LoL Champion Counters and Matchups

How these matchup statistics are calculated

Counter and synergy statistics use Ranked Solo/Duo games, exclude matches shorter than 600 seconds, and group results by patch window, region, rank scope, and champion role.

Pairwise pages use a rolling three-patch window and compare observed win rate with a log-odds expected win rate based on each champion's role-adjusted baseline; listed pairs require at least 500 games.

Read the full methodology for the model and guidance on interpreting these results.

Summary

RiftMind's League of Legends counters page highlights enemy matchups where a champion-role performs worse than expected after accounting for both champions' usual role strength. Use same-role rows for the cleanest direct matchup signal, and use all-role rows for broader draft pressure.

Detailed info:

Questions this counters page answers

1. Best champion counters - Use the counters page to find enemy champion-role matchups where the selected champion performs worse than expected after role-adjusted baselines.
2. Counterpick shortlist - Start with same-role counter rows when choosing a direct lane or role answer, then check all-role rows for broader draft pressure.
3. Direct role matchups - Filter both champions to the same role when you want the closest proxy for lane or role-specific counterpick decisions.
4. Draft-level pressure - Use all-role counters to spot enemy champions that pressure a pick through jungle pathing, teamfight tools, scaling, anti-carry patterns, or composition fit.

Counter data fields on RiftMind

1. Observed win rate - The actual win rate for the champion-role in the listed enemy matchup after RiftMind filters by patch, region, rank scope, and minimum sample.
2. Expected win rate - A log-odds baseline that estimates how often the champion-role should win from each champion's usual role-adjusted strength.
3. Delta - Observed win rate minus expected win rate in percentage points. For counters, more negative deltas indicate harder matchups.
4. Games - The number of ranked games behind the pair. Larger samples are usually more stable, especially across patches and rank scopes.

How to read RiftMind counter data

1. Counter ranking method - Counters sort by expected-win-rate delta ascending, so the strongest counter entries are matchups where the champion-role performs worse than expected.
2. Same-role versus all-role counters - Same-role counters are closer to direct lane or role matchups; all-role counters can capture draft pressure, jungle interaction, teamfight tools, scaling, and anti-carry effects.
3. How to validate a counterpick - Check role, rank scope, patch window, and sample size. Public generated summaries use at least 500 games per listed pair.