LootCalc

Public Data Snapshots

Every calculator ships with a CSV snapshot in the repository so reviewers can reconstruct our math. Recent additions include:

  • data/destiny2/raid-exotic-log.csv – Bungie API pulls for raid exotic attempts
  • data/warframe/relic-log.csv – refinement runs with tier, squad, and drop flags
  • data/lost-ark/honing-log.csv – honing cost records with artisan energy tracking
  • data/apex/pack-log.csv, data/ffxiv/dawntrail-week2.csv, data/eft/spawn-log.csv – previously published pack, loot, and spawn studies
  • data/borderlands3/legendary-log.csv & data/elden-ring/drop-log.csv – legendary farming and Discovery tracking logs
  • data/minecraft/loot-table-log.csv, data/genshin/wish-log.csv, data/destiny2/raid-guide-log.csv – datasets powering Minecraft, Genshin, and Destiny 2 guide analyses
  • data/diablo4/helltide-log.csv, data/osrs/barrows-log.csv, data/wow/delves-log.csv, data/poe/currency-log.csv – raw logs for Diablo 4, OSRS, WoW Delves, and PoE calculators

Methodology

How we calculate drop rates, expected values, and probabilities. Our transparent approach to assumptions, formulas, and data validation.

Our Approach

LootCalc uses established probability theory and statistical methods to analyze game mechanics and calculate expected outcomes. Our methodology prioritizes transparency, reproducibility, and accuracy.

Core Principles

  • Transparent assumptions: We clearly state all assumptions and limitations
  • Reproducible calculations: All formulas are documented and can be verified independently
  • Data-driven: Calculations based on verified game data, not speculation
  • Community-validated: Results cross-checked against community research and empirical data

Data Sources

We rely on multiple verified sources to ensure accuracy:

Official Sources

  • • Developer patch notes and announcements
  • • Official game wikis and databases
  • • In-game tooltip data and descriptions
  • • Published developer statements on mechanics

Community Research

  • • Data mining from game files
  • • Large-scale community drop rate studies
  • • Player-contributed empirical data
  • • Third-party databases (Wowhead, OSRS Wiki, etc.)

Mathematical Models

  • • Binomial probability distributions
  • • Geometric distributions for pity systems
  • • Expected value calculations
  • • Monte Carlo simulations for complex systems

Validation

  • • Cross-referencing multiple sources
  • • Peer review by mathematics specialists
  • • Community feedback and bug reports
  • • Regular updates for game patches

Standard Assumptions

Unless otherwise stated on specific calculator pages, we use these standard assumptions:

1. Independent Events

Each attempt (kill, chest open, etc.) is treated as an independent event unless the game explicitly uses pity or bad-luck protection systems.

Example: Each Barrows chest is independent; previous runs don't affect future drops.

2. Static Drop Rates

Drop rates are assumed to remain constant unless the game uses dynamic scaling or pity systems.

Exception: Systems like Genshin Impact's guaranteed pity are explicitly modeled.

3. Market Price Volatility

Gold per hour (GPH) and expected value calculations use current market prices, which may fluctuate.

Note: Prices are periodically updated but may not reflect real-time market conditions.

4. Optimal Play

Calculations assume optimal or typical gameplay conditions unless specified otherwise.

Example: Barrows calculations assume 88% Potential for optimal drop rates.

5. Rounding & Precision

Probabilities are typically displayed to 2-4 decimal places. Intermediate calculations use full precision.

Example: A 1/128 drop rate is displayed as 0.78125% or ~0.78%.

Common Formulas

These are the fundamental formulas used across our calculators:

Expected Value (EV)

EV = Σ (Probability × Value)

The expected value is the sum of all possible outcomes multiplied by their probabilities.

Example: If a chest has a 10% chance of 100 gold and 90% chance of 10 gold:
EV = (0.10 × 100) + (0.90 × 10) = 10 + 9 = 19 gold

Probability of At Least One Drop

P(at least 1) = 1 - (1 - p)^n

Where p is the drop rate per attempt, and n is the number of attempts.

Example: For a 1/100 drop rate after 100 attempts:
P = 1 - (1 - 0.01)^100 ≈ 0.634 or ~63.4%

Binomial Probability

P(X = k) = C(n,k) × p^k × (1-p)^(n-k)

Probability of exactly k successes in n independent trials with success rate p.

Use case: Calculating probability of exactly 3 rare drops in 100 attempts.

Gold Per Hour (GPH)

GPH = (Expected Value per Run) / (Time per Run in Hours)

Measures efficiency by combining expected value with time investment.

Example: If a run yields 50k gold EV and takes 5 minutes:
GPH = 50,000 / (5/60) = 600,000 gold per hour

Verification Process

Every calculator undergoes rigorous verification before publication:

1

Formula Validation

Mathematical formulas are reviewed by our math specialists and tested against known edge cases.

2

Data Verification

Drop rates and game mechanics are verified against multiple sources (official data, data mining, community research).

3

Community Testing

Results are compared against community-validated data and empirical studies when available.

4

Ongoing Monitoring

We track game patches and updates, responding to community feedback and bug reports promptly.

Limitations & Caveats

Important Limitations

  • Hidden mechanics: Some game systems may have undocumented behaviors not captured in our models
  • Patch changes: Game updates may change drop rates or mechanics; we update calculators when possible but there may be a delay
  • Market volatility: Gold values and market prices fluctuate; our GPH calculations reflect a snapshot in time
  • Simplified models: Complex systems may be simplified for usability; game-specific pages note these simplifications
  • Player variation: Real results will vary; probability describes long-term expectations, not guarantees

Related Resources

Published:
Last Updated:
Reviewed by: Mathematics Team

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