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Digital Crusade Super DraculaN Season 1 · BO3
result vs prediction
Sashi#94 in the world · loss 1:2
series probability
39%61%
probability at match start · final 1:2
Inner Circle#28 in the world · win 2:1
The prediction was locked in using data as of the match start: map winrates, form and head-to-head were computed only from games before it began. This is how the model's honest accuracy is verified.
Map veto prediction
For each map — both teams' winrate over 3 months. The model guesses who bans it and who keeps it: teams remove maps where they are weaker and pull toward their strong ones.
Dust2Inner Circle pick
33%56%
Sashi · 8 mapsedge Inner Circle +23%Inner Circle · 5 maps
NukeSashi ban
45%50%
Sashi · 7 mapsedge Inner Circle +5%Inner Circle · 4 maps
AncientSashi pick
50%50%
Sashi · 4 mapsnearly even +0%Inner Circle · 4 maps
MirageSashi ban
50%50%
Sashi · 0 mapsnearly even +0%Inner Circle · 6 maps
InfernoInner Circle ban
75%50%
Sashi · 4 mapsedge Sashi +25%Inner Circle · 0 maps
OverpassInner Circle ban
60%57%
Sashi · 1 mapnearly even +3%Inner Circle · 3 maps
Anubispossible decider
60%50%
Sashi · 1 mapedge Sashi +10%Inner Circle · 0 maps
Most likely veto scenario
1. BanSashi remove Mirage
2. BanInner Circle remove Inferno
3. PickSashi take Ancient
4. PickInner Circle take Dust2
5. BanInner Circle remove Overpass
6. BanSashi remove Nuke
DeciderAnubis (60% / 50%)
Prediction by map vs result
Probabilities were locked in using statistics as of the match start (map winrate over the 3 months before it). We compare against the actual result of each map.
Overpassprediction correct16:14
Sashi 56%Inner Circle 44%
The model gave 56% on Sashi — the map was taken by Sashi.
Dust2prediction correct12:16
Sashi 26%Inner Circle 74%
The model gave 74% on Inner Circle — the map was taken by Inner Circle.
Nukeprediction correct14:16
Sashi 45%Inner Circle 55%
The model gave 55% on Inner Circle — the map was taken by Inner Circle.
Model check result
Model favoriteInner Circle · 61%
Series resultInner Circle 1:2
Series predictioncorrect
Accuracy by map3 of 3