Related Work

The history of WoW combat simulation, the two fundamentally different approaches that emerged, and why it matters for understanding the design decisions behind WoW Lab.

The Two Schools

• Two fundamentally different approaches to answering "what gear should I wear": discrete event simulation and stat weighting
• Both try to solve the same problem but make very different trade-offs in accuracy, speed, and complexity
• Understanding the difference is essential context for why WoW Lab exists and the choices it makes

Discrete Event Simulation

• Simulate combat second by second (or more precisely, event by event), tracking every spell cast, buff tick, proc trigger, and cooldown
• No shortcuts. Model the actual game loop. Roll the dice. Let mechanics interact naturally
• Inherently accurate when modeled correctly because it mirrors what actually happens in-game
• Downside: computationally expensive, requires thousands of iterations for statistical significance
• This is what SimulationCraft pioneered and what WoW Lab does

SimulationCraft

• The gold standard for years. Open source C++ engine, community maintained
• Action Priority Lists (APL) for rotation logic, same concept WoW Lab uses
• Raidbots made it accessible by wrapping SimC in a web UI with cloud compute
• Limitations: single-threaded C++ codebase, difficult to extend, no browser execution, aging architecture
• SimC proved the approach works. The question was whether the tooling around it could be modernized

Early Ask Mr. Robot

• Early versions used a discrete simulation approach similar to SimC
• Provided gear optimization on top of simulation results
• Later pivoted away from discrete simulation entirely (covered below)

Stat Weights and Weighted Engines

• The alternative approach: instead of simulating combat, assign a numerical weight to each stat point
• "1 point of Crit is worth 0.8 DPS, 1 point of Haste is worth 0.95 DPS" and so on
• Score gear by multiplying each stat by its weight and summing. Higher score means better gear
• Fast. Trivially fast. No simulation needed at all once you have the weights
• The problem: weights are only accurate at the exact gear level they were computed for

Where Stat Weights Break Down

• Stat interactions are non-linear. Haste makes Crit better because you cast more spells. Crit makes Haste better because each spell hits harder on crit
• At different gear levels the relative value of stats shifts, sometimes dramatically
• Stat weights are a linear approximation of a non-linear system. Works okay near the measurement point, gets worse the further you move from it
• Breakpoints, tier set interactions, trinket procs, and talent synergies make this even messier
• You end up needing to re-simulate to get new weights anyway, which defeats the purpose

QE Live

• Stat weight based optimization tool for WoW
• Fast results, no waiting for simulation runs
• Trade-off: accuracy suffers in exactly the situations where players need the most help (comparing very different gear sets, evaluating tier pieces, trinkets with procs)

Newer Ask Mr. Robot

• Pivoted to a stat weight and analytical model approach
• Faster than discrete simulation but inherits the fundamental accuracy limitations of the approach
• Made the deliberate trade-off of speed over simulation fidelity

Why Discrete Simulation Wins

• When specs have 10+ interacting buffs, procs, and cooldowns, there is no closed-form solution
• The only way to know for sure is to simulate it and let the mechanics play out
• Stat weights can lie. Simulation results converge to truth given enough iterations
• The real challenge is not whether to simulate but how to make simulation fast and accessible enough that players don't need to settle for approximations
• That is the problem WoW Lab sets out to solve