FINAL
27 Feb 2023 22:40 UTC
CQ-GESUS CS2-APEX
SHAP
AUC 0.702
52% CONF
WRONG
GamerLegion 52.1%
47.9% VOYVODA
Why this prediction?
+100.0
Elo advantage
+84.2
Elo implied probability
+75.5
Elo win probability
−46.2
Schedule difficulty edge
−37.7
Avg opponent quality diff
+32.5
Consensus Win Prob Team1
+29.3
Days since last match (T1)
+26.6
Glicko2 rating (T2)
+25.2
Elo (T1)
+24.7
Glicko2 rating (T1)
mirage
16
–
19
OT
VOYVODA WON
Round timeline loading — available after demo parsing
Round — Player Stats
| Player | K | D | A | HS | ADR | KAST |
|---|---|---|---|---|---|---|
|
|
| Player | Rating | K | D | A | HS% | ADR | KAST |
|---|---|---|---|---|---|---|---|
| VOYVODA ★ won this map | |||||||
|
h4rn
BG
|
1.50 | 32 | 16 | 0 | 0% | 90.5 | 82.9% |
| GamerLegion | |||||||
|
iM
RO
|
1.37 | 31 | 25 | 0 | 0% | 100.1 | 80.0% |
|
acoR
DK
|
1.13 | 27 | 23 | 0 | 0% | 78.1 | 74.3% |
| VOYVODA ★ won this map | |||||||
|
REDSTAR
BG
|
1.04 | 26 | 26 | 0 | 0% | 76.0 | 68.6% |
| GamerLegion | |||||||
|
siuhy
PL
|
0.86 | 20 | 23 | 0 | 0% | 52.2 | 57.1% |
|
Keoz
BE
|
0.73 | 15 | 29 | 0 | 0% | 59.4 | 65.7% |
|
isak
SE
|
0.73 | 16 | 22 | 0 | 0% | 45.9 | 62.9% |
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inferno
8
–
16
VOYVODA WON
Round timeline loading — available after demo parsing
Round — Player Stats
| Player | K | D | A | HS | ADR | KAST |
|---|---|---|---|---|---|---|
|
|
| Player | Rating | K | D | A | HS% | ADR | KAST |
|---|---|---|---|---|---|---|---|
| VOYVODA ★ won this map | |||||||
|
REDSTAR
BG
|
1.65 | 24 | 15 | 0 | 0% | 107.0 | 79.2% |
| GamerLegion | |||||||
|
iM
RO
|
1.10 | 17 | 15 | 0 | 0% | 84.7 | 70.8% |
|
siuhy
PL
|
1.03 | 13 | 16 | 0 | 0% | 71.4 | 70.8% |
| VOYVODA ★ won this map | |||||||
|
h4rn
BG
|
0.90 | 9 | 11 | 0 | 0% | 45.3 | 75.0% |
| GamerLegion | |||||||
|
acoR
DK
|
0.87 | 10 | 14 | 0 | 0% | 35.7 | 62.5% |
|
Keoz
BE
|
0.86 | 17 | 19 | 0 | 0% | 78.3 | 50.0% |
|
isak
SE
|
0.62 | 7 | 16 | 0 | 0% | 49.2 | 54.2% |
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Available after demo parsing completes
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Available after the demo pipeline processes this match
Quantum Locked
Quantum signals require Uranium-tier data: <10% null features.
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