesday and Thursday evening before anyone else gets a shot, no written policy stops that. Only software rules do.
This guide covers the four booking rules tennis club operators configure in their booking software — what each one does, what values to set, and how they interact with membership tiers. For handling what happens after someone cancels a reservation, see [How to Automate Your Tennis Club Cancellation Policy](/blog/tennis-club-cancellation-policy-automation).
In June 2026, San Francisco's Rossi Park became the subject of a viral Reddit thread. A private Meetup-style group had been collecting $250 annual dues from the public to "join" what were actually open-access municipal tennis courts — holding prime weekend morning slots by exploiting first-come-first-served access.<sup>[1]</sup> The city's fix was a new $5/hr weekend morning reservation system.
The dynamic is familiar to private club operators. CourtReserve published a dedicated resource on the "court hog" — long-tenured members who book the same prime courts at the same time every week and know exactly when slots open.<sup>[2]</sup> What stops them isn't a member email. It's four configurable rules in your booking software that apply equally to everyone, every time.
The advance booking window defines how far ahead a member can reserve a court. The most common structure at private clubs:
- Premium members — 14 days out - Standard members — 7 days out - Non-members and guests — 2–3 days out
At clubs like Advantage Tennis Clubs, this tiered window is the primary tool for controlling prime court access.<sup>[3]</sup> The gap between tiers does real work: paying members get meaningful priority without creating a permanent advantage for whoever checks the app earliest.
Pair the advance window with a booking close-off buffer — the cutoff before a session starts when new reservations stop being accepted. Many clubs set it at 30–60 minutes: after that, an open court goes to walk-ins or waitlisted players rather than new reservations.
Your booking software should let you set both values per membership tier independently. A single global advance window for all members eliminates the access benefit your premium tier is priced to deliver.
Per-day and per-week court-hour caps prevent any one member from consuming a disproportionate share of prime court time. Real club examples from public booking policies:<sup>[4]</sup>
- Kew Gardens Tennis Club (Toronto): max 2 bookings per rolling 7-day window - Davisville Tennis Club: max 2 live (future) bookings at any one time - Elmbridge public courts (UK): hard cap of 2 hours per day, year-round
A practical private club structure: 2 hours/day and 6 hours/week for standard members; 3 hours/day and 10 hours/week for premium. Non-members at 1 hour/day. These limits apply to court time booked, not court time actually played — a 2-hour reservation that ends at 90 minutes still counts as 2 hours against the daily cap.
The [tennis club waitlist system](/blog/tennis-club-waitlist-management) backfills slots that free up when members hit their cap — the two rules work together to maximize utilization without requiring staff intervention.
Concurrent and outstanding limits are related but different — and the distinction matters for enforcement.
Outstanding reservations = total future bookings a member can hold at any time. Setting this prevents the most common hogging pattern: a member holds Court 1 Monday, Court 2 Wednesday, and Court 3 Friday simultaneously as a hedge. Davisville caps members at 2 live bookings; ECCTA on PlayByPoint limits each account to 1 outstanding reservation at any time.<sup>[4]</sup>
Concurrent reservations = bookings that overlap in time on different courts simultaneously. This applies to members who book courts under their account for others. Georgetown University Recreation explicitly prohibits concurrent reservations; Marquette University forbids reservations made in another member's name for the same purpose.<sup>[4]</sup>
CourtReserve is the only major platform that publicly documents outstanding and concurrent limits as separately configurable fields per membership tier.<sup>[2]</sup> Your [membership tier structure](/blog/tennis-club-membership-tiers-guide) guides the values: premium tiers often carry 3 outstanding reservations where standard tiers cap at 1.
Peak-hour priority runs two ways: tiered advance windows (premium members book earlier, covered in Rule 1) and time-based pricing. Anolla's platform automatically adjusts court prices by time of day — peak slots cost more, which organically shifts casual play off-peak without manual scheduling rules.<sup>[5]</sup>
Guest booking rules close a common exploit: members book courts "for a guest" to work around their own hourly caps. Strong guest policy configuration:
- Guest fee collected at booking, not on arrival — $10–$20 is typical at private clubs - Full guest name required at time of reservation; booking auto-deletes if unpaid within 15 minutes - Guest court hours count against the member's daily and weekly cap — a member's 2-hour/day limit includes courts booked on behalf of guests
For how guest access integrates with broader access strategy, see [Tennis Club Guest Day Pass Management](/blog/tennis-club-guest-day-pass-management).
Orhuk (free plan + transaction fee, no monthly fee): all four rule types — advance windows by tier, daily and weekly caps, outstanding and concurrent reservation limits, guest booking with auto-charge — are configurable from one admin panel without developer involvement. Rule changes apply immediately to all new reservations. [Start free](https://orhuk.com/get-started).
CourtReserve (~$199/mo starting, as of mid-2026): the most granular rule set among court-focused platforms. Outstanding vs. concurrent reservation limits are separately configurable per tier, with per-court rule overrides and prime-time restriction layers documented in detail in the help center.<sup>[2]</sup> Best for clubs that need complex, per-court rule differentiation.
PlayByPoint (custom pricing, demo required): strong for lesson, clinic, and camp management with DUPR matchmaking integration. Booking rule granularity is lighter — CourtReserve explicitly positions itself as the platform for "complex booking rules" where PlayByPoint targets simpler workflows.<sup>[2]</sup>
Anolla (free + €11.99/mo Pro, as of mid-2026): strong on dynamic time-of-day pricing and AI-assisted scheduling. Booking cap configurability is solid for straightforward setups. Best for clubs where price-based demand management is the primary lever rather than hard reservation caps.
- [Tennis Club Management Software: A Buyer's Guide](/blog/tennis-club-management-software-guide) - [How to Reduce No-Shows at Tennis Courts](/blog/how-to-reduce-no-shows-tennis-courts) - [Tennis Club Waitlist Management](/blog/tennis-club-waitlist-management) - [Tennis Club Membership Tiers: The Operator's Pricing Guide](/blog/tennis-club-membership-tiers-guide) - [How to Automate Your Tennis Club Cancellation Policy](/blog/tennis-club-cancellation-policy-automation) - [Tennis Club Guest Day Pass Management](/blog/tennis-club-guest-day-pass-management)
[1] SFist — "Tennis Group Accused of Hogging Inner Richmond Courts Prompts New System on Weekends" — June 2026 — sfist.com [2] CourtReserve — "Controlling Court Hogs at Your Tennis and Pickleball Club" and booking settings help documentation — courtreserve.com [3] Advantage Tennis Clubs — Court Rates and Booking Policy — advantagetennisclubs.com [4] Kew Gardens Tennis Club, Davisville Tennis Club, Elmbridge Borough Council, Georgetown University Recreation, Marquette University Recreation, ECCTA — public booking policies and FAQ pages [5] Anolla — "Best Tennis Software: AI-Driven Court Management" — anolla.com