CS2 Cumulative Results Analyzer
Simulate your CS2 case opening journey over time. This tool visualizes cumulative profit/loss, tracks milestones, and shows you the statistical reality of opening hundreds or thousands of cases. See how variance affects results and understand the long-term mathematical expectations.
How This Tool Works
This analyzer simulates case openings using Valve's official CS2 drop rates and generates a complete "journey" showing your cumulative results over time. Unlike single-session simulators, this shows how results accumulate across many openings, demonstrating the effects of expected value and variance over the long term.
Configure Your Simulation
Notable drops will appear here...
Understanding Cumulative Case Opening Results
Why Simulate Multiple Cases?
Opening a single case tells you nothing about the system—it's just one random outcome. Opening 100 or 1,000 cases reveals patterns. This tool shows you what those patterns look like, helping you understand both the mathematics and the psychological experience of extended case opening.
According to the law of large numbers, as you open more cases, your actual results will converge toward the expected value. For CS2 cases, this expected value is always negative—meaning the more you open, the closer your average loss per case approaches the theoretical loss built into the system.
Key Concepts in This Analyzer
Cumulative Profit/Loss
This graph shows your running total over time. You'll notice wild swings early on (high variance), but as you open more cases, the trend typically becomes clearer. Understanding this visual helps demonstrate why short-term "hot streaks" don't predict long-term outcomes.
Expected Value vs. Actual Value
Expected value (EV) is the mathematical average outcome if you opened infinite cases. Your actual results will vary from this, but over large sample sizes, they should approach it. Our tool calculates expected values using Valve's disclosed drop rates and approximate market prices for items.
Milestones
We track common goals like "First Knife," "Break-Even Point," and "First Covert." These milestones help contextualize your journey and show how statistically rare certain achievements actually are. For example, the median number of cases to get a first knife is around 267 (50% probability by that point), based on the geometric distribution.
Luck Score
We compare your simulated results against expected outcomes to generate a "luck score." This uses standard statistical methods to determine if your results are unusually good, unusually bad, or statistically normal. A score near 0 means average luck; positive means lucky; negative means unlucky.
CS2 Case Drop Rates
This tool uses Valve's officially disclosed drop rates for all CS2 cases:
- Mil-Spec (Blue): 79.92%
- Restricted (Purple): 15.98%
- Classified (Pink): 3.20%
- Covert (Red): 0.64%
- Rare Special (Gold/Knife/Gloves): 0.26%
- StatTrak Variant: 10% of any drop
These rates are consistent across all weapon cases and have been verified by community data. For more details, see our Case Odds Explained guide or Valve's official item drop documentation.
Why Results Vary So Much
Variance is the statistical term for how spread out results can be from the average. In case opening, high variance means you might go 500 cases without a knife, or get two knives in 50 cases. Both are statistically possible, though the former is more likely than the latter.
This tool demonstrates variance visually. Run the same simulation multiple times with identical settings and you'll see different outcomes each time—sometimes drastically different. This helps illustrate why individual experiences ("I always get lucky" or "cases are rigged") don't reflect the underlying mathematics.
The House Edge
CS2 cases have a built-in house edge (also called "rake" or "vig") of approximately 40-60% depending on the specific case and current market conditions. This means for every $1 you spend on cases, you can expect to receive approximately $0.40-$0.60 in item value on average.
This is comparable to or worse than most casino games. For context, roulette has a house edge of about 2.7-5.3%, and slot machines typically range from 2-15%. CS2 cases are closer to lottery tickets in terms of expected return.
Related Tools
Enhance your understanding of CS2 case economics with these complementary tools:
- Case Odds Calculator - Calculate exact probabilities for specific outcomes
- Case ROI Calculator - Calculate expected return on investment
- Monte Carlo Simulator - Run thousands of simulations for distribution analysis
- Variance Visualizer - Understand why results feel "random"
- Ruin Probability Calculator - Calculate bankroll depletion odds
- Case Opening Simulator - Single-session case opening practice
Last updated: January 2026