Where do the base rates come from?

Each project type's base rate is sourced from published research: Cold-start SaaS 4% (Indie Hackers / Stripe Atlas / Failory data — fraction of indie SaaS reaching $1K MRR sustained). Service business 18% (BLS small-business survival data). Content creator 6% (Patreon / Substack monetization-rate data). Mobile app 2% (Sensor Tower / data.ai monetization stats). Restaurant 30% to year 5 (BLS BED data). Book author 8% (Bowker / Author Earnings — fraction reaching meaningful sales). Nonprofit launch 12% (NCCS data). Physical product DTC 5% (Shopify / industry medians for sustained DTC brands). Agency 22% (BLS service-business survival). Each is a directional anchor against optimism bias.

Why are the multipliers capped at 0.4× / 2.5×?

Because mathematically, individual factors realistically can't move probability more than 2-3× in either direction. A complete novice (0.4×) is genuinely 60% less likely to succeed than a median operator. A deep-expertise operator (2.5×) is genuinely 2.5× more likely. Beyond those bounds, you're either misrepresenting your novice-ness or over-rating your expertise. The caps prevent the multiplication from compounding to absurd 100× lifts that don't reflect reality.

What's the 4× sanity cap on adjusted probability?

Even if every personal factor stacks at maximum (deep expertise + 3 co-founders + 24 mo runway + patient timeline), the math caps adjusted probability at 4× the base rate. Reason: multiplicative compounding produces unrealistic numbers when factors interact. A 4% base rate × 2.5 × 1.4 × 2.0 × 1.8 = 50.4% — but in reality, no startup founder is genuinely 50% likely to build a successful SaaS just because they have advantages. The cap holds the math credible. The cap applies only when the raw product exceeds 4× — sub-4× factor combinations pass through directly.

How do I pick honest scores?

Calibration: think about three peers in your domain. Score yourself relative to them, not relative to abstract '10' or 'genuine deep expertise'. Experience: have you shipped a similar project to completion before? (No = 1-3; Yes once = 4-6; Yes 3+ times = 7-9; Yes successfully + recognized = 10). Resources: how many months can you fully fund this from current savings + sources? (1-2 mo = 1-2; 6 mo = 4-5; 12 mo = 6-7; 24+ mo + income = 9-10). Timeline: how does your plan compare to base-rate norms for your project type? (Wildly optimistic = 1-3; reasonable = 5-7; conservative + buffered = 8-10).

Why is solo penalized vs co-founders?

YC data + Founders Fund data + multiple cohort studies converge: 2-co-founder teams have ~30% higher 5-yr survival rate than solo. Reasons: complementary skills, mutual accountability, capacity to handle parallel workstreams, emotional resilience during low periods. The math doesn't say solo can't work — Stripe / GitHub / many great companies started near-solo — it says base-rate-adjusted, you need stronger personal advantages to offset the team handicap. The 0.85× isn't a death sentence; it's a credibility check.

What if my project doesn't fit any type?

Use 'custom' and provide your own base rate. Where to find it: industry-association annual reports (e.g., AICPA for accounting firms), academic research on your sector, trade-press 'state of the industry' surveys, industry-survival data from BLS BED. When unsure, 5-15% is typical for entrepreneurial ventures. The honest custom rate is usually lower than your gut — base-rate-anchored thinking corrects the optimism bias every founder carries.

Should I quit if my adjusted probability is low?

Not necessarily — the calc is decision-support, not advice. Low probability + high upside (lottery-ticket situations) can still be worth pursuing if downside is bounded. Low probability + low upside is the danger zone. The calc surfaces the math; you make the call about whether the expected value (probability × outcome) justifies the cost (time, money, opportunity). Don't ignore a low number; do contextualize it.

Does this account for serial-entrepreneur lift?

Yes, via the experience score. A serial entrepreneur with 3+ shipped startups (even if some failed) honestly scores 8-10 on prior-relevant-experience — and the 2.0×+ multiplier reflects the real lift serial founders have over first-timers. 'Failure school' is a real teacher; the calc gives credit for it. The catch: you have to honestly score yourself. Founders who failed 3 times often rate themselves 'experienced' at 7+ when they should be 5 (failed at execution, not at learning).

Why no 'idea quality' input?

Because idea quality is the most over-rated factor in startup success. Marc Andreessen / Naval / many investors have written that team + execution + market timing matter far more than idea quality at the early stage. The same idea succeeds for one team and fails for another, depending on execution. Calculator captures the things that actually move the needle (experience, team, resources, timeline) and trusts that the project-type base rate already encodes 'this kind of idea, on average'. Plug in your specific personal advantages instead of arguing your idea is the exception.

How does this differ from regret-minimization-calculator?

Regret-minimization is qualitative (Bezos framing — 80-yr-old you, would you regret doing or not doing this?). Probability-of-success is quantitative (base-rate-anchored math). Pair them: regret-min handles 'is this worth pursuing for non-financial reasons?'; probability-of-success handles 'what are the honest financial / logistical odds?'. Together they map both axes of a big decision. Either alone misses half the picture.

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Probability of Success Calculator — Anchor Optimism Against Base Rates

Drop your project type, prior experience, team size, runway, and timeline realism. Calculator anchors against published base rates (cold-start SaaS 4%, restaurants 30%, books 8%, agencies 22%, etc.) and adjusts for your specific personal advantages — surfacing your honest adjusted probability and the single biggest risk in the math.

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Reviewed by CalcBold EditorialLast verified May 4, 2026Methodology

Project type

Each project type has a baked-in base rate from published research. Cold-start SaaS 4% (Indie Hackers / Stripe Atlas data); restaurants 30% to year 5 (BLS); books 8% (Bowker); apps 2% (Sensor Tower); agencies 22% (industry medians). The base rate is the historical median — what fraction of starters reached 'successful'.

Custom base rate

Only used when project type is 'custom'. Otherwise ignored. Use published research for your specific domain — most niches have at least directional data via industry reports, academic studies, or trade-association surveys. When in doubt, 5-15% is typical for entrepreneurial ventures.

Prior relevant experience

Honest score of relevant prior experience. 1: complete novice. 5: some adjacent experience (worked in the industry, shipped one similar project). 10: deep domain expertise + prior shipped projects in the space. The 5-yr rule: 5 = 'I've done this once before'; 10 = 'I've done this 5+ times'. Most founders rate themselves 7+ when they're 4 — be honest.

Team

YC data: 2-co-founder teams have ~30% higher success rate than solo. Beyond 3 co-founders, coordination cost cancels additional capacity. Solo 0.85×; solo + contractors 1.0×; 2 co-founders 1.3×; 3+ co-founders 1.4×. Co-founder fit matters more than count — wrong-fit co-founder is worse than solo.

Resource sufficiency

Resources to see this through. 1: 1 month runway, no savings. 5: 6-12 mo runway. 10: 24+ mo runway + already revenue-generating from other source. Most projects fail because they ran out of money before finding product-market fit, not because the idea was bad. Honest scoring matters — a year of runway feels like forever; it isn't.

Timeline realism

Honest timeline realism. 1: 'next month for sure'. 5: 'realistic 12-mo plan'. 10: 'patient 3-yr horizon with clear milestones'. Unrealistic timelines correlate strongly with abandonment — when month 6 doesn't deliver the month-3 promise, motivation breaks. Pad your plan 2× and rate honestly.

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What This Calculator Does

The Probability of Success Calculator anchors your optimism against published base rates by project type and adjusts for your specific personal advantages. Pick your project (cold-start SaaS, restaurant, book, agency, mobile app, content creator, nonprofit, DTC product, service business, or custom). Score your prior relevant experience, team composition, resource runway, and timeline realism. The calculator returns your honest adjusted probability — base-rate-anchored, sanity-capped, with the single largest risk identified.

Most founders carry a ~5-15× optimism bias. A cold-start SaaS founder with 4% base rate often believes their odds are 50%+ — the calculator’s job is to surface the gap between intuition and the defensible math. The output isn’t advice on whether to pursue; that’s your call. The output is the honest number to compare against expected value (probability × outcome) and regret (would the 80-yr- old you regret skipping this?). All three together make better decisions than intuition alone.

The Math — Base Rate × Personal Multipliers

Base rates are the historical median for each project type — the fraction of starters who reached the domain’s definition of success. Cold-start SaaS 4% (Indie Hackers / Stripe Atlas / Failory data — fraction of indie SaaS founders reaching $1K MRR sustained). Restaurants 30% to year 5 (BLS data). Book authors 8% (Bowker / Author Earnings — fraction with meaningful sales). Mobile apps 2% (Sensor Tower / data.ai monetization stats). Each is sourced and directionally accurate; specific niches within each category vary, but the order of magnitude holds.

Personal multipliers are bounded for credibility. Experience tops at 2.5× — even deep-domain experts with prior shipped projects realistically lift probability ~2.5×, not 10×. Team tops at 1.4× — beyond 3 co-founders, coordination cost cancels additional capacity. Resources top at 2.5× — runway matters but you can’t buy product-market fit. Timeline tops at 1.8× — patient horizons help but don’t compound infinitely. The product can’t exceed base × 4 (sanity cap) — even with all advantages stacked, you can’t be 10× more likely than median to succeed at a given project type.

Worked Example — Solo Cold-Start SaaS Founder

Plug defaults: cold-start SaaS, prior experience 5, solo, resources 5, timeline 5. Base rate = 4%. Multipliers all 1.0 (median across the board). Adjusted probability = 4% × 1 × 0.85 × 1 × 1 = 3.4%. Top risk: team (0.85× — solo). Verdict: at-median probability with no clear advantages. Recommendation: recruit a co-founder before launch (1.3× lift) or ship a smaller adjacent project first to bump experience to 7 (1.4× lift).

Now plug a more experienced setup: prior 7, solo + contractors, resources 7, timeline 7. Multipliers: experience 1.4×, team 1.0×, resources 1.4×, timeline 1.4×. Adjusted = 4% × 1.4 × 1.0 × 1.4 × 1.4 = 11%. Sanity cap = 4 × 4 = 16%; 11% is under — passes through. Verdict: above-median because of (a) experience 1.4× lift, (b) resources 1.4× lift. Top risk: team (still solo + contractors at 1.0×). Recommendation: 11% is meaningfully above 4% base, but recruiting a co-founder would lift further to ~14%.

How To Score Honestly

Experience: Have you shipped a similar project to completion before? Not similar in idea — similar in shape (built and sold a SaaS, ran an agency, launched a product). 1-3: never shipped anything in this space. 4-6: shipped one similar project (success or failure both count — failure teaches more). 7-9: shipped 3+ similar projects. 10: deep recognized expertise. Most founders self-rate 7+ when 4-5 is honest.

Team: YC / Founders Fund cohort data shows 2-co-founder teams have ~30% higher 5-yr survival than solo. Beyond 3, coordination cost cancels. Solo founders need stronger personal advantages to offset the team handicap. Co-founder fit matters more than count — wrong-fit co-founder is worse than solo.

Resources: How many months can you fully fund this from current savings + non-project income? Not “runway if I cut everything” — realistic runway including life expenses. 1-2 mo: 1. 6 mo: 4-5. 12 mo: 6-7. 24+ mo + income: 9-10. Most projects fail because they ran out of money before finding product-market fit, not because the idea was bad. Honest scoring matters.

Timeline: How does your plan compare to base-rate norms for your project type? Cold-start SaaS realistic timeline to $1K MRR is 12-24 mo. If your plan says “6 mo”, that’s a 1-3. If your plan says “18 mo with monthly milestones”, that’s 5-7. If your plan says “3 yrs with quarterly reviews and explicit kill criteria”, that’s 8-10. Pad your gut timeline 2× and rate honestly.

Common Mistakes

Rating yourself relative to abstract scales. “Am I a 7 or an 8?” is hard. “Am I better than three peers I know in this space?” is easier. Use peer-relative scoring — it’s faster and more honest. The 5-yr rule for experience: 5 = “I’ve done this once before”; 10 = “I’ve done this 5+ times”.

Arguing your idea is the exception. Idea quality is the most over-rated factor. The calculator captures things that actually move the needle (team, execution capacity, resources, timeline) and trusts the project-type base rate already encodes “this kind of idea, on average”. Plug your personal advantages instead of arguing your idea is special.

Treating the sanity cap as a personal attack.The cap exists because multiplicative compounding produces unrealistic numbers when factors interact. A 4% base × 2.5 × 1.4 × 2.0 × 1.8 = 50% feels great but isn’t calibrated reality — no one is genuinely 50% likely to build a successful SaaS just because they have stacked advantages. The cap keeps the math credible. If your raw product hits the cap, you should be skeptical of your own scoring (you probably over-rated 1-2 factors).

Quitting on low probability without checking upside.Probability is one input — pair with expected value (probability × outcome) and regret (would future-you regret skipping?). Low probability + high upside (lottery situations) can still be worth pursuing if downside is bounded. Low probability + low upside is the danger zone. Don’t make decisions on probability alone.

Pursuing on optimistic scoring.The opposite mistake: rating every factor 8-10 to justify proceeding, then being shocked when reality disappoints. Calculator’s job is partly to force calibration — if your honest scoring drops you below base × 1, that’s real signal. Don’t ignore it; do contextualize it.

Related Calculators

Pair this with the Regret Minimization Calculator — Bezos’ framing handles the non-financial side of the decision. Probability surfaces the math; regret surfaces the qualitative weight. Mismatches between the two need careful thought. The Should I Quit Job — Runway Calculator maps directly to the resources input here. If you’re flagging warning tone on resources, the runway calc shows your specific months and the savings-required-before-quitting math. The Career Switch Bootcamp ROI Calculator is a specific path; this calc generalizes the framing. Different lenses on the same career-pivot decision. And the Time Wealth Calculator surfaces the opportunity cost — even successful low-base-rate ventures cost time you can’t get back, and the time-wealth math is what makes that visible.

How to Read the Verdict

Two outputs do the work: the adjusted probability (your honest base rate × personal advantages) and the biggest risk in the math. The base rate is usually painfully low; the calc’s job is to make sure you’re reaching for it eyes-open.

Adjusted probability > 35%. Reasonable bet. Personal advantages compound the base rate meaningfully — pursue with realistic runway expectations.
Adjusted probability 10-25%.Pursue only if the asymmetric upside justifies the expected loss. Most life-changing ventures live here; don’t pretend the number is higher.
Adjusted probability < 10%.The base rate isn’t something you can hustle past. Either pick a different category (lower base-rate anchor), or accept the venture is mostly an option-value play, not an expected- value bet.
Biggest risk is “runway.” Run the runway calc before committing. Most promising ventures fail not on execution but on running out of money before the slow part ends.

Frequently Asked Questions

The most common questions we get about this calculator — each answer is kept under 60 words so you can scan.

Where do the base rates come from?
Each project type's base rate is sourced from published research: Cold-start SaaS 4% (Indie Hackers / Stripe Atlas / Failory data — fraction of indie SaaS reaching $1K MRR sustained). Service business 18% (BLS small-business survival data). Content creator 6% (Patreon / Substack monetization-rate data). Mobile app 2% (Sensor Tower / data.ai monetization stats). Restaurant 30% to year 5 (BLS BED data). Book author 8% (Bowker / Author Earnings — fraction reaching meaningful sales). Nonprofit launch 12% (NCCS data). Physical product DTC 5% (Shopify / industry medians for sustained DTC brands). Agency 22% (BLS service-business survival). Each is a directional anchor against optimism bias.
Why are the multipliers capped at 0.4× / 2.5×?
Because mathematically, individual factors realistically can't move probability more than 2-3× in either direction. A complete novice (0.4×) is genuinely 60% less likely to succeed than a median operator. A deep-expertise operator (2.5×) is genuinely 2.5× more likely. Beyond those bounds, you're either misrepresenting your novice-ness or over-rating your expertise. The caps prevent the multiplication from compounding to absurd 100× lifts that don't reflect reality.
What's the 4× sanity cap on adjusted probability?
Even if every personal factor stacks at maximum (deep expertise + 3 co-founders + 24 mo runway + patient timeline), the math caps adjusted probability at 4× the base rate. Reason: multiplicative compounding produces unrealistic numbers when factors interact. A 4% base rate × 2.5 × 1.4 × 2.0 × 1.8 = 50.4% — but in reality, no startup founder is genuinely 50% likely to build a successful SaaS just because they have advantages. The cap holds the math credible. The cap applies only when the raw product exceeds 4× — sub-4× factor combinations pass through directly.
How do I pick honest scores?
Calibration: think about three peers in your domain. Score yourself relative to them, not relative to abstract '10' or 'genuine deep expertise'. Experience: have you shipped a similar project to completion before? (No = 1-3; Yes once = 4-6; Yes 3+ times = 7-9; Yes successfully + recognized = 10). Resources: how many months can you fully fund this from current savings + sources? (1-2 mo = 1-2; 6 mo = 4-5; 12 mo = 6-7; 24+ mo + income = 9-10). Timeline: how does your plan compare to base-rate norms for your project type? (Wildly optimistic = 1-3; reasonable = 5-7; conservative + buffered = 8-10).
Why is solo penalized vs co-founders?
YC data + Founders Fund data + multiple cohort studies converge: 2-co-founder teams have ~30% higher 5-yr survival rate than solo. Reasons: complementary skills, mutual accountability, capacity to handle parallel workstreams, emotional resilience during low periods. The math doesn't say solo can't work — Stripe / GitHub / many great companies started near-solo — it says base-rate-adjusted, you need stronger personal advantages to offset the team handicap. The 0.85× isn't a death sentence; it's a credibility check.
What if my project doesn't fit any type?
Use 'custom' and provide your own base rate. Where to find it: industry-association annual reports (e.g., AICPA for accounting firms), academic research on your sector, trade-press 'state of the industry' surveys, industry-survival data from BLS BED. When unsure, 5-15% is typical for entrepreneurial ventures. The honest custom rate is usually lower than your gut — base-rate-anchored thinking corrects the optimism bias every founder carries.
Should I quit if my adjusted probability is low?
Not necessarily — the calc is decision-support, not advice. Low probability + high upside (lottery-ticket situations) can still be worth pursuing if downside is bounded. Low probability + low upside is the danger zone. The calc surfaces the math; you make the call about whether the expected value (probability × outcome) justifies the cost (time, money, opportunity). Don't ignore a low number; do contextualize it.
Does this account for serial-entrepreneur lift?
Yes, via the experience score. A serial entrepreneur with 3+ shipped startups (even if some failed) honestly scores 8-10 on prior-relevant-experience — and the 2.0×+ multiplier reflects the real lift serial founders have over first-timers. 'Failure school' is a real teacher; the calc gives credit for it. The catch: you have to honestly score yourself. Founders who failed 3 times often rate themselves 'experienced' at 7+ when they should be 5 (failed at execution, not at learning).
Why no 'idea quality' input?
Because idea quality is the most over-rated factor in startup success. Marc Andreessen / Naval / many investors have written that team + execution + market timing matter far more than idea quality at the early stage. The same idea succeeds for one team and fails for another, depending on execution. Calculator captures the things that actually move the needle (experience, team, resources, timeline) and trusts that the project-type base rate already encodes 'this kind of idea, on average'. Plug in your specific personal advantages instead of arguing your idea is the exception.
How does this differ from regret-minimization-calculator?
Regret-minimization is qualitative (Bezos framing — 80-yr-old you, would you regret doing or not doing this?). Probability-of-success is quantitative (base-rate-anchored math). Pair them: regret-min handles 'is this worth pursuing for non-financial reasons?'; probability-of-success handles 'what are the honest financial / logistical odds?'. Together they map both axes of a big decision. Either alone misses half the picture.