The most accurate
League of Legends
draft tool.

Most draft tools rely on simple champion-vs-champion win rate statistics and fixed formulas to estimate draft strength. LoLDraftAI is fundamentally different: it uses a custom-trained neural network that learns directly from millions of game outcomes. This means it captures complex interactions like team composition synergies, multi-lane dynamics, and scaling patterns that formula-based tools miss. The model is updated with every new patch.

DraftGap, iTero, and LoLTheory all rely on champion-vs-champion matchup statistics. They evaluate a draft as a list of pairs. LoLDraftAI is a neural network that reads the whole draft together, so it can reason about things like a team's damage profile or scaling. It outperforms all three on real matches neither tool had seen before. See the DraftGap, iTero, and LoLTheory comparisons for the numbers.

LoLDraftAI is the only rune tool that takes the entire draft into account: your team, the enemy team, and every matchup, when recommending runes. Other tools suggest runes based on your champion alone or simple matchup lookups. Because the rune model shares the same base as the draft prediction model, it has a deep understanding of champion interactions and can tailor rune choices to your specific game.

Not at all. LoLDraftAI uses a custom-trained machine learning model built specifically for League of Legends draft prediction. It is trained on millions of real ranked games and learns the complex relationships between champions, matchups, synergies, team compositions, and game dynamics, directly from match outcomes. Learn more about how it works.

The model achieves 56.7% accuracy at predicting game outcomes from draft alone, and 57.7% when runes are included. This is significant considering draft is only one factor in winning a game. The model is also well-calibrated: when it predicts a 55% win rate, games really do end up around 55%, meaning you can trust the predicted percentages. In our internal study, taking the model's top suggestion as the last pick raised the picking team's predicted win rate by +4% to +7% on average, depending on whether we benchmark against random pick order or a more realistic order in which the strongest champion is assumed to be the last pick. See the per-pick lift study for the full curve.

The model evaluates the strength of a draft composition as a whole. Since the Riot API does not provide pick order data, the model is not inherently counter-pick aware. However, LoLDraftAI offers a Typical Counterpick Adjusted mode in champion recommendations, which adjusts predicted winrates based on how much each champion's impact typically swings when counterpicked, helping you identify safe blind picks.

The model is updated with every new patch. Patches typically release on Thursday, and the model usually updates by Saturday to have enough games for reliable data. The model can be used on the new patch immediately. Champion synergies and counters stay mostly the same between patches, so accuracy barely decreases.