ESL One Bangkok 2024. Закрытые квалификации · BO3
result vs predictionTMTeam Mansafwin 2:0
series probability
44%56%
probability at match start · final 2:0
RSRogue Squadloss 0:2
The prediction was locked in using data as of the match start: hero winrates, form and head-to-head were computed only from games before it began. This is how the model's honest accuracy is verified.
Teams' go-to heroes · 6 months
Who plays what and how often they win. "Signature" — from 6 games with a 60%+ winrate: such a pick statistically raises the win chance.
Team Mansaf
No games played over 6 months.
Rogue Squad
No games played over 6 months.
Patch meta · 3 months
The most picked heroes of the pro scene and their winrate. Picking a meta hero adds points to the team in the model.
Tusk
439 picks · 581 bans
Clockwerk
376 picks · 393 bans
Luna
327 picks · 390 bans
Pangolier
326 picks · 454 bans
Enchantress
307 picks · 581 bans
Dark Willow
287 picks · 156 bans
Dragon Knight
274 picks · 328 bans
Sand King
262 picks · 772 bans
Prediction components
Form (series winrate)60% vs 60%
Hero pool strength50% Team Mansaf
Head-to-head0 – 0
Model total56% Rogue Squad
Prediction by game vs result
Probabilities were locked in using statistics as of the match start: the draft was assessed by hero comfort, counter-picks and late-game potential. We compare against the actual result.
Game 1prediction missed36:18
Team Mansaf 44%Rogue Squad 56%
The model gave 56% on Rogue Squad — the game was taken by Team Mansaf in 38:55.
Game 2prediction missed38:25
Team Mansaf 44%Rogue Squad 56%
The model gave 56% on Rogue Squad — the game was taken by Team Mansaf in 35:13.
Model check result
Model favoriteRogue Squad · 56%
Series resultTeam Mansaf 2:0
Series predictionmissed
Accuracy by game0 of 2