Financing a Logan, Ohio Rental: DSCR Numbers to Know

Sep 2

11 min read

Hocking Hills gorge, cave, or Logan civic landmark, no people in foreground. Wikimedia: Old Man's Cave (23085).jpg

Debt service coverage ratio underwriting on a Logan, Ohio short-term rental should start on Logan's own numbers. On an AirROI extract filed for the August 2025 through July 2026 window, typical Logan listings earned about $52,213 last year from 783 active rentals, with an average daily rate near $390, occupancy around 40.1 percent, and a RevPAR of roughly $161. A DSCR calculation built on any other city's revenue figure is not underwriting the actual property.

Columbus listings earned about $22,498 last year from 2,536 active rentals on the same window. That is a separate city, a separate file, and a separate guest pool, and it should never be blended into a Logan DSCR file. A lender packet for a Logan property should carry Logan's $52,213 figure clearly, note remaining registration items that still need confirming, and keep Columbus's $22,498 on its own clearly labeled line if it appears at all.

This page is a plain-language walk through the revenue figures a Logan DSCR file should use, the registration questions that remain open, and the seasonal pattern a lender or a borrower should expect the property's income to follow across a year. This is not legal advice. It is a summary of the underlying extract, built to help a borrower ask sharper questions of a lender, an appraiser, or an attorney before closing on financing.

Independent hosts still write most of this 783-listing market, and a borrower buying a Logan property for short-term rental use should understand that the DSCR question and the marketing question are connected. A property that qualifies on paper for adequate coverage still needs to actually reach the $52,213 typical revenue figure through real bookings, which depends on accurate, specific listing copy and a clear registration status, not just a favorable loan structure.

Where DSCR Underwriting Should Start

DSCR starts on $52,213, Logan's typical annual revenue on 783 listings, not on Columbus's $22,498 from the same window. That $52,213 figure pairs with a $390 ADR and 40.1 percent occupancy to produce a $161 RevPAR, and a borrower building a DSCR file should show a lender all three figures together rather than presenting the ADR or occupancy figure in isolation, since either number alone can overstate or understate the property's actual expected income.

Year over year, the extract shows Logan revenue down about 8.2 percent while supply is up about 35.5 percent. A conservative DSCR file should reflect that trend rather than projecting forward on last year's stronger figures, since a lender reviewing the file is likely to apply their own haircut to optimistic projections, and a borrower who has already built a conservative case is in a stronger negotiating position than one who has not.

Keeping The Revenue Trough Out Of The Coverage Ratio

A 30-night minimum-stay filter is not the same thing as a filled hole month, and a DSCR file should not model it as such. About 30.4 percent of Logan listings already run a 30-night minimum, but that setting can sit on a calendar without producing actual occupied nights, and February is the revenue hole in this sample regardless of how many listings carry a long minimum-stay filter. A lender packet that quietly assumes a 30-night filter equals filled occupancy in the slow month is overstating expected income in exactly the month that needs the most conservative treatment.

Occupancy is weakest in February in this sample, which is the same month as the revenue hole, so a DSCR file should treat February as a single, honestly modeled low month rather than smoothing it into the annual average or assuming a minimum-stay strategy has quietly solved it. A lender who sees a DSCR file that explicitly accounts for a slow February, rather than hiding it inside a flat monthly average, is looking at a more credible underwriting package.

Named Events Are Demand, Not A Coverage Ratio

Named event weekends show up in this sample as demand signals, not as occupancy proof, and a DSCR file should not lean on a single strong weekend to justify an optimistic annual revenue projection. A borrower who wants to reference a specific named local event in a lender conversation should pair it with the actual annual figures, the $52,213 typical revenue and the 40.1 percent occupancy, rather than presenting the event weekend as representative of the property's typical month.

This distinction matters because a lender reviewing a DSCR file is trying to determine whether the property can service its debt across a full year, not just during its best weekend. A file built around the honest annual figures from this sample, with named events mentioned as color rather than as the basis for the projection, tends to hold up better under a lender's own scrutiny than a file built around cherry-picked peak performance.

Two Separate Files, Two Separate Note Structures

City parcels and unincorporated county parcels near Logan are two separate files with two separate registration paths, and a DSCR packet should identify which one applies to the specific property before assembling the rest of the underwriting narrative. A parcel inside the City of Logan runs through the city's § 157.163 licensing process and the Service Director's office, while a parcel in unincorporated Hocking County follows a separate county process. Confusing the two, or assuming a city-based license covers a county parcel, is a mistake worth catching before a lender or an appraiser catches it instead.

Keeping tourism-style copy out of the column that has to pay the note is a useful discipline here. A DSCR file is a financial document, and while it is reasonable to note the property's proximity to Old Man's Cave or Ash Cave as context for demand, the coverage ratio itself should rest entirely on the $52,213 typical revenue, the $390 ADR, and the 40.1 percent occupancy figures, not on descriptive language about the surrounding attractions. A lender is evaluating cash flow, not scenery, and a file that keeps those two kinds of content clearly separated reads as more disciplined.

A Lender Packet, Assembled Line By Line

A complete lender packet for a Logan property should carry, at minimum: the $52,213 typical annual revenue on 783 listings, the $390 ADR, the 40.1 percent occupancy, the $161 RevPAR, the year-over-year trend of revenue down 8.2 percent against supply up 35.5 percent, the identification of which city or county file the specific parcel falls under, a note on remaining § 157.163 license status if the parcel is inside city limits, and remaining lodging tax confirmation with the correct county authority. Columbus figures, if referenced at all, should appear on a clearly separate line labeled as a different city's data, never blended into the Logan totals above.

Assembling the packet this way, one confirmed line at a time, gives a lender a document that is easy to audit against the underlying extract. A packet that instead presents a single blended annual revenue number, without breaking out ADR, occupancy, and RevPAR separately, or without noting which registration items remain open, asks the lender to take more on faith than a line-by-line packet does, which tends to slow down rather than speed up the underwriting conversation.

What This Page Does Not Resolve

This page summarizes the revenue and seasonal figures on the AirROI extract and flags the registration and tax items that still need direct confirmation with the City of Logan and the correct county authority. It does not calculate a specific coverage ratio for a specific loan amount, interest rate, or property expense structure, since those figures are specific to each borrower's actual financing terms and property costs, not to the market-wide extract this page is built from.

A borrower should bring the figures on this page to a lender, an accountant, or an attorney as a starting point for their own specific DSCR calculation, rather than treating any number here as a finished coverage ratio. The market-level data narrows the range of reasonable assumptions; it does not replace the property-specific and loan-specific work a full underwriting file still requires.

How Guest Origin Affects A Conservative Revenue Model

Most Logan guests arrive from Columbus, then Cincinnati, for a typical stay of about 2.4 nights, and a DSCR model should reflect that this is a short-stay, drive market rather than a long-stay or fly-in market. A conservative revenue model built around frequent short turnovers, rather than a smaller number of long stays, should account for realistic vacancy between bookings and turnover costs, both of which affect the net income a lender ultimately cares about more than the gross typical revenue figure alone.

A borrower underwriting against the roughly 2.4-night typical stay should also factor in that shorter stays generally mean more frequent cleaning and turnover cycles than a long-term or extended-stay property would require, which affects the expense side of a DSCR calculation even though it does not appear directly in this sample's revenue figures. This is a property-management cost question, not a market-data question, but it belongs in the same conversation with a lender since it affects the net cash flow available to service the debt.

Building In A Margin For The Softening Trend

Given that revenue is down about 8.2 percent year over year while supply is up about 35.5 percent, a prudent borrower should build a margin into their own coverage ratio calculation rather than underwriting to the exact $52,213 figure with no cushion. A property that comfortably covers its note at a revenue figure somewhat below $52,213 is in a stronger position than one that only covers its note if the property performs at or above the current typical figure, especially in a market where supply is growing faster than revenue.

This margin matters most for the February revenue hole. A borrower who models a full year at the average $52,213 figure without separately accounting for a weaker February may find their actual monthly cash flow tighter than the annual average suggests during that specific month, even if the annual figure clears the coverage ratio comfortably. A month-by-month cash flow view, not just an annual total, gives a more complete picture of whether the property can service debt consistently across the full calendar.

A Short Checklist Before The Loan Funds

Before closing, a borrower should have on hand a copy of the extract figures cited on this page with the source and date clearly noted, a written confirmation from the City of Logan on the specific parcel's registration status, a written confirmation of the correct county lodging tax authority for that parcel, and a month-by-month cash flow model that separately calls out the February revenue hole rather than folding it into an annual average. Each of these items closes a gap that a lender, an appraiser, or a title company is likely to ask about during underwriting, and having them ready before being asked tends to move a file through underwriting faster than scrambling to produce them after a request.

None of this replaces the guidance of a licensed lender, accountant, or attorney working the specific loan file, and the figures on this page should be treated as a starting reference drawn from a single market extract rather than a substitute for that professional review. A borrower who walks into a financing conversation already holding Logan-specific numbers, rather than generic assumptions, tends to have a more productive conversation with whoever is underwriting the loan.

Frequently Asked Questions

What revenue figure should I use for DSCR underwriting on a Logan rental?

Use Logan's own typical annual revenue figure, about $52,213 on 783 listings from the August 2025 through July 2026 AirROI extract, paired with a $390 ADR and 40.1 percent occupancy that together produce a $161 RevPAR. Do not substitute Columbus's $22,498 figure from the same window; the two cities have different guest pools and supply levels, and a lender reviewing a mismatched figure may question the entire file. Confirm your specific underwriting approach with your lender or attorney.

Why shouldn't I use Columbus numbers if it's the nearest larger city?

Columbus is a separate city with its own $22,498 typical annual revenue on 2,536 listings, a different guest pool, and a different registration process entirely. Blending Columbus figures into a Logan DSCR file misrepresents the actual property's expected income and can undermine a lender's confidence in the rest of the file. Keep any Columbus reference on its own clearly labeled line, separate from the Logan-specific figures the coverage ratio is actually built on.

Does the 30-night minimum stay setting help fill my revenue hole month?

Not automatically. About 30.4 percent of Logan listings already run a 30-night minimum, but that filter setting does not guarantee occupied nights, and February remains the revenue hole in this sample regardless of how many listings carry that setting. A DSCR file should model February conservatively based on actual occupancy data rather than assuming a minimum-stay filter has solved the slow month for a specific property.

How should year-over-year trends affect my DSCR projection?

The extract shows Logan revenue down about 8.2 percent year over year while supply is up about 35.5 percent. A conservative DSCR file should reflect that softening trend rather than projecting forward from a stronger prior year, since a lender is likely to discount an optimistic projection anyway. Building a conservative case from the start tends to produce a more credible file and a smoother underwriting conversation.

What registration items should I confirm before closing on financing?

Confirm remaining § 157.163 license requirements, remaining tourist-home spacing rules, and remaining Service Director files directly at cityoflogan.oh.gov, along with remaining lodging tax obligations through the correct county authority. These items were not fully settled in this sample and should not be treated as confirmed without a direct check. A borrower should loop in an attorney or closing agent to confirm exactly what is required before the loan funds.

Is there a contradiction in the county lodging tax information for Logan?

Yes, and it should be flagged rather than guessed past. Logan sits in Hocking County, and some source material references a Hocking County lodging tax page directly, while other material references a Brown County planning page in the same context. Since Logan is not in Brown County, that reference appears to be a data error rather than a second confirmed filing requirement, and a borrower should confirm the correct county authority directly rather than assuming either version is complete.

Can I use a single strong event weekend to support a higher DSCR projection?

No. Named event weekends in this sample represent demand, not occupancy, and should not be used to justify an above-typical annual revenue projection. A DSCR file built on the $52,213 typical annual figure, with named events mentioned only as color, holds up better under a lender's scrutiny than one that extrapolates a single busy weekend across the full year.

What's the difference between a lender packet built on Logan versus Columbus figures?

A Logan packet should show $52,213 typical revenue on 783 listings, $390 ADR, 40.1 percent occupancy, and $161 RevPAR, all specific to Logan's own market. A Columbus packet would show $22,498 on 2,536 listings from a different guest pool. The two should never be merged into one blended average; a lender reviewing a Logan property needs Logan's numbers, clearly sourced to the correct city, to accurately assess coverage.

Should my DSCR file mention the market's supply growth?

Yes, disclosing it strengthens the file's credibility. Supply is up about 35.5 percent year over year in this sample while revenue is down about 8.2 percent, meaning more listings are competing for a similar or shrinking pool of typical revenue. A DSCR file that acknowledges this trend and still shows adequate coverage under conservative assumptions is more persuasive to a lender than one that ignores rising competition entirely.

Work with Crest & Cove Creative

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