Diyar — CS2 Stats
76561198166337667[U:1:206071939]✓ No bans
How this compares with the same rank
Median values for Level 10 among CSDB-tracked players (n=3,007), 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 | 58.6% | 52.0% |
| Shot accuracy | 14.2% | 13.7% |
| Kill/death ratio | 1.68 | 1.08 |
| Match win rate | 50.5% | 48.8% |
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -20pp win rate · -0.01 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
Limited utility dependence
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 sh1ro 89% playstyle similarity
Most alike: opening-fight frequency, positioning profile.
Where you differ: lower aim profile; lower utility contribution.
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
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
Reaction time. 559ms 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 6.6/10 (Solid), 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 | 25 | 15–10 | 60% | 0.01 | |
| A | 22 | 14–8 | 64% | 0.03 | |
| S | 18 | 12–6 | 67% | 0.03 | |
| C | 8 | 3–5 | 38% | 0.01 | |
| C | 7 | 3–4 | 43% | 0.03 | |
| A | 7 | 4–3 | 57% | 0.05 | |
| A | 7 | 4–3 | 57% | 0.01 | |
| — | 2 | 2–0 | 100% | 0.04 | |
| cache_b | — | 2 | 0–2 | 0% | 0.02 |
| — | 1 | 1–0 | 100% | -0.01 | |
| — | 1 | 1–0 | 100% | 0.04 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (38% over 8). 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 resultsLWLLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 166 | 51% | 1.06 | 16.5 |
| Dust2 | 125 | 50% | 1.16 | 18.6 |
| Ancient | 111 | 62% | 1.23 | 18.0 |
| Inferno | 47 | 57% | 1.16 | 17.5 |
| Nuke | 45 | 40% | 0.99 | 16.4 |
| Anubis | 36 | 58% | 1.06 | 17.1 |
| Train | 19 | 58% | 1.35 | 19.4 |
| Overpass | 9 | 44% | 1.08 | 18.0 |
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
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
38% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–10 | -0.02 | 19% | 19 Jul → | ||
| 8–13 | 0.04 | 19% | 18 Jul → | ||
| 14–16 | 0.02 | 23% | 24 Jun → | ||
| 6–13 | 0.00 | 13% | 2 Jun → | ||
| 13–6 | 0.09 | 17% | 12 May → | ||
| 13–11 | -0.02 | 21% | 12 May → | ||
| 10–13 | -0.02 | 13% | 9 May → | ||
| 13–7 | -0.01 | 23% | 9 May → | ||
| 13–7 | 0.08 | 35% | 2 May → | ||
| 4–13 | -0.01 | 13% | 20 Apr → | ||
| 17–19 | -0.01 | 22% | 19 Apr → | ||
| 13–7 | -0.01 | 26% | 13 Apr → | ||
| 13–11 | -0.02 | 21% | 13 Apr → | ||
| 7–13 | -0.03 | 27% | 10 Apr → | ||
| 9–5 | 0.16 | 17% | 8 Apr → | ||
| 13–10 | 0.10 | 23% | 6 Apr → | ||
| 13–7 | 0.04 | 24% | 6 Apr → | ||
| 13–11 | -0.01 | 18% | 4 Apr → | ||
| 13–6 | 0.02 | 20% | 4 Apr → | ||
| 7–13 | 0.00 | 17% | 2 Apr → | ||
| 13–8 | 0.05 | 17% | 2 Apr → | ||
| 2–13 | -0.02 | 23% | 2 Apr → | ||
| 13–8 | 0.08 | 21% | 31 Mar → | ||
| 11–13 | -0.04 | 20% | 29 Mar → | ||
| cache_b | 9–13 | -0.01 | 8% | 28 Mar → | |
| 13–5 | -0.01 | 11% | 28 Mar → | ||
| 13–11 | 0.04 | 18% | 28 Mar → | ||
| 13–10 | 0.04 | 22% | 28 Mar → | ||
| 11–13 | 0.00 | 16% | 27 Mar → | ||
| 6–13 | -0.03 | 33% | 27 Mar → | ||
| 6–13 | 0.04 | 26% | 24 Mar → | ||
| 11–13 | -0.07 | 15% | 16 Mar → | ||
| 13–4 | 0.01 | 21% | 14 Mar → | ||
| 13–8 | 0.03 | 22% | 14 Mar → | ||
| 8–13 | 0.07 | 21% | 13 Mar → | ||
| 16–13 | 0.02 | 23% | 12 Mar → | ||
| 16–19 | -0.04 | 17% | 11 Mar → | ||
| 13–9 | 0.13 | 15% | 8 Mar → | ||
| 13–4 | 0.18 | 27% | 8 Mar → | ||
| 13–10 | 0.07 | 17% | 8 Mar → | ||
| 13–4 | 0.05 | 22% | 6 Mar → | ||
| 13–7 | 0.00 | 31% | 5 Mar → | ||
| 7–13 | -0.02 | 16% | 4 Mar → | ||
| 9–13 | 0.03 | 26% | 28 Feb → | ||
| 13–7 | 0.07 | 18% | 28 Feb → | ||
| 19–16 | 0.01 | 23% | 28 Feb → | ||
| 13–8 | 0.07 | 22% | 28 Feb → | ||
| 13–11 | 0.10 | 28% | 27 Feb → | ||
| 16–13 | 0.04 | 26% | 22 Feb → | ||
| 16–13 | 0.05 | 18% | 22 Feb → | ||
| 9–13 | 0.05 | 26% | 22 Feb → | ||
| 3–13 | -0.06 | 14% | 22 Feb → | ||
| 13–8 | 0.04 | 23% | 22 Feb → | ||
| 13–11 | 0.05 | 21% | 21 Feb → | ||
| 16–14 | 0.06 | 19% | 21 Feb → | ||
| 13–4 | 0.07 | 19% | 21 Feb → | ||
| 13–11 | 0.11 | 20% | 21 Feb → | ||
| 13–8 | 0.04 | 16% | 21 Feb → | ||
| 13–8 | 0.15 | 24% | 21 Feb → | ||
| 9–13 | 0.07 | 15% | 21 Feb → | ||
| 10–13 | -0.08 | 19% | 18 Feb → | ||
| 13–9 | 0.06 | 32% | 17 Feb → | ||
| 5–13 | -0.08 | 19% | 17 Feb → | ||
| 3–13 | -0.05 | 19% | 15 Feb → | ||
| 13–6 | -0.03 | 18% | 15 Feb → | ||
| 2–13 | -0.06 | 33% | 15 Feb → | ||
| 13–5 | 0.03 | 26% | 15 Feb → | ||
| 13–4 | 0.13 | 32% | 15 Feb → | ||
| 10–13 | -0.02 | 21% | 14 Feb → | ||
| 13–7 | -0.03 | 19% | 13 Feb → | ||
| 4–13 | 0.02 | 19% | 8 Feb → | ||
| 6–13 | 0.03 | 19% | 8 Feb → | ||
| 13–9 | 0.07 | 25% | 8 Feb → | ||
| 9–13 | 0.04 | 10% | 7 Feb → | ||
| 13–1 | 0.03 | 14% | 7 Feb → | ||
| 3–13 | -0.01 | 21% | 6 Feb → | ||
| cache_b | 11–13 | 0.04 | 19% | 30 Jan → | |
| 13–6 | 0.08 | 14% | 30 Jan → | ||
| 11–13 | -0.02 | 19% | 29 Jan → | ||
| 11–13 | -0.02 | 16% | 27 Jan → | ||
| 5–13 | 0.01 | 12% | 25 Jan → | ||
| 11–13 | 0.03 | 26% | 23 Jan → | ||
| 13–6 | 0.08 | 13% | 22 Jan → | ||
| 13–7 | 0.05 | 15% | 21 Jan → | ||
| 13–7 | 0.04 | 24% | 21 Jan → | ||
| 12–16 | 0.01 | 25% | 21 Jan → | ||
| 13–8 | 0.04 | 19% | 20 Jan → | ||
| 13–11 | 0.03 | 25% | 20 Jan → | ||
| 11–13 | -0.01 | 15% | 19 Jan → | ||
| 13–4 | -0.03 | 11% | 18 Jan → | ||
| 13–5 | -0.01 | 17% | 17 Jan → | ||
| 5–13 | 0.06 | 17% | 16 Jan → | ||
| 13–8 | 0.01 | 24% | 16 Jan → | ||
| 19–17 | 0.00 | 19% | 16 Jan → | ||
| 8–13 | -0.02 | 13% | 14 Jan → | ||
| 13–11 | 0.07 | 24% | 13 Jan → | ||
| 13–9 | 0.04 | 23% | 12 Jan → | ||
| 7–13 | -0.05 | 23% | 10 Jan → | ||
| 13–11 | -0.01 | 24% | 10 Jan → | ||
| 13–9 | 0.03 | 20% | 10 Jan → |
Match data via Leetify.