Gacha Pull Probability Simulator Pity
Calculate your chance of pulling a banner item from base rate, soft and hard pity, current pity count and available pulls, with expected cost per pull.
Gacha Pull Probability Simulator Pity
Calculator
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Formula: P(success in N) = 1 - Product(1 - rate_i) for i = 1 to N
Worked example โ Success probability: 99.5% with 25 pulls | Expected: ~14 pulls | Cost: $37.50
Formula
P(success in N) = 1 - Product(1 - rate_i) for i = 1 to N
The cumulative success probability equals 1 minus the product of failure probabilities at each pull. The effective rate at each pull position accounts for soft pity (linearly increasing rates after a threshold) and hard pity (guaranteed at the cap). This geometric-like distribution with rate escalation models real gacha systems accurately.
Worked Examples
Example 1: Standard Banner with Soft Pity
Problem:A game has 0.6% base rate, 90-pull hard pity, soft pity at pull 74. You are at 65 pity and have 25 pulls. What is your chance of getting the item?
Solution:Pulls 66-73 (8 pulls at 0.6%): Fail prob = (0.994)^8 = 0.953. Pulls 74-90 (soft pity, rates escalate from 0.6% to ~50%): At pull 74, rate jumps to ~6%. By pull 80, rate is ~22%. By pull 85, rate is ~38%. Cumulative success by pull 90 (25 pulls from current): > 99.5%. Expected to hit around pull 78-80 (13-15 pulls from current).
Result:Success probability: 99.5% with 25 pulls | Expected: ~14 pulls | Cost: $37.50
Example 2: Early Pity Planning
Problem:Starting from 0 pity with 0.6% rate and 90 pity. How many pulls for 90% confidence? Budget at $1.50 per pull.
Solution:At 0.6% base rate, probability of early hit in first 73 pulls: 1-(0.994)^73 = 35.5%. Soft pity from 74-90 adds significant probability. By pull 80: ~75% cumulative. By pull 85: ~92% cumulative. For 90% confidence, need approximately 83-84 pulls. Cost: 84 x $1.50 = $126.00.
Result:90% confidence: ~84 pulls ($126) | Guarantee: 90 pulls ($135)
Frequently Asked Questions
What is the pity system in gacha games?
The pity system is a mechanic that guarantees a rare item after a certain number of unsuccessful pulls. It exists to prevent extremely unlucky streaks and give players a deterministic upper bound on spending. Most games implement two forms: soft pity (gradually increasing rates after a threshold, typically 75% of the hard pity) and hard pity (guaranteed item at a fixed pull count). For example, in a game with 90-pull hard pity and 0.6% base rate, soft pity might start at pull 74 where rates increase from 0.6% to roughly 6-33% per pull until the guarantee at pull 90.
How does soft pity affect the expected number of pulls?
Soft pity dramatically reduces the expected number of pulls compared to pure random chance. Without any pity system at a 0.6% rate, the expected pulls for one copy would be about 167. With soft pity starting at pull 74, the expected drops to roughly 62-65 pulls because the escalating rates mean most players get the item between pulls 75-85. Only about 1-2% of players actually reach hard pity. This makes the effective rate much higher than the advertised base rate, which is why experienced players track their soft pity threshold carefully.
What is the 50/50 system and how does it affect probabilities?
Many gacha games implement a 50/50 system where winning the featured item is not guaranteed even when hitting pity. You have a 50% chance of getting the featured item and 50% chance of getting a random item from the pool. If you lose the 50/50, the next pity is guaranteed to be the featured item. This means in the worst case, you need to hit pity twice (180 pulls at 90 pity). The expected pulls for a specific featured item considering the 50/50 is roughly 1.5x the expected pulls to pity, since on average you lose every other 50/50.
How much should I budget for a specific character or item?
Budget for the worst case while hoping for the best. At typical rates (0.6% base, 90 hard pity), budget for 160-180 pulls for guarantee with a 50/50 system. At $1-2 per pull, that is $160-360. However, statistically, 90% of players will get the item within 80-85 pulls (one pity cycle) thanks to soft pity. The median player needs about 60-65 pulls. Only plan to spend what you can afford to lose. Track your pity counter and pull history to make informed decisions about when to save versus spend your resources.
Is it better to do single pulls or ten-pulls?
Mathematically, single pulls and ten-pulls have identical rates in most games. However, single pulls offer one key advantage: you can stop immediately after getting the desired item, saving remaining pulls for the next banner. With ten-pulls, you might get the item on the first pull of a ten-pull and waste the remaining nine. The only exception is games that offer a guaranteed 4-star or higher in every ten-pull, which provides slightly better value. For tracking pity, single pulls give more precise control over your pity counter.
Why does the geometric distribution stop describing a banner once pity is added?
A pure geometric distribution assumes every trial has the same success probability, which makes it memoryless: 20 failures in a row tell you nothing about pull 21. Pity deliberately breaks that assumption by making the per-pull rate a function of the counter, so the process becomes a sequence of Bernoulli trials with changing probabilities. Cumulative success is then one minus the running product of the individual failure terms rather than a closed-form power, which is exactly what this simulator evaluates pull by pull instead of applying 1 minus (1 minus p) to the power n.
What is the difference between the advertised base rate and the effective rate over a full cycle?
The advertised figure, commonly 0.6 percent, is the flat probability that applies only while the counter sits below the soft pity threshold. Once the ramp begins the per-pull rate climbs steeply toward the hard cap, so averaged across a complete cycle the realised rate is far higher, in the region of 1.6 percent for a 0.6 percent base with a 90-pull cap. That is why players who divide their total pulls by their total rare items get a number several times the published rate and assume the disclosure is wrong. Both figures are correct; they measure different things.
Does the pity counter reset when a banner ends?
That depends entirely on the title, and it is the single most important thing to confirm before planning a budget. Most games maintain separate counters for distinct pools, so character, weapon and standard banners each track their own progress, and a counter usually carries across successive banners of the same type rather than zeroing when one ends. Some titles do reset on rotation. Since every probability this tool reports is conditional on the current-pity input, entering a counter that the game has silently reset will make the odds look far better than they are.
What does it mean when the tool says 90 percent confidence at a given pull count?
It means that if a very large number of players started from your exact counter and pulled that many times, about 90 in every 100 would have obtained the item and 10 would not. It is a statement about the population, not a promise about your account, and it does not improve as you fail. There is no accumulated debt outside the pity counter itself: below the soft pity threshold the per-pull rate is unchanged by your history, so the belief that a dry streak is owed a win is the gambler's fallacy.
Why do two players with identical rates end up with wildly different totals?
Because the low-rate portion of the distribution has enormous spread. For a flat 0.6 percent rate the standard deviation of pulls to first success is about 166, essentially as large as the mean of roughly 167, so outcomes of 20 and 400 are both unremarkable. Pity compresses this dramatically by truncating the tail: no one can exceed the hard cap, and the soft pity ramp bunches most results into a narrow band just before it. That is why anecdotes about luck are far more extreme on banners with a high cap or none at all.
References
Background & Theory
History
Reviewed for accuracy by Daniel Agrici, Founder & Lead Developer ยท Editorial policy
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