Use your favourite features in-game with our Desktop AppLoL Tier List for All Roles, Platinum+
| Current patch | 25.24 |
| Last updated | 11 days ago |
Based on the matches analyzed in Patch 25.24, the top 5 highest win rate champions up to low Diamond are Swain Bot, Briar Jungle, Milio Support, Rumble Mid, and Veigar Bot. By picking and mastering these champions, you will have a much higher chance of winning games in the current patch. Furthermore, if you're interested in tier list curated by our high elo players, please refer to our low elo and high elo tier lists.
Rank | Role | Champion | Changes | Tier | Win | Pick | Ban | Matches | Counters | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
1 |  |  | — |  Optimal | 52.7% | 22.0% | 18.3% | 615 866 |      | ||
2 | |  | — |  Great | 49.3% | 17.5% | 21.7% | 490 155 | | ||
3 | | | — | Optimal | 50.7% | 17.1% | 3.3% | 477 830 |    | ||
4 | | | — | Great | 49.1% | 16.7% | 2.7% | 467 453 |   | ||
5 | | | — | Optimal | 51.2% | 13.1% | 3.0% | 365 360 | | ||
6 | |  | — |  Situational | 48.4% | 12.1% | 2.9% | 339 361 | | ||
7 | |  | — | Great | 50.4% | 11.9% | 6.7% | 333 228 | | ||
8 | | | — | Optimal | 51.8% | 10.4% | 5.0% | 290 165 | | ||
9 | | | — | Optimal | 51.9% | 8.8% | 7.1% | 244 433 | | ||
10 | |  | — |  Not Good | 48.7% | 7.7% | 2.3% | 216 264 | | ||
11 | |  | — | Situational | 49.6% | 6.8% | 2.9% | 190 476 | | ||
12 | |  | — | Not Good | 47.0% | 6.6% | 3.9% | 184 887 |  | ||
13 | | | — | Situational | 49.8% | 5.3% | 1.9% | 147 298 | | ||
14 | | | — |  Good | 50.2% | 5.1% | 8.9% | 143 755 |   | ||
15 | | | — | Good | 50.7% | 4.5% | 2.0% | 126 923 | | ||
16 | |  | — | Not Good | 46.4% | 3.9% | 0.9% | 108 563 | | ||
17 | | | — | Situational | 49.9% | 3.7% | 4.0% | 104 615 | | ||
18 | | | — | Good | 50.4% | 3.7% | 0.5% | 104 411 | | ||
19 | |  | — | Not Good | 47.9% | 3.6% | 10.3% | 100 710 | | ||
20 | | | — | Not Good | 49.1% | 2.9% | 0.3% | 81 490 | | ||
21 | | | — | Great | 52.2% | 2.0% | 0.9% | 54 957 | | ||
22 | | | — | Optimal | 53.1% | 1.5% | 2.3% | 41 243 | | ||
23 | |  | — | Good | 51.4% | 1.5% | 0.6% | 41 057 | | ||
24 | |  | — | Not Good | 47.0% | 1.4% | 0.3% | 39 633 | | ||
25 | |  | — | Optimal | 54.3% | 1.1% | 4.4% | 31 329 | | ||
26 | |  | — | Not Good | 48.4% | 1.1% | 60.2% | 30 168 | | ||
27 | |  | — | Not Good | 46.8% | 1.0% | 0.3% | 28 757 | | ||
28 | |  | — | Good | 50.8% | 0.9% | 20.6% | 25 164 | | ||
29 | |  | — | Optimal | 53.2% | 0.6% | 2.2% | 15 731 | | ||
30 | |  | — | Not Good | 49.7% | 0.4% | 0.7% | 11 412 | | ||
31 | |  | — | Great | 52.0% | 0.2% | 2.2% | 6 541 | | ||
32 | |  | — | Great | 52.2% | 0.2% | 0.9% | 5 647 | | ||
33 | |  | — | Great | 52.2% | 0.1% | 0.4% | 3 210 | | ||