Six criteria, one market anchor and a single formula. We walk through a US pre-seed example to the dollar and show where the method helps and where it misleads.
The Scorecard valuation method starts from the average pre-money valuation of recently funded companies in a startup’s region, then moves that number up or down depending on how the startup compares with an average company on six criteria. It needs no revenue and no full financial model. Angel investors have used it for more than twenty years, and it is one of the five methods in every Equidam valuation.
What is the Scorecard valuation method?
The method was written by angel investor Bill Payne. In his own account, he first wrote it up in May 2001, detailed it in his 2006 book, saw the Ohio TechAngels adopt it as the “Bill Payne Method” in 2008, and renamed it the “Scorecard Method” in 2010 for an Angel Capital Education Foundation workshop (Payne, Scorecard Valuation Methodology, 2011 revision). It is also called the Benchmark Method.
Payne describes it as comparing the target company “to typical angel-funded startup ventures” and adjusting “the average valuation of recently funded companies in the region” (Payne, 2011). So the Scorecard is mainly a comparison rather than a forecast. Apart from a rough view of revenue and market size three years out, it rates what exists today rather than what a spreadsheet says will happen.
How does the Scorecard method work?
There are three steps.
- Set the anchor: the average pre-money valuation of comparable funding rounds in the startup’s country.
- Score six criteria, judging for each whether the startup is stronger or weaker than the average company behind that anchor.
- Multiply the anchor by one plus the weighted sum of the scores.
In Equidam, the formula is:
Pre-money valuation = Average valuation × (1 + Σ weight × score)
A score of 0 means “the same as the average comparable company”. Positive scores mean a better position from an investor’s point of view, negative scores a worse one.
You can check the formula against our public sample valuation report (p.9). The sample company has a US average of $6,880,000 and a weighted score sum of 0.74375, and $6,880,000 × 1.74375 gives the reported Scorecard result of $11,997,000.
Where does the average valuation come from?
Payne’s instruction was to find “the average pre-money valuation of pre-revenue companies in the region and business sector of the target company,” though he added that “in most regions, the pre-money valuation does not vary significantly from one business sector to another” (Payne, 2011). We compute it.
Our anchor is the average pre-money valuation of angel, pre-seed and seed rounds in each country over the last 30 months, from Crunchbase round data, with outliers removed (sample report, p.21; Data Sources). Countries with too few local rounds fall back to their sub-region, and we refresh the anchors twice a year. The July 2026 update drew on 4,606 rounds (Parameters Update P6.3), and every country’s current value is in the P6.3 average and maximum valuations table. For the United States, the Scorecard average is $6,450,000 (Equidam internal data, parameters effective July 2026).
The anchor pools all industries in a country, which is Payne’s observation put into practice. Separating a strong company from a weak one is left to the six criteria.
What are the six criteria, and why these weights?
Equidam uses six criteria with these default weights (sample report, p.9). Each one is built from traits taken from the founder’s answers to our questionnaire, and the full trait list is in the report’s appendix (p.21).
- Strength of the team, 30%: traits such as founder time commitment, years of industry experience, and business and managerial background.
- Size of the opportunity, 25%: expected revenue in year three, market size in three years, and the geographic scope of the business.
- Strength and protection of the product or service, 15%: how far the product has been rolled out, customer loyalty, and IP protection.
- Competitive environment, 10%: the level and quality of competition, the company’s advantage over it, and barriers to entry.
- Strategic relationships with partners, 10%: how strong the company’s relationships with key partners are.
- Funding required, 10%: how much capital the company needs for its stage. Needing less counts as the better position.
The weights add up to 100% (one widely read guide lists weights that sum to 98%). They are defaults, and a founder can change them in the platform if a criterion matters more or less for their business.
Team gets the largest weight because that is what investors say drives their decisions. In a survey of 885 venture capitalists, Gompers, Gornall, Kaplan and Strebulaev found that VCs see the management team as “somewhat more important” than business characteristics such as product or technology. In the working-paper version, 47% of VC firms named the team as the single most important factor (NBER working paper 22587). Payne put it more bluntly: “A great team will fix early product flaws, but the reverse is not true” (Payne, 2011).
The evidence does not all point one way. Kaplan, Sensoy and Strömberg followed 50 VC-backed companies from business plan to IPO and found that business lines stayed stable while management changed a lot. They concluded that investors should, at the margin, “place more weight on the business (‘the horse’) than on the management team (‘the jockey’).” We keep the team at 30% because it reflects how early-stage investors decide, but if your edge is the business itself, that paper supports your case.
Scoring happens at the trait level. A trait scores 0 if it matches the assumed average, more if it is better from an investor’s point of view, and less if it is worse. The trait scores add up to the criterion score (Help Center: Scorecard). In our published examples, criterion scores run from -0.25 to +1.5 (Help Center; 2026 sample report, p.14), and the example below stays inside that range.
Scorecard method example: how would a US pre-seed startup be valued?
Take Frostline, a hypothetical US pre-seed company building wireless temperature sensors and monitoring software for refrigerated food shipments. Two founders work on it full time, one with eight years in food logistics and a previous startup behind her. It has a working prototype in testing but no patents yet. The market is large, competition is about average for the space, it has signed a pilot with one regional refrigerated-freight carrier, and it will need a fairly large amount of capital for manufacturing before it earns revenue.
Against the average US round, Frostline might score like this:
| Criterion | Weight | Score | Weight × score | Effect on valuation |
|---|---|---|---|---|
| Strength of the team | 30% | +0.75 | +0.2250 | +$1,451,250 |
| Size of the opportunity | 25% | +0.50 | +0.1250 | +$806,250 |
| Product/service strength and protection | 15% | -0.25 | -0.0375 | -$241,875 |
| Competitive environment | 10% | 0.00 | 0.0000 | $0 |
| Strategic relationships with partners | 10% | +0.25 | +0.0250 | +$161,250 |
| Funding required | 10% | -0.25 | -0.0250 | -$161,250 |
| Total | 100% | +0.3125 | +$2,015,625 |
The arithmetic, end to end:
- Weighted sum: 0.2250 + 0.1250 – 0.0375 + 0 + 0.0250 – 0.0250 = 0.3125
- Multiplier: 1 + 0.3125 = 1.3125
- Scorecard valuation: $6,450,000 × 1.3125 = $8,465,625
- Check: $6,450,000 + $2,015,625 = $8,465,625
The team’s +0.75 adds $1,451,250 by itself, while the early product and the large capital need take away $403,125 between them. Our Checklist method article values the same company with the second qualitative method. On the Checklist method, Frostline comes out at $7,097,500 against a $17M maximum. At development-stage weights, the two qualitative methods together contribute $4,668,938 of Frostline’s blended valuation.
How does that compare with what pre-seed startups are valued at today?
The H1 2026 Valuation Delta puts US pre-seed companies valued on Equidam at $5.16M, against a global median of $5.20M. Frostline’s Scorecard result is higher than that, and the gap is expected.
The two numbers measure different things. The $6.45M anchor is the average of closed angel, pre-seed and seed rounds in the US, so it includes seed deals and is an average rather than a median. The Valuation Delta figures are the results of full five-method Equidam valuations for pre-seed companies preparing their first institutional round, not prices paid in closed rounds. And Frostline scores above average on three of the six criteria and below on two. The Valuation Delta hub has the full series back to 2019.
How sensitive is the result?
The result is sensitive to two inputs.
The first is the scores. Moving the team score by one +0.25 step changes the valuation by $483,750 (0.30 × 0.25 × $6,450,000).
The second is the anchor, and it matters more. The result scales one for one with the average: a 10% lower anchor gives a 10% lower valuation, whatever the scores. Before our July 2026 update, the US average was $6,590,000 (P6.3 table). The same scores on that anchor would have produced $8,649,375, which is $183,750 more for an identical company.
What happens to the Scorecard result in a full Equidam valuation?
Equidam blends the Scorecard with four other methods: the Checklist method, the Venture Capital method, and two discounted cash flow methods. Each one’s weight depends on the company’s stage (sample report, appendix p.20).
The Scorecard’s default weight is 38% at the idea stage, 30% at development, 15% at the startup stage and 6% at expansion. At growth and maturity it drops to 0%, and the Checklist method follows the same path. The VC method holds at 16% from idea through expansion, rises to 20% at growth and goes to 0% at maturity. The two DCF methods climb from 4% each at the idea stage to 50% each at maturity.
The logic, in the report’s words: qualitative information matters more “where performance uncertainty is extremely high,” and “quantitative information is more reliable in later stages” (sample report, p.20). Founders can adjust these weights too.
A company with a prototype and no revenue would typically be at the development stage. There, Frostline’s $8,465,625 Scorecard result carries a 30% weight and contributes $2,539,688 to the blended figure. The other methods supply the remaining 70%, and the final report gives a range rather than a single point.
Why blend five methods instead of using the Scorecard alone?
The Scorecard inherits whatever the market was paying and cannot see future cash flows, while the DCF methods depend entirely on projections. Side by side, no single assumption decides the result. Payne gave angels the same advice: “Best practice for angels investing in pre-revenue ventures is to use multiple methods” (Payne, Flathead Beacon, 2011).
A valuation is the bar the company has to clear next, and a transparent blend gives founders and investors a shared set of assumptions to argue about. Our methodology page and the five methods overview explain the other four methods.
How reliable is the Scorecard method, and when should you trust it less?
It is not built to find a single “true” number, and nobody should present it that way. What it does well is make the reasoning visible: this is what comparable companies raised at, this is where the company is stronger or weaker, and this is how much each point counts. An investor who disagrees can point to the exact score or anchor. Its weak spots are just as specific.
Anchors move. In our own July 2026 update, the median country’s average valuation rose 12.1% in six months, and India’s rose 26.2% (Parameters Update P6.3). Outside data points the same way: within one dataset of 3,774 angel investments, the Angel Capital Association found pre-seed valuations at the 80th percentile were 2.7 times those at the 20th (ACA, 2024).
Scores involve judgment. Payne wrote that “No two angel investors will value a company (or business plan) the same” (Payne, 2011). Scoring from concrete questionnaire answers, as we do, narrows that spread without removing it.
A weighted scorecard also lets strengths offset weaknesses, so a great team can make up for a weak market. Angels often do not decide that way. Maxwell, Jeffrey and Lévesque found that they reject opportunities with one fatal flaw before weighing anything else. The Scorecard helps price a company that passes that screen, but it cannot tell you whether it will.
Some companies fit badly. Payne’s 2019 revision says the method suits most pre-seed and seed deals “except those with very high capital requirements prior to achieving first revenues (such as some life science and energy deals)” (Payne, 2019). And if your case is that your company is far from typical, a method built on the typical company will pull you back toward the middle. As we have written before, in that situation “qualitative methods probably shouldn’t be the primary focus of your valuation” (The role of qualitative methods).
Once a company has a financial track record, cash flows say more than a comparison with average peers. That is why the Scorecard’s weight falls to 6% at expansion and 0% at growth and maturity.
How is Equidam’s version different from Bill Payne’s original?
Payne’s table has seven factors, each with a weight range: team 0-30%, size of the opportunity 0-25%, product/technology 0-15%, competitive environment 0-10%, marketing/sales channels/partnerships 0-10%, need for additional investment 0-5%, and other 0-5% (Payne, 2011). We use six criteria with fixed default weights, drop the “other” bucket, and give funding required 10%.
The scoring looks different but works the same way. Payne rates each factor as a percentage of average, for example 125% for a stronger-than-average team or 150% for a larger opportunity, multiplies each by its weight, and adds them up to get a multiplier. Our score of +0.25 is his 125%. Because the weights sum to 100%, the two approaches give the same answer.
His worked example also shows how much the anchor has moved. In 2011 he assumed a $1.5M average, based on an informal summer 2010 survey of angel groups. In 2019 he switched to a median of $4.5M, the midpoint between the Angel Capital Association’s average pre-seed ($4M) and seed ($5M) deals, which put the same example company at “just over $5.2 million” (Payne, 2019). The 2011 version printed the sum of factors as 1.075; the listed factors add up to 1.155, which is the figure the 2019 revision uses.
Scorecard vs Berkus, Risk Factor Summation and First Chicago: what is the difference?
The Berkus method adds value from zero instead of adjusting an average. Dave Berkus assigns up to $500,000 each to a sound idea, a prototype, a quality management team, strategic relationships, and product rollout or sales, for a maximum of $2 million before revenue or $2.5 million after roll-out (Berkus, 2016). Berkus himself now calls the fixed matrix “too restrictive” and suggests dividing your area’s average pre-revenue valuation by five to set the value of each element. Our Checklist method keeps the building-block idea but splits a data-driven country maximum across five weighted criteria.
Risk Factor Summation also starts from the regional average. It scores twelve risks, from management and stage of the business to litigation, reputation and exit potential, on a scale from -2 to +2, and each +1 adds $250,000 while each -1 subtracts $250,000 (Payne, Flathead Beacon, 2011).
The First Chicago method belongs to a different family. It builds a best-case, base-case and worst-case scenario, each with its own forecast (Achleitner and Lutz, 2005), assigns each a probability, and takes the probability-weighted sum as the valuation (Riethdorf, How to Value an Early Stage Company, UC San Diego startup toolkit). Because it runs on forecasts, it sits closer to DCF than to the Scorecard.
| Method | Starting point | How it adjusts | Limit on result | Fits best |
|---|---|---|---|---|
| Scorecard | Regional average valuation | Weighted scores on 6 criteria (Payne: 7) | None built in | Pre-revenue and early stage |
| Berkus | Zero | Up to $500K per element, 5 elements | $2M pre-revenue, $2.5M after roll-out | Pre-revenue only |
| Risk Factor Summation | Regional average valuation | ±$250K per step on 12 risks | None built in | Pre-revenue, as a cross-check |
| First Chicago | Scenario forecasts | Probability weights on best, base and worst case | None built in | Companies with forecastable outcomes |
More on which methods hold up: startup valuation methods to use and avoid.
What is the next step?
Inside an Equidam valuation, four other methods test the Scorecard’s view from different angles, using data from more than 160,000 companies valued (Equidam internal data) and 30,000+ public comparables across 90+ countries and 600+ industries (Data Sources).
To see how your own company would score, the Help Center guide to the Scorecard lists every trait we use. When you want the Scorecard run alongside the other four methods, with the current anchor for your country and a report you can share with investors, you can compare Equidam plans.