The Volume ThesisTeam Ignite Ventures
The mathematics of venture capital's power-law distribution — why concentrated conviction underperforms volume, translated into the numbers LPs actually care about. All figures framed around a standard 4-year fund deployment.
Distribution:Industry avg50/50 BlendYC-calibrated
Global Settings
Skill: market avg
Portfolio size
Selection skill
Recycling (% of committed)
10%
Reserves & follow-on
Reserves10%
Threshold3x
Check2×
Median MOIC
…
30 positions · typical fund
Net IRR
16.6%
4-yr deploy, 10-yr hold
P(return ≥ 1x)
…
doesn't lose money
P(return ≥ 3x)
…
strong fund
The Core Argument — Three Views of One Math
Three mathematical frameworks — the Horsley Bridge outlier model, the Kelly Criterion, and Monte Carlo simulation — all point to a similar portfolio-size floor.
Honest caveat: these frameworks aren't independent — they share distributional inputs. Think of them as one argument viewed three ways, not three separate proofs. Changing the underlying outcome distribution will move all three together.
Invest in more companies. Smaller checks.
Kelly optimal per year
~250
Kelly over 4-yr
~1000
Failure rate → 0%
~150 positions
Horsley Bridge avg-VC floor
~150
Expected Value — Which Outcomes Drive the Math?
Each outcome tier contributes probability × multiplier to the fund's expected value. The table below shows how much each tier contributes — a useful honesty check. If you think the centicorn rate is too generous, adjust it in the Assumptions tab and watch every number in the tool shift.
| Outcome | Probability | Multiple | Contribution to EV | % of total EV |
|---|---|---|---|---|
| 💀Total Loss (0x) | 53.3% | 0x | 0.00x | 0.0% |
| 🚶Walking Dead (1x) | 13.3% | 1x | 0.13x | 2.2% |
| 🤝Small Exit $30–75M (3x) | 10.3% | 3x | 0.31x | 5.0% |
| ✅Exit ~$100–150M (6x) | 12.3% | 6x | 0.74x | 12.1% |
| 🎯Good Exit ~$400M (15x) | 6.2% | 15x | 0.92x | 15.1% |
| 🏆Big Exit ~$750M (25x) | 2.6% | 25x | 0.64x | 10.5% |
| 🦄Unicorn $1–3B (55x) | 1.5% | 55x | 0.85x | 13.8% |
| 💎Mega $3–10B (150x) | 0.39% | 150x | 0.58x | 9.5% |
| 🔥Decacorn $10–25B (400x) | 0.072% | 400x | 0.29x | 4.7% |
| ⚡Ultra $25–100B (1200x) | 0.031% | 1200x | 0.37x | 6.0% |
| 🚀Centicorn $100B–1T (5000x) | 0.018% | 5000x | 0.92x | 15.1% |
| 🌌Terracorn $1T+ (20000x) | 0.002% | 20000x | 0.37x | 6.0% |
| Total expected MOIC | 6.12x | 100% |
Notice tiers contributing over 30% are highlighted — they're doing disproportionate work. If a single low-probability tier produces most of the expected value, the model is highly sensitive to that one assumption. This is why venture math is dominated by a handful of outlier outcomes in the training data (Facebook, Google, Uber) and why returns are hard to replicate.
Selection Skill — What the 1-5 Scale Means
Models how much your picking ability shifts the outcome distribution vs. the market baseline. Anchored to Horsley Bridge's empirical finding that top-tier VCs hit outliers ~4.5% per investment vs 2% for average funds.
| Skill | Label | Unicorn tier ($1–3B) | Loss rate |
|---|---|---|---|
| 1 | Below average | 0.58% | 57% |
| 2 | Slightly below average | 1.04% | 55% |
| 3 | Average | 1.54% | 53% |
| 4 | Above average | 2.38% | 51% |
| 5 | Excellent | 3.27% | 48% |
At skill 5, unicorn rate roughly doubles, decacorn 1.5×, centicorn 2×, loss rate drops 15%. Inverse for below-average skill.
Outcome Distribution · industry average
💀Total Loss (0x)53.3%0x
🚶Walking Dead (1x)13.3%1x
🤝Small Exit $30–75M (3x)10.3%3x
✅Exit ~$100–150M (6x)12.3%6x
🎯Good Exit ~$400M (15x)6.2%15x
🏆Big Exit ~$750M (25x)2.6%25x
🦄Unicorn $1–3B (55x)1.5%55x
💎Mega $3–10B (150x)0.39%150x
🔥Decacorn $10–25B (400x)0.072%400x
⚡Ultra $25–100B (1200x)0.031%1200x
🚀Centicorn $100B–1T (5000x)0.018%5000x
🌌Terracorn $1T+ (20000x)0.002%20000x
Disclaimer
This tool is for educational and informational purposes only. It is not investment advice, not an offer to sell or a solicitation of an offer to buy any security, and not a recommendation to pursue any particular investment strategy. Past performance of venture capital funds does not guarantee future results. All venture investments involve significant risk including total loss of capital, illiquidity, and long holding periods. Before making any investment decision, conduct your own due diligence and consult with qualified legal, tax, and financial advisors. Team Ignite Ventures makes no representation that the modeled distributions, assumptions, or simulated outcomes reflect any actual fund's past or future performance.
Probabilistic framework. Portfolio size represents total positions over a 4-year fund deployment. Twelve outcome tiers span total loss through terracorn ($1T+); multiples are post-dilution returns to a ~$15M blended pre-seed/seed entry (Carta 2025 medians: ~$10M pre-seed SAFE caps, ~$20M seed post-money). Dilution applied per Carta per-round medians (Series A ~19%, B ~15%, C ~11%, D ~9%, plus option-pool refreshes): a seed investor retains roughly 79% of their stake through Series A, ~67% through B, ~59% through C, ~53% through D, and ~45% through E/F — so a $1.5B exit after Series C/D returns ~55x on a $15M entry, and a $15B exit after E/F returns ~400x. Three presets: industry average (cumulative $1B+ rate ≈2%, calibrated to Correlation Ventures' 21K-financings dataset, Carta cohort data, Horsley Bridge outlier rates, and PitchBook/CB Insights rare-outcome counts), YC-calibrated (cumulative unicorn rate ≈6% per Garry Tan's stated 6–12% for recent batches, low end used), and a 50/50 blend of the two. The terracorn base rate (≈0.002%) counts nine VC-backed companies at $1T+: Apple, Microsoft, Alphabet, Amazon, Meta, Nvidia, Tesla, SpaceX (June 2026 IPO), and OpenAI — the last a forward-looking inclusion at its $852B March 2026 mark with an S-1 filed. Selection skill shifts tail probabilities per Horsley Bridge findings via Ulu Ventures (top-tier 4.5% outlier rate, market average 2%, hypothetical superstar 7% — the latter is Ulu's construct, not an empirical observation). Monte Carlo: seeded per portfolio size for reproducible curves; 3,000 sims/size standard (scaled up to 12,000 at n≤20), 10,000 in high-precision mode, 5,000 per side for head-to-head. Reserves model simulates follow-on deployment into companies above the mark-up threshold. Fund economics: management fees (2% × 10yr) reduce investable capital to 80% of commitments and are returned to LPs before carry; recycling (adjustable, default 10% of committed capital) reinvests early proceeds; 20% carry applies via European waterfall (LPs receive 100% of distributions until commitments are returned, 80/20 thereafter); every invested cohort is held a standardized 10 years from its capital call, anchored to Crunchbase exit-timing data and SaaStr's 10.0-year median for $1B+ SaaS acquisitions.
Sources — read the underlying data yourself: Correlation Ventures 21K financings (via Seth Levine) · Carta Class of 2018 cohort · Carta seed/pre-seed valuations · Carta dilution by round · Crunchbase exit timing · SaaStr $1B+ exit timing · Horsley Bridge outlier rates (via Ulu Ventures) · Ulu Ventures portfolio construction · Garry Tan on YC unicorn rates · PitchBook accelerator analysis · PitchBook unicorn tracker · View source on GitHub