?
ESL One Bangkok 2024. Открытые квалификации · BO1
result vs prediction
Habibisloss 0:1
series probability
39%61%
probability at match start · final 0:1
GG teamwin 1:0
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.

Habibis

No games played over 6 months.

GG team

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
Tusk
433 picks · 557 bans
52%
Clockwerk
Clockwerk
376 picks · 381 bans
53%
Pangolier
Pangolier
329 picks · 444 bans
49%
Luna
Luna
316 picks · 374 bans
54%
Enchantress
Enchantress
301 picks · 580 bans
51%
Dark Willow
Dark Willow
278 picks · 149 bans
49%
Dragon Knight
Dragon Knight
266 picks · 345 bans
50%
Batrider
Batrider
258 picks · 242 bans
50%
Prediction components
Form (series winrate)50% vs 57%
Hero pool strength50% Habibis
Head-to-head0 – 0
Model total61% GG team
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 correct21:53
Habibis 39%GG team 61%
The model gave 61% on GG team — the game was taken by GG team in 26:53.
Model check result
Model favoriteGG team · 61%
Series resultGG team 0:1
Series predictioncorrect
Accuracy by game1 of 1