How Holiday Weekends Skew RV Park Revenue Projections

The answer: a park that's full on July 4th weekend can still average 45-55% occupancy for the year, and investors who anchor their projections to the holiday number instead of the annual number consistently overpay. Holiday weekends are real revenue, but they're a thin slice of the calendar. The mistake is letting a great August weekend set the tone for a 12-month pro forma.

Why Peak Weekends Distort the Picture

RV parks fill up around Memorial Day, July 4th, Labor Day, and sometimes a few fall foliage or hunting-season weekends. During those stretches, occupancy can sit near 100% and rates jump 20-40% above the regular nightly rate. Sellers and brokers often build pro formas using an "annualized" run rate based on what the park earned during its three or four best weekends. That math looks great on paper. It falls apart the moment you check occupancy in February.

Seasonality in this asset class is not a minor variable, it's the defining one. A park in a seasonal climate might run near capacity for 10-14 weeks a year and sit at 15-25% occupancy the rest of the time. If you want the full breakdown of why that swing happens, this look at summer versus winter occupancy patterns walks through the drivers park by park.

The Numbers That Actually Matter

Cap rates on RV parks typically run 7-12%, wider than most commercial real estate, because the cash flow is operationally intensive and the revenue is uneven month to month. That spread exists precisely because a buyer has to underwrite the whole year, not just the peak.

Here's where it gets tricky for growth assumptions. Forecast occupancy growth across the industry is flat, running 0-1% a year through the rest of the decade. The post-pandemic surge in RV travel, when occupancy spiked and rates followed, was an anomaly, not a new baseline. Investors who model 5-8% annual revenue growth off a 2021 or 2022 comp are extrapolating from a period that isn't coming back the same way.

• Peak weekend rate: useful for setting your ceiling, not your average.

• Annual average occupancy: the number that should drive your revenue line.

• Revenue growth assumption: should be modeled at 0-1% a year, not pandemic-era spikes.

What a Realistic Model Looks Like

Take a 60-site park charging $55 a night in peak season and $35 in shoulder and off-season. If you assume 95% occupancy for 10 peak weeks, 50% for 20 shoulder weeks, and 20% for the remaining 22 weeks, your blended annual occupancy lands closer to 45%. Run that math and compare it to a naive model that just annualizes the peak rate at 95% occupancy year-round. The gap between those two numbers is often 40-60% of projected gross revenue. That gap is where deals go bad.

This is also why smart underwriting doesn't lean on rate growth or occupancy growth to make the deal work. It leans on margin improvement and value-add instead, things you actually control: cutting utility waste, renegotiating vendor contracts, adding metered electric, or converting underused tent sites into full-hookup RV sites. Since top-line growth is expected to stay flat, NOI growth has to come from operations, not from betting the market gets stronger.

Diversify the Revenue Streams, Not Just the Assumptions

One way to reduce dependence on peak-weekend swings is to build revenue streams that aren't tied to nightly transient traffic at all. Site rentals are the obvious one, but private lot leases, long-term monthly stays, and amenity fees (laundry, propane, firewood, dump station access) all add revenue that holds up in the off-season. A park with 20% of its sites on annual leases has a much steadier baseline than one that's 100% dependent on weekend travelers. If you want to see how operators fill the calendar outside of peak season, this post on off-season occupancy strategies covers specific tactics that shift the annual average up.

The Honest Tradeoff

A pro forma built on holiday weekend rates will always look more attractive than one built on realistic annual averages. That's the tradeoff: the accurate model is less exciting, but it's the one that survives due diligence, lender scrutiny, and an actual winter. Buyers who get burned usually aren't fooled by bad data, they're fooled by good data applied to the wrong 10 weeks of the year.

If you're evaluating a deal and want a second set of eyes on whether the projections reflect a full-year average or a cherry-picked peak, reach out through the contact page at Invest With Zac and we can walk through the numbers together.