LoL Champion Counters and Matchups

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. In Low Elo, notable same-role examples include Sion Mid is countered by Yone Mid, Aurelion Sol Mid is countered by Yone Mid, Yasuo Mid is countered by Volibear Mid, Malzahar Mid is countered by Sion Mid, Vladimir Mid is countered by Malzahar Mid, Yasuo Mid is countered by Azir Mid, Ahri Mid is countered by Mel Mid, Mel Mid is countered by Fizz Mid, Kassadin Mid is countered by Yone Mid, and Vex Mid is countered by Mel Mid. Use same-role rows for the cleanest direct matchup signal, and use all-role rows for broader draft pressure.

Updated 2026-11-15. Data is current for LoL patch 26.22 (all regions, low elo and high elo).

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.

Top 10 Low Elo same-role counter matchups

  1. Sion Mid vs Yone Mid - Low Elo data: Sion Mid against Yone Mid, 40.3% observed win rate, -8.3 percentage points vs expected, 1,273 games, 3-patch window 26.20-26.22.
  2. Aurelion Sol Mid vs Yone Mid - Low Elo data: Aurelion Sol Mid against Yone Mid, 41.3% observed win rate, -7.7 percentage points vs expected, 3,794 games, 3-patch window 26.20-26.22.
  3. Yasuo Mid vs Volibear Mid - Low Elo data: Yasuo Mid against Volibear Mid, 44.5% observed win rate, -7.4 percentage points vs expected, 1,106 games, 3-patch window 26.20-26.22.
  4. Malzahar Mid vs Sion Mid - Low Elo data: Malzahar Mid against Sion Mid, 42.7% observed win rate, -7.0 percentage points vs expected, 2,521 games, 3-patch window 26.20-26.22.
  5. Vladimir Mid vs Malzahar Mid - Low Elo data: Vladimir Mid against Malzahar Mid, 43.5% observed win rate, -5.9 percentage points vs expected, 4,864 games, 3-patch window 26.20-26.22.
  6. Yasuo Mid vs Azir Mid - Low Elo data: Yasuo Mid against Azir Mid, 48.8% observed win rate, -5.2 percentage points vs expected, 3,587 games, 3-patch window 26.20-26.22.
  7. Ahri Mid vs Mel Mid - Low Elo data: Ahri Mid against Mel Mid, 49.2% observed win rate, -5.1 percentage points vs expected, 10,798 games, 3-patch window 26.20-26.22.
  8. Mel Mid vs Fizz Mid - Low Elo data: Mel Mid against Fizz Mid, 39.2% observed win rate, -5.0 percentage points vs expected, 3,983 games, 3-patch window 26.20-26.22.
  9. Kassadin Mid vs Yone Mid - Low Elo data: Kassadin Mid against Yone Mid, 43.8% observed win rate, -5.0 percentage points vs expected, 3,497 games, 3-patch window 26.20-26.22.
  10. Vex Mid vs Mel Mid - Low Elo data: Vex Mid against Mel Mid, 49.9% observed win rate, -4.9 percentage points vs expected, 2,758 games, 3-patch window 26.20-26.22.

Top 10 High Elo same-role counter matchups

  1. Morgana Support vs Yuumi Support - High Elo data: Morgana Support against Yuumi Support, 46.1% observed win rate, -4.3 percentage points vs expected, 1,380 games, 3-patch window 26.20-26.22.
  2. Yuumi Support vs Nautilus Support - High Elo data: Yuumi Support against Nautilus Support, 43.9% observed win rate, -4.0 percentage points vs expected, 8,463 games, 3-patch window 26.20-26.22.
  3. Alistar Support vs Swain Support - High Elo data: Alistar Support against Swain Support, 48.9% observed win rate, -3.7 percentage points vs expected, 2,186 games, 3-patch window 26.20-26.22.
  4. Rakan Support vs Morgana Support - High Elo data: Rakan Support against Morgana Support, 47.6% observed win rate, -3.7 percentage points vs expected, 1,769 games, 3-patch window 26.20-26.22.
  5. Swain Support vs Yuumi Support - High Elo data: Swain Support against Yuumi Support, 45.3% observed win rate, -3.6 percentage points vs expected, 1,348 games, 3-patch window 26.20-26.22.
  6. Leona Support vs Morgana Support - High Elo data: Leona Support against Morgana Support, 48.2% observed win rate, -3.6 percentage points vs expected, 5,048 games, 3-patch window 26.20-26.22.
  7. Rakan Support vs Swain Support - High Elo data: Rakan Support against Swain Support, 49.3% observed win rate, -3.5 percentage points vs expected, 1,284 games, 3-patch window 26.20-26.22.
  8. Lux Support vs Yuumi Support - High Elo data: Lux Support against Yuumi Support, 47.6% observed win rate, -3.3 percentage points vs expected, 2,994 games, 3-patch window 26.20-26.22.
  9. Alistar Support vs Morgana Support - High Elo data: Alistar Support against Morgana Support, 49.0% observed win rate, -3.2 percentage points vs expected, 2,657 games, 3-patch window 26.20-26.22.
  10. Nautilus Support vs Swain Support - High Elo data: Nautilus Support against Swain Support, 47.4% observed win rate, -3.1 percentage points vs expected, 3,164 games, 3-patch window 26.20-26.22.

Most played matchup guides

  1. Caitlyn vs Jhin ADC - 8 researched tips and facts. Caitlyn wins 48.3% of 81,250 Low Elo games.
  2. Jhin vs Caitlyn ADC - 8 researched tips and facts. Jhin wins 51.6% of 81,250 Low Elo games.
  3. Caitlyn vs Jinx ADC - 8 researched tips and facts. Caitlyn wins 48.1% of 59,296 Low Elo games.
  4. Jinx vs Caitlyn ADC - 8 researched tips and facts. Jinx wins 51.9% of 59,296 Low Elo games.
  5. Caitlyn vs Kai'Sa ADC - 9 researched tips and facts. Caitlyn wins 49.5% of 58,277 Low Elo games.
  6. Kai'Sa vs Caitlyn ADC - 9 researched tips and facts. Kai'Sa wins 50.4% of 58,277 Low Elo games.
  7. Miss Fortune vs Caitlyn ADC - 8 researched tips and facts. Miss Fortune wins 51.9% of 55,249 Low Elo games.
  8. Caitlyn vs Miss Fortune ADC - 8 researched tips and facts. Caitlyn wins 48.1% of 55,249 Low Elo games.
  9. Miss Fortune vs Jhin ADC - 7 researched tips and facts. Miss Fortune wins 50.8% of 54,766 Low Elo games.
  10. Jhin vs Miss Fortune ADC - 7 researched tips and facts. Jhin wins 49.2% of 54,766 Low Elo games.

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 versus expected win rate in percentage points, scaled down for pairs with fewer games. 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 1,000 games per listed pair.

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 1,000 games.

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