Mostly metrics
A directional representation of how the debt portion of the cap stack has evolved over the last 25 years in private equity backed deals.
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THE METRIC THAT QUIETLY DRIVES PE DEALS
We often talk about (obsess over) valuation multiples in this newsletter. I wanted to bring in the Looking for Leverage newsletter (which I also write) to explain how debt ratios impact the velocity and size of deals getting done today.
What follows is an examination of Debt to EBITDA ratios, and more specifically, how they underpin the valuations of both mid market private equity deals as well as large take privates (like those we are seeing floated for PagerDuty and Olo, as well as past deals like Qualtrics, Smartsheet, New Relic, and Twitter).
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Private Equity Doesn’t Work Without Debt
It’s how they amplify wins without increasing the equity check… And it’s also how they get into a catastrophic pickle when rates spike or the exit window closes.
When you’re left holding the bag
Everyone talks about valuation multiples. But the metric that actually governs private equity behavior is much simpler: Debt to EBITDA ratios.
The state of this metric allows investors to get in and out, and ultimately impacts how far the valuation multiples can stretch.
Here’s how that ratio has changed over the last 25 years, and why it still defines dealmaking in 2025.
2000–2007: Loose Lending
2008–2009: The Retrenchment
2010–2019: Rebuild and Expand
2020–2022: Peak Aggression
2023–2025: The Reset
Let’s jump in.
The Leverage Cycle
Directional and for illustration purposes. We’ve seen it swing below ~4x and nearly ~8x.
2000–2007: Loose Lending
Typical Leverage: 5 to 6x
Covenant-lite structures were common.
Senior debt came from banks, mezzanine filled the gap.
Deals were underwritten to adjusted EBITDA with aggressive add-backs (you could put a lot of BS in there).
Wait, WTF is Mezzanine?
Mezzanine debt sits between senior debt and equity. It’s unsecured, higher-yielding, and often comes with equity kickers (like warrants). Think of it as the risk-seeking middle child of the capital stack — flexible, pricey, and willing to take a bet when banks won’t.
Back to our regularly scheduled timeline…
2008–2009: Retrenchment
Typical Leverage: 3 to 4.5x
The financial crisis forced lenders to pull back.
Equity contributions increased as a result.
Cash interest coverage and downside cases regained relevance.
Wait, WTF is Cash Interest Coverage?
The cash interest coverage ratio (also known simply as the cash coverage ratio) is a financial metric that assesses a company's ability to cover its interest expenses using its available cash flow.
Unlike the traditional interest coverage ratio, which utilizes earnings before interest and taxes (EBIT), the cash coverage ratio focuses on true cash flow from operations, providing a more precise picture of a company's liquidity and its ability to service debt in the short term.
It’s a litmus test for your ability to keep your head above the debt waters organically by building what you build and selling what you sell.
Back to our regularly scheduled timeline…
2010–2019: Rebuild and Expand
Typical Leverage: 5 to 6.5x
Rates stayed low.
Direct lending grew.
SaaS and recurring revenue models supported leverage over 7x.
Unitranche became popular.
Wait, WTF is Unitranche?
Unitranche is a hybrid loan that combines senior and junior debt into a single facility. Instead of having:
A first-lien term loan at, say, SOFR + 400 bps, and
A second-lien loan at SOFR + 800 bps,
A unitranche loan might be structured at a single blended rate (e.g., SOFR + 600 bps), often with fewer lenders involved and simpler documentation.
Why Did Unitranche Become Popular?
Simpler structure = faster deal execution: One agreement, one lender (or a tight club), one set of terms. That means less time negotiating intercreditor agreements and easier coordination post-close.
Private credit funds loved it: Direct lenders like Ares, Golub, and Owl Rock could offer unitranche structures to win deals, keep all the economics, and avoid sharing control with banks or mezz funds. When times are good, lenders want the whole steak, even if it’s bordering on holding too much risk.
PE sponsors preferred it: It allowed them to move quickly, reduce execution risk, and often get more flexible terms — particularly for middle-market deals.
Operators asked for it: You only need to report your financial results to one lender each period, you avoid stacking covenants from multiple parties, and if things went south you only have to work with one bank.
Back to our regularly scheduled timeline…
2020–2022: Peak Aggression
Typical Leverage: 6.5 to 7.5x, occasionally higher
Profitable SaaS deals could stretch past 8x
Capital was abundant, and interest rates were low.
Lenders competed for allocation, and wrote bold term sheets.
Sponsors pushed leverage as far as the model allowed, and sometimes further.
2023–2025: Reset
Typical Leverage: 4.5 to 5.5x
Rate hikes and weaker exits shifted the market.
Lenders became more selective.
Cash flow mattered again.
Deal structures normalized.
Where Things Stand in 2025
Most transactions are clearing at 5.0x leverage. That’s for businesses with real earnings, strong cash conversion, and squeaky clean reporting.
Premium assets with stable margins may see 6.0x, but they’re the exception.
Pre-EBITDA tech deals are being heavily structured or sidelined altogether.
Private credit is still in the game, but with stricter terms:
Tighter covenants
Larger equity buffers
Limited tolerance for pro forma gymnastics
The Capital Stack Has Compressed
In today’s environment, most deals are getting done with just the senior layer. If junior debt shows up, it’s in small doses — and it usually comes with warrants or higher equity risk.
What’s in each tier?
Senior Debt
Usually a mix of revolvers and first-lien term loans
Lower cost, secured, and comes with tighter controls
Provided by banks or private credit funds (the latter typically at 200 bps higher)
Junior Debt
Includes mezzanine, second lien, holdco notes, and seller paper
Higher risk, higher yield
Mostly disappeared post-2022 unless the business is rock solid
In prior cycles, 7x leverage often included 2 to 3x of junior capital: mezzanine, second lien, holdco notes, or seller paper.
Today, most of that is gone. Sponsors are relying almost entirely on senior debt, and even that comes with more scrutiny.
Senior lenders are holding the line at 5 to 5.5x. If junior capital appears, it’s smaller, more expensive, and usually includes warrants or other upside instruments.
The composition of the stack reflects market psychology:
In risk-on environments, junior capital expands.
In conservative markets, it vanishes.
Implications for Operators
Capital structure matters again
You can’t assume debt will show up on favorable terms. Lenders want downside cases, cash flow visibility, and execution credibility.
Equity checks are rising
With lower leverage, sponsors are funding more of the deal with equity. This affects return math, capital efficiency, and ownership dynamics.
Stretch structures are scarce
If a deal needs 6.5x leverage to pencil out, it may not be financeable. Operators must assume a lower ceiling and build their models accordingly.
Summary
Private equity hasn’t abandoned leverage, but it’s relearning discipline (whether it wants to or not).
In 2021, you could pencil in 7.5x debt and someone, somewhere would fund it.
In 2025, you’d better hope for 5.0x, and prove you deserve more.
Every model starts with a multiple. The ones grounded in reality start with a ratio.
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TL;DR: The top ten are UP week-over-week. But the overall median FELL BELOW 5x for just the fifth time in the last five years, illustrating a continued bifurcation between the best companies and everyone else.
Top 10 Medians:
EV / NTM Revenue = 17.7x (UP 1.8x w/w)
CAC Payback = 20 months
Rule of 40 = 50%
Revenue per Employee = $480k
Figures for each index are measured at the Median
Median and Top 10 Median are measured across the entire data set, where n = 143
Population Sizes:
Security & Identity = 17
Data Infrastructure & Dev Tools = 13
Cloud Platforms & Infra = 15
Horizontal SaaS & Back office = 19
GTM (MarTech & SalesTech) = 19
Marketplaces & Consumer Platforms = 18
FinTech & Payments = 24
Vertical SaaS = 18
Revenue Multiples
Revenue multiples are a shortcut to compare valuations across the technology landscape, where companies may not yet be profitable. The most standard timeframe for revenue multiple comparison is on a “Next Twelve Months” (NTM Revenue) basis.
NTM is a generous cut, as it gives a company “credit” for a full “rolling” future year. It also puts all companies on equal footing, regardless of their fiscal year end and quarterly seasonality.
However, not all technology sectors or monetization strategies receive the same “credit” on their forward revenue, which operators should be aware of when they create comp sets for their own companies. That is why I break them out as separate “indexes”.
Reasons may include:
Recurring mix of revenue
Stickiness of revenue
Average contract size
Cost of revenue delivery
Criticality of solution
Total Addressable Market potential
From a macro perspective, multiples trend higher in low interest environments, and vice versa.
Multiples shown are calculated by taking the Enterprise Value / NTM revenue.
Enterprise Value is calculated as: Market Capitalization + Total Debt - Cash
Market Cap fluctuates with share price day to day, while Total Debt and Cash are taken from the most recent quarterly financial statements available. That’s why we share this report each week - to keep up with changes in the stock market, and to update for quarterly earnings reports when they drop.
Historically, a 10x NTM Revenue multiple has been viewed as a “premium” valuation reserved for the best of the best companies.
Efficiency
Companies that can do more with less tend to earn higher valuations.
Three of the most common and consistently publicly available metrics to measure efficiency include:
CAC Payback Period: How many months does it take to recoup the cost of acquiring a customer?
CAC Payback Period is measured as Sales and Marketing costs divided by Revenue Additions, and adjusted by Gross Margin.
Here’s how I do it:
Sales and Marketing costs are measured on a TTM basis, but lagged by one quarter (so you skip a quarter, then sum the trailing four quarters of costs). This timeframe smooths for seasonality and recognizes the lead time required to generate pipeline.
Revenue is measured as the year-on-year change in the most recent quarter’s sales (so for Q2 of 2024 you’d subtract out Q2 of 2023’s revenue to get the increase), and then multiplied by four to arrive at an annualized revenue increase (e.g., ARR Additions).
Gross margin is taken as a % from the most recent quarter (e.g., 82%) to represent the current cost to serve a customer
Revenue per Employee: On a per head basis, how much in sales does the company generate each year? The rule of thumb is public companies should be doing north of $450k per employee at scale. This is simple division. And I believe it cuts through all the noise - there’s nowhere to hide.
Revenue per Employee is calculated as: (TTM Revenue / Total Current Employees)
Rule of 40: How does a company balance topline growth with bottom line efficiency? It’s the sum of the company’s revenue growth rate and EBITDA Margin. Netting the two should get you above 40 to pass the test.
Rule of 40 is calculated as: TTM Revenue Growth % + TTM Adjusted EBITDA Margin %
A few other notes on efficiency metrics:
Net Dollar Retention is another great measure of efficiency, but many companies have stopped quoting it as an exact number, choosing instead to disclose if it’s above or below a threshold once a year. It’s also uncommon for some types of companies, like marketplaces, to report it at all.
Most public companies don’t report net new ARR, and not all revenue is “recurring”, so I’m doing my best to approximate using changes in reported GAAP revenue. I admit this is a “stricter” view, as it is measuring change in net revenue.
OPEX
Decreasing your OPEX relative to revenue demonstrates Operating Leverage, and leaves more dollars to drop to the bottom line, as companies strive to achieve +25% profitability at scale.
The most common buckets companies put their operating costs into are:
Cost of Goods Sold: Customer Support employees, infrastructure to host your business in the cloud, API tolls, and banking fees if you are a FinTech.
Sales & Marketing: Sales and Marketing employees, advertising spend, demand gen spend, events, conferences, tools.
Research & Development: Product and Engineering employees, development expenses, tools.
General & Administrative: Finance, HR, and IT employees… and everything else. Or as I like to call myself “Strategic Backoffice Overhead.”
All of these are taken on a Gaap basis and therefore INCLUDE stock based comp, a non cash expense.
Please check out our data partner, Koyfin. It’s dope.
Hoping your ARR bridge ties.
CJ
