A modifier applied to encounters or items that changes difficulty or value.
Some affixes slow clear speed, reducing GPH even when EV per run is unchanged.
Affixes can indirectly change time/cost assumptions rather than drop rates.
Count of successes in n independent trials with constant probability p.
Exactly k: C(n,k)·p^k·(1−p)^(n−k). Any-unique: 1−(1−p)^n.
If p changes each trial (pity, buffs), use ∏(1−p_i) and its complements instead of a single p.
The chance of seeing an event at least once across N attempts: P(≥1) = 1 − (1 − p)^N.
With p=1/16 per run, after 20 runs the chance of any unique is 1 − (15/16)^20.
Cumulative probability rises quickly at first and then tapers; charts help visualize realistic streaks.
A range likely containing the true rate/mean at a stated confidence level (e.g., 95%).
After 200 runs, report a 95% CI for any-unique rate rather than a single estimate.
More data shrinks the interval; high variance widens it. Use exact/binomial methods for small n.
The probability that a specific item appears in a single attempt (e.g., chest, kill, or roll). Expressed as a percentage or 1-in-N.
If a boss has a 5% drop rate for an item, the chance to get at least one in 20 attempts is 1 − (1 − 0.05)^20.
Drop rates may change across seasons or patches. Always confirm the current table for your activity.
A pattern where each additional unit of effort yields smaller gains (e.g., scaling penalties or caps).
If a buff stacks with diminishing returns, EV per run increases slower at higher stacks.
Some games apply DR to stats or currencies; not always relevant to drop odds.
A long series of attempts with no desired drop despite p>0.
At p=5%, zero hits over 60 tries happens with (0.95)^60≈4.6%.
Avoid gambler's fallacy: odds are not 'due'. Evaluate EV and pacing instead.
Average reward per attempt: EV = Σ(outcome value × probability). Neutral to time; pair with GPH for time efficiency.
"EV/chest is stable; improving route time raises EV/hour but not EV per chest."
EV is an average, not a guarantee. High variance may hide long dry streaks despite good EV.
EV translated by your average run time and costs to estimate net profit per hour.
If EV per run is 50k and a run takes 90s, you can do ~40 runs/hour → ~2M GPH before costs.
Travel time, consumables, or wipes affect real GPH; LootCalc lets you include these costs.
A guarantee the target rarity drops by a fixed maximum number of attempts.
P(success by N) = 1. Example: guaranteed 5★ at 90 pulls; counter resets after success.
Does not predict which attempt hits—only bounds the worst case. Combine with soft pity when applicable.
Repeated drop checks where one outcome does not affect the next.
Two 2% checks: P(any)=1−0.98²≈3.96%. Over n: 1−(1−p)^n.
Many games approximate independence. Pity or lockouts break independence or identical p.
Attempts whose success chance is unaffected by past outcomes.
Example: per-run p=6%. Over 20 trials, P(any)=1−(1−0.06)^20≈71.0%.
If p varies by setup/time, treat as non-identical trials and use the mixed-p formula.
The defined set of outcomes and their probabilities or weights used to generate rewards.
Updating a loot table in the calculator changes EV and ‘any unique’ odds immediately.
Always check patch notes; tables may differ by difficulty/tier.
Only one unique can drop per reward slot. The model computes union probability: P(any unique) = 1 − Π(1 − p_i).
Barrows uniques share one slot; the calculator uses a mutual-exclusion model for accurate ‘any unique’ odds.
Independent rolls vs. mutually exclusive tables produce different cumulative curves—choose the one matching the activity.
The 50th percentile: half the outcomes lie at or below it.
Median GPH is robust to jackpots. Compare with EV to understand skew.
In skewed loot, EV ≠ median; players often feel closer to median in short sessions.
A system that increases your odds or guarantees a reward after many attempts without success.
Some seasons grant higher weights or a guaranteed cache after threshold attempts; LootCalc notes these when documented.
Implementation varies by game and season; always check patch notes.
A hard guarantee or very high chance to receive a reward after a fixed number of attempts without success.
If a pity cap triggers at 50 attempts, cumulative probability is 100% at N ≥ 50 regardless of base drop rate.
Different from soft pity (gradual odds increase). Implementation varies by season.
A cut-point at a chosen probability (e.g., 90th percentile).
"90% of sessions ≤ X gp" captures tail risk better than EV alone.
Needs the full distribution (or a good approximation); tails need more data.
A pseudo-random process that decides outcomes such as drops or affixes. In games, RNG is driven by a PRNG algorithm and a changing seed.
Two players with the same EV can see different short-term results because RNG streaks are normal in small samples.
RNG is pseudo-random, not truly random; seeds and implementations vary by game.
A gacha mechanic where drop probability increases after many misses.
Example: base 0.6% increases by +0.1% per pull after 74, reaching ~2.0% by 90.
Soft pity changes p across attempts, breaking the 'identical trials' assumption; model as varying p_i.
The square root of variance. Expresses average distance from the mean in the same units as the metric (e.g., gp).
If GPH has a large standard deviation, comparing two routes requires longer testing to be confident.
Useful for confidence intervals and A/B comparisons of routes.
The number of observed runs. Larger samples reduce variance of the estimate and tighten confidence intervals.
Comparing two routes with similar EVs requires enough runs to overcome randomness.
Small samples can be misleading, especially with rare, high-value drops.
A content period with its own balance, tables, and thresholds. Calculators pin data to the current season.
Switching seasons updates item-level ranges and vault thresholds in the Delves calculator.
Old seasons are archived; always confirm which season the data reflects.
A points or attempt level where rewards upgrade (e.g., weekly vault tiers or track milestones).
Delves award higher item level once you reach the next threshold; calculator shows per-tier ranges.
Thresholds reset per week/season depending on the system.
Probability that at least one of several events occurs.
Independent case: P(any)=1−∏(1−p_i). For identical per-run p over n runs: 1−(1−p)^n.
If events are dependent, use inclusion–exclusion or a simulator.
A measure of the spread of outcomes around the average (EV). Higher variance means wider swings run to run.
Activities with rare, high-value uniques have high variance: long dry streaks followed by spikes.
Variance explains why results can be far from EV in the short term while converging in the long term.
A weekly chest offering rewards based on activities completed and thresholds reached.
Completing more high-tier delves unlocks better vault item-level choices.
Tables and thresholds change by season; LootCalc follows current patch notes.
Average where components contribute per weight (time share, frequency, or value).
EV/hour across routes = Σ(route EV/h × time-share). Chest mix EV = Σ(w_i·EV_i).
Weights can be any non-negative proportions; normalize if they don't sum to 1.