Player
22Clutches won
1v5Best clutch won
1.02Rating
37Maps
1.11K/D
69.0ADR
35%HS
69%KAST
85–46Opening duels
By map
| Map | Maps | K/D | ADR |
|---|---|---|---|
| mirage | 10 | 1.29 | 64.6 |
| ancient | 9 | 1.06 | 70.7 |
| dust2 | 7 | 1.28 | 80.6 |
| nuke | 5 | 1.07 | 75.8 |
| overpass | 3 | 0.66 | 53.8 |
| inferno | 2 | 0.60 | 34.2 |
| anubis | 1 | 1.50 | 80.3 |
Last 20 maps
| Opponent | Map | K–D | ADR |
|---|---|---|---|
| ALKA | mirage | 12–9 | 51.5 |
| ALKA | ancient | 18–11 | 83.6 |
| Meia Noite | nuke | 24–20 | 70.3 |
| Meia Noite | ancient | 18–17 | 64.0 |
| Meia Noite | dust2 | 11–7 | 71.5 |
| ALKA | ancient | 14–16 | 71.0 |
| ALKA | nuke | 14–15 | 71.7 |
| ALKA | mirage | 15–9 | 82.8 |
| MIBR Academy | dust2 | 20–9 | 109.5 |
| MIBR Academy | mirage | 22–13 | 81.3 |
| MIBR Academy | nuke | 37–20 | 100.1 |
| largadosypelados | dust2 | 16–22 | 74.7 |
| largadosypelados | mirage | 17–18 | 58.3 |
| largadosypelados | inferno | 6–13 | 28.8 |
| QUINTESSÊNCIA | ancient | 15–6 | 93.1 |
| QUINTESSÊNCIA | mirage | 17–12 | 68.7 |
| QUINTESSÊNCIA | dust2 | 18–14 | 86.7 |
| Team Spirit | overpass | 5–12 | 55.3 |
| Team Spirit | ancient | 7–12 | 42.2 |
| Team Spirit | mirage | 9–14 | 44.0 |
Team history
| Team | Maps | Period |
|---|---|---|
 Mira | 5 | 2026-09 – 2026-09 |
 RED Canids Academy | 19 | 2026-02 – 2026-07 |
 RED Canids | 8 | 2026-04 – 2026-04 |
| internet kings | 5 | 2026-01 – 2026-01 |
Career by year
| Year | Maps | Rating | ADR | KAST |
|---|---|---|---|---|
| 2026 | 37 | 1.02 | 69.0 | 69% |
Rating by event
| Event | Maps | Rating | ADR | KAST |
|---|---|---|---|---|
| CCT 2026 South America Series 6 | 5 | 1.11 | 68.0 | 74% |
| Gamers Club Liga Série A: June 2026 | 6 | 1.25 | 86.9 | 74% |
| Gamers Club Serie A: May 2026 | 6 | 0.94 | 69.2 | 67% |
| IEM Rio 2026 | 8 | 0.81 | 55.3 | 63% |
| Liga Gamers Club Série A 2026 February | 5 | 0.99 | 61.4 | 71% |
| Liga Gamers Club Série A 2026 January | 2 | 0.62 | 41.8 | 58% |
| CCT Season 3 South America Series 7 | 5 | 1.19 | 83.9 | 73% |
ADR and KAST are our own calculations from round data. Rating is our calculation from round data (1.0 formula).
