green cat with commando hat — CS2 Stats
76561198126697210[U:1:166431482]✓ No bans
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +0pp win rate · +0.00 avg rating
Player DNA
Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.
Your pro match

Plays most like NiKo 79% playstyle similarity
Most alike: opening-fight frequency, opening-duel success.
Where you differ: lower utility contribution; lower aim profile.
Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →
Strengths & areas to improve
Areas to improve
Reaction time. 656ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.
Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.
CSDB Rating breakdown
Composite 4.7/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.
Trends
Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
| A | 29 | 17–12 | 59% | -0.01 | |
| C | 21 | 9–12 | 43% | 0.02 | |
| A | 12 | 7–5 | 58% | -0.01 | |
| S | 12 | 8–4 | 67% | 0.01 | |
| C | 11 | 4–7 | 36% | 0.01 | |
| D | 9 | 3–6 | 33% | 0.00 | |
| A | 5 | 3–2 | 60% | 0.01 | |
| — | 1 | 1–0 | 100% | 0.06 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.
Lifetime stats
Most-used weapons
Lifetime map wins
Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWLWLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Dust2 | 22 | 68% | 0.98 | 13.9 |
| Mirage | 13 | 38% | 0.93 | 14.8 |
| Ancient | 10 | 50% | 1.18 | 17.8 |
| Anubis | 9 | 89% | 1.06 | 14.6 |
| Inferno | 5 | 60% | 0.90 | 15.0 |
| Cache | 4 | 25% | 0.96 | 15.5 |
| Train | 3 | 67% | 0.94 | 15.0 |
| Nuke | 3 | 67% | 1.04 | 17.0 |
Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.
Skill profile
Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.
Recommended for you
Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.
- Grenades & UtilityGrenade Lineups →
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 3.5634 — below the 4 mark we flag
- Advanced Mechanics
You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.
T opening duels 25.8806% — below the 40% mark we flag
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 8–13 | -0.07 | 8% | 23 Aug → | ||
| 13–4 | 0.08 | 23% | 23 Aug → | ||
| 8–13 | -0.10 | 24% | 16 Aug → | ||
| 8–13 | -0.09 | 16% | 15 Aug → | ||
| 6–5 | -0.08 | 21% | 15 Aug → | ||
| 14–16 | -0.05 | 12% | 15 Aug → | ||
| 9–13 | -0.01 | 25% | 15 Aug → | ||
| 13–10 | 0.01 | 17% | 14 Aug → | ||
| 13–3 | 0.07 | 23% | 14 Aug → | ||
| 13–9 | -0.04 | 12% | 14 Aug → | ||
| 16–12 | 0.07 | 15% | 14 Aug → | ||
| 13–9 | -0.03 | 28% | 14 Aug → | ||
| 13–11 | -0.01 | 19% | 14 Aug → | ||
| 7–13 | -0.09 | 20% | 14 Aug → | ||
| 9–13 | -0.03 | 20% | 13 Aug → | ||
| 13–8 | 0.02 | 15% | 13 Aug → | ||
| 5–13 | -0.13 | 22% | 13 Aug → | ||
| 8–13 | -0.03 | 22% | 13 Aug → | ||
| 10–13 | -0.06 | 18% | 13 Aug → | ||
| 13–3 | -0.01 | 24% | 13 Aug → | ||
| 13–7 | 0.02 | 10% | 13 Aug → | ||
| 14–16 | -0.03 | 29% | 13 Aug → | ||
| 9–13 | 0.03 | 18% | 12 Aug → | ||
| 13–5 | 0.04 | 32% | 12 Aug → | ||
| 6–13 | -0.05 | 21% | 12 Aug → | ||
| 6–13 | -0.02 | 19% | 11 Aug → | ||
| 8–13 | -0.02 | 13% | 11 Aug → | ||
| 13–16 | 0.06 | 12% | 9 Aug → | ||
| 11–13 | 0.03 | 20% | 8 Aug → | ||
| 13–7 | 0.05 | 17% | 7 Aug → | ||
| 4–13 | -0.00 | 35% | 3 Aug → | ||
| 6–13 | -0.05 | 11% | 2 Aug → | ||
| 13–11 | -0.06 | 29% | 30 Jul → | ||
| 13–10 | 0.02 | 18% | 30 Jul → | ||
| 16–12 | -0.02 | 30% | 30 Jul → | ||
| 13–4 | 0.07 | 22% | 30 Jul → | ||
| 16–12 | -0.05 | 24% | 29 Jul → | ||
| 14–16 | -0.02 | 15% | 28 Jul → | ||
| 9–13 | -0.07 | 16% | 28 Jul → | ||
| 13–10 | 0.03 | 12% | 28 Jul → | ||
| 13–8 | 0.05 | 19% | 18 Jul → | ||
| 13–10 | 0.02 | 14% | 18 Jul → | ||
| 13–4 | 0.28 | 19% | 18 Jul → | ||
| 13–5 | 0.07 | 19% | 18 Jul → | ||
| 13–9 | 0.00 | 19% | 3 Jul → | ||
| 9–13 | 0.08 | 14% | 3 Jul → | ||
| 13–9 | -0.00 | 33% | 3 Jul → | ||
| 13–8 | -0.06 | 26% | 3 Jul → | ||
| 3–13 | 0.01 | 31% | 28 Jun → | ||
| 13–7 | 0.02 | 23% | 22 Jun → | ||
| 6–13 | -0.02 | 7% | 25 May → | ||
| 11–13 | -0.00 | 18% | 25 May → | ||
| 13–5 | 0.04 | 22% | 25 May → | ||
| 13–9 | 0.03 | 17% | 24 May → | ||
| 13–6 | -0.01 | 18% | 24 May → | ||
| 14–16 | -0.04 | 10% | 16 May → | ||
| 9–13 | -0.03 | 23% | 16 May → | ||
| 13–5 | 0.04 | 23% | 16 May → | ||
| 10–13 | -0.05 | 14% | 16 May → | ||
| 13–11 | -0.01 | 21% | 15 May → | ||
| 10–13 | 0.02 | 21% | 14 May → | ||
| 5–13 | -0.08 | 16% | 11 May → | ||
| 16–12 | 0.04 | 33% | 11 May → | ||
| 15–15 | 0.01 | 20% | 10 May → | ||
| 13–10 | 0.11 | 14% | 9 May → | ||
| 16–13 | 0.05 | 18% | 9 May → | ||
| 13–4 | -0.03 | 21% | 9 May → | ||
| 11–13 | 0.04 | 17% | 9 May → | ||
| 8–13 | -0.03 | 23% | 9 May → | ||
| 3–13 | 0.05 | 26% | 9 May → | ||
| 4–13 | -0.06 | 25% | 9 May → | ||
| 13–11 | 0.00 | 16% | 9 May → | ||
| 5–13 | -0.01 | 19% | 8 May → | ||
| 11–13 | 0.09 | 28% | 6 May → | ||
| 8–13 | 0.04 | 34% | 6 May → | ||
| 13–6 | 0.02 | 16% | 6 May → | ||
| 8–13 | -0.01 | 28% | 6 May → | ||
| 13–11 | -0.01 | 29% | 6 May → | ||
| 13–10 | 0.08 | 33% | 6 May → | ||
| 6–13 | -0.04 | 10% | 5 May → | ||
| 14–16 | 0.03 | 14% | 5 May → | ||
| 13–9 | 0.02 | 29% | 5 May → | ||
| 14–16 | 0.02 | 13% | 5 May → | ||
| 11–13 | -0.03 | 43% | 5 May → | ||
| 13–11 | -0.01 | 26% | 5 May → | ||
| 7–13 | 0.06 | 26% | 29 Apr → | ||
| 10–13 | -0.04 | 29% | 29 Apr → | ||
| 13–11 | -0.02 | 39% | 29 Apr → | ||
| 13–10 | -0.04 | 21% | 29 Apr → | ||
| 9–13 | 0.03 | 17% | 28 Apr → | ||
| 8–13 | 0.02 | 26% | 27 Apr → | ||
| 13–3 | 0.09 | 32% | 27 Apr → | ||
| 13–9 | 0.09 | 34% | 27 Apr → | ||
| 13–7 | 0.06 | 33% | 26 Apr → | ||
| 16–12 | 0.08 | 16% | 25 Apr → | ||
| 13–7 | -0.05 | 27% | 25 Apr → | ||
| 7–13 | -0.01 | 28% | 24 Apr → | ||
| 13–10 | 0.01 | 20% | 24 Apr → | ||
| 13–6 | 0.05 | 36% | 24 Apr → | ||
| 16–13 | 0.04 | 12% | 24 Apr → |
Match data via Leetify.