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NukeMap 1
OverpassMap 2
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Map Results
W
Vitality
W–L
L
RED Canids
Duration: 42:52
W
Vitality
W–L
L
RED Canids
Duration: 45:20
Streams
Map Breakdown
Series best: ZywOo — 2.10 average rating across 2 maps.
Overpass
Vitality 13–6 RED CanidsVitality1st half 9 · 2nd half 4CT 4/7 · T 9/12Pistols 2/2
RED Canids1st half 3 · 2nd half 3CT 3/12 · T 3/7Pistols 0/2
| Player | K | D | A | +/− | ADR | KAST | Rating |
|---|---|---|---|---|---|---|---|
| ZywOoVitality | 21 | 8 | 3 | +13 | 105.8 | 90% | 1.86 |
| meziiVitality | 20 | 10 | 6 | +10 | 95.1 | 95% | 1.59 |
| flameZVitality | 16 | 14 | 5 | +2 | 90.9 | 84% | 1.59 |
| apEXVitality | 11 | 9 | 10 | +2 | 77.2 | 79% | 1.02 |
| ropzVitality | 13 | 13 | 3 | +0 | 71.7 | 79% | 0.96 |
| kauezRED Canids | 11 | 17 | 4 | -6 | 61.7 | 68% | 0.96 |
| chayJESUSRED Canids | 12 | 15 | 5 | -3 | 87.7 | 58% | 0.94 |
| reNTURED Canids | 12 | 15 | 3 | -3 | 60.4 | 58% | 0.87 |
| dav1deuSRED Canids | 11 | 18 | 5 | -7 | 57.8 | 68% | 0.69 |
| dropRED Canids | 8 | 16 | 4 | -8 | 48.9 | 53% | 0.51 |
Nuke
Vitality 13–4 RED CanidsVitality1st half 11 · 2nd half 2CT 11/12 · T 2/5Pistols 2/2
RED Canids1st half 1 · 2nd half 3CT 3/5 · T 1/12Pistols 0/2
| Player | K | D | A | +/− | ADR | KAST | Rating |
|---|---|---|---|---|---|---|---|
| ZywOoVitality | 24 | 10 | 1 | +14 | 138.5 | 94% | 2.34 |
| flameZVitality | 18 | 7 | 3 | +11 | 101.0 | 82% | 1.72 |
| ropzVitality | 12 | 10 | 5 | +2 | 77.2 | 82% | 1.23 |
| chayJESUSRED Canids | 14 | 12 | 2 | +2 | 87.2 | 71% | 1.22 |
| apEXVitality | 8 | 10 | 6 | -2 | 60.5 | 82% | 1.03 |
| dav1deuSRED Canids | 13 | 14 | 2 | -1 | 84.8 | 65% | 1.02 |
| meziiVitality | 8 | 8 | 4 | +0 | 57.5 | 77% | 0.91 |
| reNTURED Canids | 6 | 14 | 1 | -8 | 42.6 | 47% | 0.51 |
| kauezRED Canids | 6 | 14 | 0 | -8 | 32.6 | 41% | 0.49 |
| dropRED Canids | 6 | 16 | 2 | -10 | 53.4 | 53% | 0.48 |
About Vitality vs RED Canids
This BO3 Counter-Strike 2 match is part of Group A on the IEM circuit. Vitality took the series 2–0. For head-to-head form and predicted lineups, see the head-to-head tool and the prediction model.