Poker Win Rate Calculator
Is your win rate statistically real, or still noise? Confidence intervals, the probability you are actually a winner, and how many hands it takes to prove it.
Your sample
Questions to ask it
"Confirm" = the 95% confidence interval no longer includes 0 if you truly win at that rate.
Win rate benchmarks by stake
Community-consensus estimates compiled from long-running forum discussions (TwoPlusTwo, r/poker) — not measured data. "Good" means a solid regular after rake; the best players exceed these.
| Online stake | Good win rate |
|---|---|
| NL2 | 6–15 bb/100 |
| NL5 | 5–10 bb/100 |
| NL10 | 4–8 bb/100 |
| NL25 | 3–6 bb/100 |
| NL50 | 2–5 bb/100 |
| NL100+ | 1–4 bb/100 |
| Live stake | Good win rate |
|---|---|
| $1/$2 live | 4–8 bb/hr (~$10–20/hr) |
| $1/$3 live | 4–8 bb/hr (~$15–25/hr) |
| $2/$5 live | 3–7 bb/hr (~$15–35/hr) |
| $5/$10 live | 2–5 bb/hr (~$20–50/hr) |
Methodology — normal approximation, stated plainly
- Standard error: SE = σ × √(100 ÷ hands), where σ is your standard deviation in bb/100. Confidence intervals are observed rate ± z × SE with z = 1.96 (95%) and z = 1.04 (70%).
- Probabilities:P(true > X) = Φ((observed − X) ÷ SE), the standard normal CDF. This treats your observed rate as the point estimate with a flat prior — no hidden Bayesian adjustments.
- Inverse mode: hands = 100 × (z × σ ÷ target)². This is the sample where the CI half-width equals the target rate, i.e. where a true winner at that rate is statistically distinguishable from break-even.
- Live conversion: per-hour σ = σ(bb/100) × √(hands-per-hour ÷ 100); the SE over H hours is that divided by √H. Dollar figures are big-blind figures × your big blind size.
- Assumptions this makes: results are independent and identically distributed (they roughly are, hand to hand), your true win rate is constant over the sample (over long periods it is not — you improve, pools change, you move stakes), and the normal approximation holds (excellent beyond a few thousand hands). Treat the output as a well-founded estimate, not a verdict.
"Is my win rate real?" — the honest answer
Usually: not yet provable, and anyone who tells you otherwise is selling something. Poker results are a small signal buried in enormous noise. A 6-max cash game swings about 100 big blinds per 100 hands — twenty to forty times a good win rate. The consequence, which this calculator makes concrete, is that samples most players consider huge are statistically small. At 50,000 hands, a true 5 bb/100 winner has a 95% confidence interval stretching from roughly −3.8 to +13.8 bb/100: consistent with being a slight loser and with being a crusher. The interval, not the point number, is what you actually know.
That is not a reason for despair — it is a reason to use the right yardsticks. P(true win rate > 0) rises well above 90% long before the full 95% interval clears zero, and watching that probability climb month over month is a far saner progress metric than the win rate itself, which will lurch around for hundreds of thousands of hands.
How many hands is "enough"?
The inverse-mode formula gives the uncomfortable table: with σ = 100, confirming 10 bb/100 takes about 38,000 hands, 5 bb/100 takes about 154,000, 2.5 bb/100 takes about 615,000, and a 1 bb/100 edge needs nearly four million hands — more than most careers. Two practical lessons follow. First, the smaller your edge, the longer you are flying on instruments: track your play honestly in a session journal and judge yourself on decisions, volume, and study rather than the monthly graph. Second, sample size is an argument for playing where your edge is biggest — a large edge at a lower stake is both more profitable per hour of variance and provable sooner than a thin edge higher up.
Confidence intervals, downswings, and your bankroll
The same standard deviation that makes win rates hard to verify is what produces five-figure-hand downswings for genuine winners. If the interval math here feels abstract, our variance simulator draws it: plug in your rate and σ and watch fifty alternate versions of you play the same sample — some of them lose. That visual is the best tilt vaccine we know. And because the plausible range of your true win rate is wide, bankroll rules should be built for the pessimistic end of your interval, not the observed number — our bankroll calculator takes exactly that input.
Live players face the same math on a slower clock: at 27 hands an hour, a year of full-time play is a weekend of online multi-tabling. The live tab converts your hourly results into the same statistical language, so a $1/$2 grinder and a Zoom reg can answer the identical question — how much of this is skill, and how much is sample?
Frequently asked questions
How many hands do I need to know my true win rate?
Far more than feels reasonable. With a standard deviation of 100 bb/100, proving a 2.5 bb/100 win rate is statistically distinct from break-even at 95% confidence takes roughly 615,000 hands; a 5 bb/100 rate takes about 154,000. Under 50,000 hands, almost any observed win rate is compatible with being anywhere from a solid winner to a slight loser — that is the honest math, and it is why this calculator shows the full confidence interval instead of a single number.
What is a good win rate at micro-stakes?
Community-consensus estimates (not measured data): roughly 6-15 bb/100 at NL2, 5-10 at NL5, 4-8 at NL10, 3-6 at NL25, and 2-5 at NL50, all after rake. Live, 4-8 big blinds per hour is commonly cited as a good rate at $1/$2 and $1/$3. Anything positive after rake over a large sample beats most of the player pool.
What standard deviation should I use?
Common tracker-reported figures: about 100 bb/100 for 6-max NLHE cash, 75-85 for full-ring, 100-110 for fast-fold formats, 130-160 for heads-up, and 140-160+ for PLO. Live full-ring play usually sits near 70-90 bb/100. Your own tracker (or our journal) reports your personal figure — use that if you have it, because the confidence interval scales linearly with it.
What does the 95% confidence interval actually mean?
If your true win rate stayed constant and you replayed samples of this size many times, about 95% of the intervals built this way would contain the true rate. Practically: any win rate inside the interval is consistent with your data. If the interval spans from -3 to +13 bb/100, your results genuinely cannot distinguish a good winner from a slight loser yet.
What is the probability my win rate is real?
We compute P(true win rate > 0) = Phi(observed / standard error) under a normal approximation — the probability that your underlying rate is positive given the observed data, treating the observed rate as the best estimate. It is a useful gut-check, not a guarantee: it assumes your game, stakes, and the player pool stay constant, which over long samples they never quite do.
How is a live poker win rate measured?
In dollars per hour and big blinds per hour, because live sessions deal only 25-30 hands an hour. A $25/hr rate at $2/$5 is 5 bb/hr. The slow deal rate is why live win rates take years to verify: 1,000 live hours is only about 27,000 hands — a sample an online grinder clears in a week.
Why does my observed win rate swing so much between months?
A monthly sample of 20,000 hands with a standard deviation of 100 bb/100 has a standard error of about 7 bb/100 — so a true 4 bb/100 winner will post monthly rates anywhere from -10 to +18 in the normal course of variance. Month-to-month swings of 10+ bb/100 are noise, not evidence your game changed. Our variance simulator makes this visceral.
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