Planning Poker Calculator
The formula
What the planning poker tells you
The plain odds behind planning poker: single-event probability, the fair-price payout it implies, and how repetition moves the chance of at least one success.
Calculation: p = fav ÷ poss; P(at least one hit in n trials) = 1 − (1−p)^n. Enter your inputs and every substitution is shown below the result.
Reading the result
The fair-payout line is the decision column — any offered price above it carries positive expected value, below it funds the house.
Limitations and best practice
Independence is the assumption; card draws, weather and streaks correlate, which shrinks the repetition column’s real value.
This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Frequently asked questions
Do odds “even out”?
What changes with repetition?
Source & methodology
Classical probability (Laplace) for equally-likely outcomes.
Planning Poker explained: formula, worked example and honest limits
Every bet is a price, and this page computes whether the price is fair. There are plenty of pages about Planning Poker; almost none of them show the working. This one does: the formula, every input, a fully computed example, and a sensitivity analysis calculated live from this engine’s own defaults.
Most confusion about Planning Poker comes from mixing up the input you control with the input you merely observe. The formula treats them identically, but your decisions should not: one deserves measurement, the other deserves a defensible estimate.
What makes Planning Poker worth calculating is not precision but position: it tells you which side of a threshold you are on, and by how much. A rough figure that settles the direction beats an elaborate one that never commits.
What makes a calculation page trustworthy is that its copy is derived from its own arithmetic: here single-trial probability = 33.33%, recomputed every time a field changes, and the sensitivity section ranks the inputs that move the result — Possible outcomes first, at ≈11.1 % of the headline for a ten-percent error either way in that input — which is the thread the rest of this guide pulls on.
The Planning Poker formula, explained
The engine implements a single stated model: p = fav ÷ poss; P(at least one hit in n trials) = 1 − (1−p)^n. There is no hidden coefficient and no login-gated precision — the formula printed is the formula executed, which is also what makes the result citable.
Favourable outcomes (example value 2) is a quantity rather than a category — precision here is cheap and worth having. If you are unsure what belongs in this field, look at the printed steps: the substitution shows exactly how the engine uses it.
Possible outcomes (example value 6) is a plain measured quantity — the unit shown in the label is the unit the formula expects. The example value is there to demonstrate the mechanics, not to describe your situation — overwrite it.
Repetitions (independent) (example value 2) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. This input feeds the formula directly; a defensible figure here is worth more than false precision anywhere else.
The default Planning Poker calculation, written out in full
Abstract formulas are hard to trust, so here is the complete substitution using the default inputs, written the way an examiner would want it. Starting figures: Favourable outcomes, Possible outcomes, Repetitions (independent). Run to the end, the single-trial probability resolves to 33.33% — Live odds — worth calculating the payoff on the bands this tool uses.
- p = 2 ÷ 6 = 0.3333
- Odds against = (1−p)÷p = 2.00:1
- P(hit within 2 tries) = 1 − 0.6667^2 = 55.6 %
Odds against — 2.00 :1. Read next to the headline, this is the figure that shows the shape of the trade-off.
At least one hit in 2 — 55.6%. If your inputs change, this is usually the first companion figure to move.
Fair payout to break even — 3.00 :1. If your inputs change, this is usually the first companion figure to move.
Re-running with your own figures is instant; re-running by hand once is the best way to know the tool is telling you the truth.
The Planning Poker corridor: your result across a realistic band
Single-point answers invite false confidence, so the same engine was run across a band around the input that matters most here. Each row is a full recalculation of Planning Poker, not an interpolation.
| Possible outcomes setting | Single-trial probability |
|---|---|
| 80 % of the example value | 41.67% |
| 90 % of the example value | 37.04% |
| example inputs | 33.33% |
| 110 % of the example value | 30.30% |
| 120 % of the example value | 27.78% |
Across 5 settings of Possible outcomes, the result spans 27.78% to 41.67%. A decision that only works at one row of this table is a decision waiting for an input to move. Reproduce it in the form above by editing Possible outcomes alone; the substitution steps will follow your figures exactly.
Sensitivity: which inputs change Planning Poker the most
Generic advice says “it depends on your inputs”; this section says exactly how much. Each field was perturbed by ±10 % in isolation and the single-trial probability recomputed, so the ranking below is measured rather than asserted. For Planning Poker the ranking is measured rather than guessed, and it belongs to these defaults: shift the starting point and the order can shift with it.
- Possible outcomes +10 % → Planning Poker = 30.30% · −10 % → 37.04% (the single-trial probability shifts ≈11.1 %)
- Favourable outcomes +10 % → Planning Poker = 36.67% · −10 % → 30.00% (the single-trial probability shifts ≈10.0 %)
Possible outcomes is the dominant lever here: ten percent either way moves the result by about 11.1 %, from 30.30% to 37.04%. Measure that input from a document rather than from memory, and treat Favourable outcomes as the second priority (≈10.0 % per ten percent). Everything below that can stay approximate, which is a licence to stop chasing data that would not change the decision.
Interpreting the Planning Poker verdict
The value above only becomes useful the moment you know what it is being measured against. The default case lands in the “Live odds — worth calculating the payoff” band, and bands are deliberately wide because real situations overlap. The sensitivity list shows how far a modest input error moves you along that ladder: for Possible outcomes, ±10 % covers 30.30% to 37.04%. The practical reading rules: ask what would have to change to move you one band. If the answer is “a small, plausible input difference”, the band itself is not the finding — the uncertainty is.
In Technology & Computing, Planning Poker is one instrument in an orchestra: on its own it is a number, next to Odds against and At least one hit in 2 it becomes a diagnosis. The tools linked above exist so the headline never has to carry that weight alone.
The errors that quietly break a Planning Poker figure
Independence is the assumption; card draws, weather and streaks correlate, which shrinks the repetition column’s real value. This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Treating the example inputs as a recommendation. They are a demonstration of the mechanism — a decision-grade Planning Poker begins the moment your own figures replace them.
Attention is also misallocated between fields. Having measured this engine, we can say where it belongs: Possible outcomes first, everything else second.
A final trap is presentation: reporting Planning Poker to more decimal places than the inputs support. The tool prints what the arithmetic gives; you should quote only what your least precise field justifies.
Six things to confirm before acting on Planning Poker
- Confirm the example values are plausible for your own situation before replacing them.
- Check that every field the formula needs actually arrived from a document, not from recollection.
- Check Possible outcomes before anything else: it is the measured dominant input, ≈11.1 % of Planning Poker per ten percent.
- Recompute once with the dominant input deliberately set low, and see whether the decision changes.
- Compare the output against one published benchmark or a colleague’s independent estimate.
- Repeat the ±10 % test on the inputs that matter and see whether the decision — not just the number — still holds.
Five steps from raw inputs to a figure you can defend
Using a calculator well sounds trivial, but the difference between a decision-grade figure and a throwaway one lives entirely in the routine. The routine for Planning Poker takes a minute to learn and applies to every input above.
Step 1 — start from evidence. The inputs behind Planning Poker are favourable outcomes, possible outcomes, repetitions (independent). Write them down with their source next to each one; if you cannot name where a figure came from, that is the input most likely to be wrong. If the verdict changes with a ten-percent nudge, report the nudge alongside the number.
Step 2 — compute the version you would not be embarrassed by. If a stranger audited your inputs, which set would you hand over? Enter that set, read the result, and treat everything else as upside. If the answer changes your behaviour, it deserves a second run with different assumptions.
Step 3 — play with the inputs on purpose. Ten percent up, ten percent down, one field at a time. Within a few minutes you will know this calculation better than most people who quote its results. The input you reach for first is usually the one you measured longest ago.
Step 4 — ask what would have to be true. Take the result you want and work backwards through the inputs until you find the assumption that produces it; then decide honestly whether that assumption is defensible. Re-running a number costs seconds; retracting a decision costs considerably more.
Step 5 — record the context, not just the number. Note today’s date and the inputs alongside the 33.33% output. Six months from now the context is what turns this figure into a trend. A result worth acting on survives having its two shakiest inputs halved.
From calculation to decision: where Planning Poker earns its keep
Numbers earn their keep in conversations, and Planning Poker is no exception. In Technology & Computing discussions around Software Development, this figure decides whether an option stays on the table: it converts an opinionated debate into an arithmetic one, and arithmetic is the only referee both sides accept. Write the assumptions in the same file as the result, and future arguments take minutes instead of meetings.
The audience for this page is players deciding whether a wager is mathematically worth taking. In professional Software Development practice the pattern is always the same — screen with Planning Poker, then invest slow analysis only in whatever survives the screen. Note the assumption you are least sure about; that is where the real risk lives.
Treat Planning Poker like a smoke alarm rather than a painting — its value is in being tested periodically, not in being admired once. The point of transparency is that a reader can disagree with a specific line rather than with you.
People also ask about Planning Poker
What affects Planning Poker the most?
The short answer: Possible outcomes. The longer answer is the sensitivity table on this page, where every numeric input was probed by ten percent and the single-trial probability recalculated — Possible outcomes moved it furthest, by roughly 11.1 % (30.30% to 37.04%).
Which matters more: favourable outcomes or possible outcomes?
Possible outcomes, by a factor of about 1.1. Concretely: ten percent on Possible outcomes is worth ≈11.1 % of Planning Poker, the same nudge on Favourable outcomes only ≈10.0 %. That ranking is re-computed for each page from that page’s own defaults.
What is a typical Planning Poker?
On the worked example above Planning Poker comes out at 33.33%. Treat that as one point on a distribution rather than a norm: the bands, the companion outputs and the sensitivity ranking tell you how wide the plausible range really is.
How do I calculate Planning Poker by hand?
p = fav ÷ poss; P(at least one hit in n trials) = 1 − (1−p)^n is the entire method. Work the inputs in that order — p = 2 ÷ 6 = 0.3333 — and you will reach 33.33% on the default figures, the same number this tool prints.
What happens to Planning Poker if possible outcomes changes by 10 %?
On these inputs a ±10 % change in possible outcomes takes Planning Poker to 30.30% against the 33.33% example — around 11.1 % of the headline. The same test on every other field is in the sensitivity section.
Is the Planning Poker result of 33.33% good or bad?
Neither, on its own — the label “Live odds — worth calculating the payoff” is the band this figure falls in for the example inputs, and your own inputs will place you elsewhere on the same ladder. Judge the number against your history and your alternatives, and remember that a ten-percent error in Possible outcomes alone moves it by ≈11.1 %.
What affects Planning Poker the most?
Sensitivity depends on where you start, but the inputs Favourable outcomes and Possible outcomes typically move Planning Poker further than the rest because they enter the formula multiplicatively. If you can only measure two things well, measure those and hold the others at conservative defaults.
Can Planning Poker be negative or empty?
Yes, and that is informative rather than broken: a negative Planning Poker usually means the inputs encode an outflow or a shortfall, and the verdict band above labels exactly that situation instead of hiding it.
Do odds “even out”?
Each trial is memoryless — the law of large numbers guarantees averages over the long haul, not corrections soon.
What changes with repetition?
The at-least-one line compounds (1−(1−p)^n) — 3 % once per try becomes 1−0.97^30 ≈ 60 % across 30 tries.
Is my data private on this page?
Yes — computation happens locally in your browser, with no account, no tracking of your inputs and nothing sent to a server. The printed formula is the whole story of what happens to your figures.
Glossary for Planning Poker
- Odds against
- 2.00 :1 on the example inputs — a companion figure printed beside the headline of Planning Poker so that no result is read in isolation.
- At least one hit in 2
- 55.6% for the Planning Poker worked case; it sits next to the main result because it carries context the headline leaves out.
- Fair payout to break even
- 3.00 :1 in the default Planning Poker calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Single-trial probability
- The primary output of this tool: 33.33% for the default inputs, computed exactly from p = fav ÷ poss; P(at least one hit in n trials) = 1 − (1−p)^n.
- Worked example
- The step-by-step substitution printed above, so the arithmetic can be re-derived by hand or in a spreadsheet.
- Verdict band
- The plain-language label — here “Live odds — worth calculating the payoff” — mapping the computed figure onto experience-based ranges for Technology & Computing.
- Sensitivity (±10 %)
- How far the Planning Poker moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Method, sources and what this tool cannot tell you
The model is published arithmetic implemented exactly as written: p = fav ÷ poss; P(at least one hit in n trials) = 1 − (1−p)^n. Source of record: Classical probability (Laplace) for equally-likely outcomes. Where a professional version of this calculation differs, it differs in inputs and jurisdiction-specific coefficients, not in the algebra — which is why re-checking your inputs beats hunting for a second calculator.
Treat the output as a precise answer to the question you typed: exact arithmetic, transparent formula, published source, no hidden rounding. Nothing is smoothed, weighted or adjusted behind the scenes; where judgement enters, this page says so and names the input responsible.
Turning this Planning Poker into a decision
Compare the computed edge against the actual price being offered; a positive theoretical edge still loses to bad odds.
Whoever you are (players deciding whether a wager is mathematically worth taking), the next step is the same: replace the example inputs with your own, note the date, and re-run whenever a figure moves. In Technology & Computing, a dated figure is a trend, and an undated one is a rumour.