Score
0.46
Kelly
0.0%
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Bootstrapped micro-SaaS
Side business / micro-venture · 12-month horizon
Score 0.46 · expected value is negative under current assumptions (NO_GO)
With the resources you committed ($19,240 of equivalent capital) over a 12-month horizon, the prior win rate is 13.3%, the payoff ratio is b=3.47, giving an expected value of EV=-$7,791 and a risk-adjusted return of RAROC=-0.27. Under your current assumptions this is not worth acting on. The Kelly-optimal stake of 0.0% sits inside the 20% risk budget for your Working professional profile.
Ten hours a week for a year on a niche subscription product, with $240 of hosting. The win rate is the share of Stripe-verified indie projects that clear $1,000/month, discounted by the 54% that never earn anything. Almost all of the cost is your own time.
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The three numbers
Win rate, payoff ratio and expected value decide most of the recommendation; Kelly, RAROC and score turn them into an action.
Win rate p
13.3%
Prior probability of success
Payoff ratio b
3.47 ×
b = E[win] / E[loss]
Expected value
-$7,791
EV = capital × (p × b − (1 − p))
Kelly
0.0%
(b·p − (1 − p)) / b
RAROC
-0.27
EV / (capital × σ)
Score
0.46
score = p × b
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What you are committing
Equivalent capital $19,240, converted from five kinds of resource.
This opportunity carries $19,240 of equivalent capital. The largest single component is your own time, at 99% of the total ($19,000). Time cannot be recovered once spent. Set an explicit time ceiling and force a review when you are halfway through it.
How non-cash resources are priced
One hour of your own time is priced at $38 and one person-month of hired labour at $8,080. These are market shadow prices, not what you personally earn; changing them changes only the scale, not the ranking.
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How this compares with the category
Your assumptions against the Beta(α, β) prior for this kind of decision.
Category mean win rate
6.7%
Beta(α=2, β=28)
Category payoff P50
2.50 ×
P90 13.00×
Your win rate of 13.3% is well above the category baseline of 6.7% (+6.6%). Make sure that edge rests on specific, checkable facts rather than optimism. The payoff ratio of 3.47× is above the baseline median of 2.50× — check that your success case has not quietly flattened the downside tail. Baseline source: Stripe-verified indie project revenue distribution (US-IND-01..04) + fitted Patreon earnings distribution (US-CRE-01..04).
Baseline source: Stripe-verified indie project revenue distribution (US-IND-01..04) + fitted Patreon earnings distribution (US-CRE-01..04)
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Action plan
Sized to the risk budget of your profile: Working professional.
Recommendation: NO_GO — under your current win-rate and payoff assumptions the expected value is negative. This is not where your money and time should go.
- The expected value is negative. That is arithmetic, not a lack of nerve.
- Two ways forward: (a) restructure the inputs — less cash, more time, or a smaller scope — until the expected value turns positive; or (b) move the resources to a higher-ranked GO opportunity in your portfolio.
- Save this decision and recompute every three months. Category win rates and payoff ratios move over time.
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Sensitivity analysis
How much the expected value moves when each variable is swung ±20%, ranked by impact. The top two are the ones worth researching before you commit.
- · The tornado analysis identifies Win rate (p) as the variable the conclusion is most sensitive to: a ±20% swing moves the expected value by $4,579. Spend your research budget here first.
- · The second most sensitive variable is Payoff ratio (b) (expected value swings $3,556); the remaining inputs matter markedly less.
- · A quick test for whether to keep researching: buy the information only if it costs less than one fifth of the expected-value swing it would resolve.
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Monte Carlo distribution
10,000 simulated outcomes, seed demo-side-saas — rerunning with the same inputs gives the same distribution.
P5
-$62,683
Median (P50)
-$16,652
P95
$121,545
Probability of a positive outcome
14.2%
Across 10,000 Monte Carlo runs: P5 = -$62,683, P50 = -$16,652, P95 = $121,545, and the probability of a positive outcome is 14.2%. The distribution is right-skewed — a long upside tail carries most of the value.
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Scenarios
Bull, base and bear, moving win rate and payoff ratio together by ±15%.
Scenario analysis (win rate and payoff ratio moved together by ±15%): bull = -$4,541, base = -$7,791, bear = -$10,642. The $6,101 gap between bull and bear measures how fragile your assumptions are — the wider it is, the more due diligence pays for itself.
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Counterfactual matrix
What the expected value becomes at other combinations of win rate and payoff ratio — how wrong your assumptions can be before the answer changes.
The counterfactual grid shows that expected value turns non-negative once the win rate reaches 20%, or once the payoff ratio reaches 0.5×. Treat those two lines as the minimum bar any further evidence has to clear.
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Assumptions
Every input behind the numbers above, in one place.
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Reproducibility appendix
Everything needed to recompute this report yourself.
Core formulas
EV = capital × (p × b − (1 − p)) f* = (b·p − (1 − p)) / b RAROC = EV / (capital × σ)Python
from models.feasibility_model import expected_value, kelly_fraction, raroc, go_no_go
p, b, sigma, capital = 0.133, 3.474, 1.5, 19240
ev = expected_value(p, b, capital)
kelly = kelly_fraction(p, b)
rr = raroc(ev, capital, sigma)
print(ev, kelly, rr, go_no_go(ev, kelly, 0.20, rr))TypeScript
import { expectedValue, kellyFraction, raroc, goNoGo } from "decision-lab/lib/feasibility";
const p = 0.133, b = 3.474, sigma = 1.5, capital = 19240;
const ev = expectedValue(p, b, capital);
const kelly = kellyFraction(p, b);
const rr = raroc(ev, capital, sigma);
console.log(ev, kelly, rr, goNoGo(ev, kelly, 0.20, rr));Both implementations are in the repository and are kept in agreement by golden-parity tests: models/feasibility_model.py and lib/feasibility/.
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Sources and disclaimer
- · Kelly J.L. (1956). A New Interpretation of Information Rate. Bell System Technical Journal.
- · Markowitz H. (1952). Portfolio Selection. The Journal of Finance.
- · Sharpe W.F. (1966). Mutual Fund Performance. The Journal of Business.
- · Kahneman D. & Tversky A. (1979). Prospect Theory. Econometrica.
- · Industry baseline: Stripe-verified indie project revenue distribution (US-IND-01..04) + fitted Patreon earnings distribution (US-CRE-01..04)
- · Decision Lab methodology
- · Full business plan (PDF)