GAME — CS2 Stats
76561197979474181[U:1:19208453]✓ No bans
How this compares with the same rank
Median values for Level 10 among CSDB-tracked players (n=218), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.
| Metric | This player | Level 10 median |
|---|---|---|
| Headshot rate | 49.9% | 52.8% |
| Shot accuracy | 14.9% | 13.7% |
| Kill/death ratio | 1.34 | 1.08 |
| Match win rate | 56.5% | 49.2% |
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -10pp win rate · -0.05 avg rating
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Sharp aimerStrong CT-side opener
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 s1mple 95% playstyle similarity
Most alike: opening-fight frequency, positioning 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
Strengths
Aim. Aim score of 89 — the mechanical foundation is a clear strength.
CT openings. 68% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
Areas to improve
T-side openings. Opening success drops from 68% on CT to 41% on T — the same duels are being taken with worse setups on the attacking side.
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 7.2/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×0.95 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 |
|---|---|---|---|---|---|
| B | 25 | 13–12 | 52% | 0.05 | |
| S | 20 | 13–7 | 65% | 0.05 | |
| A | 15 | 9–6 | 60% | 0.02 | |
| S | 12 | 8–4 | 67% | 0.05 | |
| A | 8 | 5–3 | 63% | 0.03 | |
| S | 5 | 4–1 | 80% | 0.05 | |
| — | 4 | 3–1 | 75% | 0.07 | |
| — | 4 | 1–3 | 25% | 0.03 | |
| cache_b | — | 4 | 3–1 | 75% | 0.03 |
| — | 1 | 0–1 | 0% | -0.05 | |
| cbble_d | — | 1 | 1–0 | 100% | 0.08 |
| — | 1 | 1–0 | 100% | 0.08 |
Across the last 100 tracked matches.
Ancient is currently your weakest sufficiently-sampled map (52% over 25). Start with the 6 essential Ancient 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 resultsLWLLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Ancient | 1616 | 60% | 1.43 | 19.2 |
| Anubis | 1065 | 56% | 1.37 | 18.8 |
| Dust2 | 844 | 53% | 1.37 | 18.8 |
| Inferno | 521 | 57% | 1.42 | 18.6 |
| Mirage | 402 | 48% | 1.30 | 18.2 |
| Nuke | 330 | 51% | 1.31 | 17.7 |
| Overpass | 268 | 56% | 1.45 | 19.2 |
| Train | 261 | 58% | 1.42 | 18.7 |
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.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–11 | -0.03 | 33% | 27 Aug → | ||
| 13–8 | -0.01 | 35% | 22 Aug → | ||
| 14–16 | -0.01 | 34% | 18 Aug → | ||
| 7–13 | -0.03 | 31% | 18 Aug → | ||
| 13–7 | 0.07 | 38% | 17 Aug → | ||
| 9–13 | 0.01 | 31% | 8 Aug → | ||
| 5–13 | 0.07 | 25% | 8 Aug → | ||
| 19–15 | 0.10 | 28% | 8 Aug → | ||
| 13–7 | 0.02 | 28% | 1 Aug → | ||
| 8–13 | 0.04 | 23% | 22 Jul → | ||
| 10–13 | 0.03 | 22% | 12 Jul → | ||
| 13–10 | 0.09 | 49% | 12 Jul → | ||
| 14–16 | 0.07 | 20% | 12 Jul → | ||
| 14–16 | 0.05 | 29% | 17 Jun → | ||
| 13–8 | 0.06 | 30% | 15 Jun → | ||
| 13–8 | 0.05 | 13% | 15 Jun → | ||
| 9–13 | 0.03 | 31% | 15 Jun → | ||
| 13–6 | 0.11 | 32% | 15 Jun → | ||
| 13–10 | 0.14 | 35% | 15 Jun → | ||
| 13–10 | 0.08 | 16% | 14 Jun → | ||
| 13–4 | 0.02 | 50% | 12 Jun → | ||
| 13–8 | 0.08 | 25% | 12 Jun → | ||
| 9–13 | 0.05 | 20% | 12 Jun → | ||
| 13–4 | 0.09 | 30% | 10 Jun → | ||
| 13–11 | 0.09 | 26% | 9 Jun → | ||
| 8–13 | 0.00 | 23% | 9 Jun → | ||
| 13–8 | 0.09 | 28% | 9 Jun → | ||
| 19–16 | 0.11 | 23% | 9 Jun → | ||
| 7–13 | 0.01 | 24% | 9 Jun → | ||
| 10–13 | 0.02 | 26% | 9 Jun → | ||
| 9–13 | -0.02 | 20% | 8 Jun → | ||
| 1–13 | -0.06 | 23% | 8 Jun → | ||
| 7–13 | 0.01 | 24% | 1 Jun → | ||
| 13–5 | 0.06 | 28% | 1 Jun → | ||
| 14–16 | -0.02 | 23% | 31 May → | ||
| 13–10 | 0.06 | 31% | 31 May → | ||
| 13–11 | 0.02 | 30% | 31 May → | ||
| 10–0 | 0.19 | 17% | 31 May → | ||
| 13–8 | 0.04 | 29% | 31 May → | ||
| 8–13 | 0.01 | 17% | 31 May → | ||
| 19–16 | 0.04 | 18% | 31 May → | ||
| 16–13 | -0.03 | 21% | 28 May → | ||
| 9–13 | 0.03 | 21% | 28 May → | ||
| 13–6 | 0.05 | 25% | 23 May → | ||
| 13–10 | 0.03 | 28% | 18 May → | ||
| 11–13 | 0.06 | 26% | 18 May → | ||
| 13–6 | 0.05 | 23% | 15 May → | ||
| 11–13 | -0.01 | 13% | 15 May → | ||
| 13–7 | 0.15 | 28% | 9 May → | ||
| 16–13 | 0.03 | 31% | 8 May → | ||
| 13–4 | 0.05 | 39% | 7 May → | ||
| 19–16 | 0.01 | 18% | 6 May → | ||
| 13–8 | 0.04 | 40% | 4 May → | ||
| 7–13 | 0.01 | 31% | 2 May → | ||
| 7–13 | -0.02 | 29% | 22 Apr → | ||
| 13–11 | 0.06 | 45% | 19 Apr → | ||
| 22–19 | -0.01 | 29% | 16 Apr → | ||
| 13–5 | 0.05 | 26% | 13 Apr → | ||
| 13–6 | -0.04 | 39% | 13 Apr → | ||
| 13–11 | 0.01 | 42% | 13 Apr → | ||
| 13–10 | 0.00 | 41% | 13 Apr → | ||
| 11–13 | 0.05 | 24% | 10 Apr → | ||
| 13–1 | 0.06 | 27% | 10 Apr → | ||
| 2–13 | -0.00 | 31% | 6 Apr → | ||
| 4–13 | -0.02 | 20% | 1 Apr → | ||
| 2–13 | 0.02 | 18% | 1 Apr → | ||
| 10–13 | 0.06 | 17% | 1 Apr → | ||
| cache_b | 13–10 | 0.07 | 27% | 1 Apr → | |
| 13–4 | 0.12 | 36% | 1 Apr → | ||
| 13–8 | 0.01 | 31% | 28 Mar → | ||
| 13–10 | -0.06 | 35% | 26 Mar → | ||
| 13–7 | -0.02 | 20% | 23 Mar → | ||
| 9–13 | 0.01 | 15% | 23 Mar → | ||
| cache_b | 13–7 | 0.04 | 14% | 23 Mar → | |
| 13–9 | 0.08 | 21% | 23 Mar → | ||
| 13–8 | -0.01 | 22% | 23 Mar → | ||
| 10–13 | 0.01 | 27% | 23 Mar → | ||
| 1–13 | 0.04 | 18% | 23 Mar → | ||
| 14–16 | 0.04 | 23% | 16 Mar → | ||
| 9–13 | -0.05 | 29% | 16 Mar → | ||
| cbble_d | 13–6 | 0.08 | 33% | 16 Mar → | |
| cache_b | 13–16 | -0.03 | 18% | 16 Mar → | |
| 13–11 | 0.10 | 25% | 16 Mar → | ||
| 16–14 | -0.02 | 28% | 14 Mar → | ||
| 13–7 | 0.08 | 39% | 14 Mar → | ||
| cache_b | 13–9 | 0.04 | 16% | 14 Mar → | |
| 14–16 | 0.04 | 39% | 14 Mar → | ||
| 13–11 | 0.08 | 27% | 12 Mar → | ||
| 10–13 | 0.03 | 18% | 12 Mar → | ||
| 16–14 | 0.09 | 21% | 12 Mar → | ||
| 4–13 | 0.01 | 32% | 12 Mar → | ||
| 13–3 | 0.27 | 27% | 11 Mar → | ||
| 9–13 | 0.08 | 24% | 11 Mar → | ||
| 13–2 | 0.24 | 26% | 11 Mar → | ||
| 13–8 | 0.04 | 29% | 11 Mar → | ||
| 13–10 | 0.01 | 32% | 11 Mar → | ||
| 13–8 | 0.16 | 32% | 11 Mar → | ||
| 16–13 | 0.10 | 23% | 11 Mar → | ||
| 13–6 | -0.05 | 21% | 10 Mar → | ||
| 11–13 | 0.02 | 28% | 9 Mar → |
Match data via Leetify.