Info

Welcome to the Stats Lab!

The tools here are prototypes made by LuzRaposa. They currently use Big Event ("Tier 1") demo data from 2026 and are updated after each new event. We also process some smaller tournament data to make the Roster Move Simulator more fun, but you can toggle this on or off for each tool. If you have any questions or just like what you see, reach out to us on social media — we look forward to hearing from you!

What is Duel Swing?

Duel Swing is our signature "pure firepower" metric. Each duel is assigned a win probability for both players based on their health, armor, weapons, distance, and vision — the winner gains points equal to their opponent's probability, and the loser loses points equal to theirs. This naturally adjusts for economic situations, since weapon quality and resources are already baked into the probability.

For a full breakdown, see the Duel Swing article on rdy.gg.

What is Round Swing?

Our Round Swing is not the same as HLTV's metric of the same name. Ours uses a meticulously calibrated neural network model to calculate the probabilities of a team winning the current round. Whenever a player takes a significant action (like getting a kill, planting the bomb, assisting a teammate, dying, etc.), we measure the difference in their team's win probability before and after the action happened and award them the difference. By adding together a player's round probability deltas for an entire map, we get "Round Swing Sum", which indicates how a player's actions impacted their team's chances of winning.

How does our rating system work?

Our system evaluates player performance using Duel Swing to measure the volume and quality of a player's kills, plus Round Swing to track how individual actions impact round win probability. It also features a small role-adjustment metric that benchmarks players against the average for their specific positions. This individual-focused approach is less team-dependent than traditional ratings (HLTV, Leetify, etc.) and uses a 0-100 scale to highlight gaps between good, great, and elite players.

For a full explanation, see the Win Condition CS podcast episode.