Riyadh Masters 2023 · BO3
result vs prediction
Entityloss 0:2series probability
33%67%
probability at match start · final 0:2
OGwin 2:0The 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.
Entity
No games played over 6 months.
OG
Rubick
Taiga · 34 games
Invokeroften banned
bzm · 18 games
Disruptor
Chuvash · 17 games
Monkey Kingoften banned
Taiga · 17 games
Venomancersignature
DM · 17 games
Doomoften banned
DM · 16 games
Keeper of the Lightsignature
Taiga · 16 games
Dark Willow
Taiga · 15 games
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.
Techies
639 picks · 691 bans
Rubick
494 picks · 321 bans
Doom
450 picks · 986 bans
Ember Spirit
403 picks · 856 bans
Batrider
399 picks · 938 bans
Void Spirit
392 picks · 353 bans
Beastmaster
381 picks · 1007 bans
Pugna
379 picks · 450 bans
Prediction components
Form (series winrate)25% vs 34%
Hero pool strength52% OG
Head-to-head1 – 7
Model total67% OG
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 correct32:27
Entity 33%OG 67%
The model gave 67% on OG — the game was taken by OG in 42:15.
Game 2prediction correct17:31
Entity 33%OG 67%
The model gave 67% on OG — the game was taken by OG in 29:36.
Model check result
Model favoriteOG · 67%
Series resultOG 0:2
Series predictioncorrect
Accuracy by game2 of 2