Darkas — CS2 Stats
76561199062383874[U:1:1102118146]
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -10pp win rate · -0.02 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
Sharp aimer
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 Twistzz 92% playstyle similarity
Most alike: opening-duel success, positioning profile.
Where you differ: 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
Strengths
Aim. Aim score of 85 — the mechanical foundation is a clear strength.
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. 578ms 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 7.3/10 (Strong), 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 |
|---|---|---|---|---|---|
| S | 38 | 30–8 | 79% | 0.01 | |
| S | 29 | 21–8 | 72% | 0.01 | |
| A | 12 | 7–5 | 58% | -0.03 | |
| S | 10 | 7–3 | 70% | 0.01 | |
| — | 3 | 2–1 | 67% | 0.03 | |
| — | 3 | 1–2 | 33% | -0.04 | |
| — | 2 | 1–1 | 50% | -0.00 | |
| debris | — | 1 | 0–1 | 0% | -0.03 |
| boulder | — | 1 | 0–1 | 0% | -0.09 |
| — | 1 | 0–1 | 0% | -0.03 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (58% over 12). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWLWLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 1281 | 49% | 1.08 | 15.9 |
| Ancient | 1270 | 54% | 1.14 | 16.3 |
| Anubis | 970 | 57% | 1.15 | 16.2 |
| Vertigo | 310 | 59% | 1.18 | 16.8 |
| Nuke | 296 | 51% | 1.05 | 15.2 |
| Inferno | 173 | 45% | 1.15 | 16.7 |
| Dust2 | 125 | 36% | 0.90 | 13.6 |
| Train | 120 | 54% | 1.09 | 16.2 |
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.
- 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 34.5172% — below the 40% mark we flag
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 1–13 | -0.06 | 19% | 25 Aug → | ||
| 13–9 | 0.04 | 30% | 27 Jul → | ||
| debris | 8–8 | -0.03 | 15% | 22 Jul → | |
| 13–3 | 0.14 | 31% | 22 Jul → | ||
| boulder | 0–13 | -0.09 | 0% | 14 Jul → | |
| 8–13 | -0.06 | 32% | 14 Jul → | ||
| 13–7 | 0.03 | 16% | 2 Jun → | ||
| 13–10 | -0.10 | 42% | 21 May → | ||
| 13–6 | 0.07 | 24% | 21 May → | ||
| 9–5 | 0.05 | 12% | 20 May → | ||
| 13–0 | 0.00 | 0% | 20 May → | ||
| 13–8 | -0.00 | 17% | 20 May → | ||
| 13–3 | 0.04 | 22% | 11 May → | ||
| 13–6 | 0.01 | 14% | 11 May → | ||
| 9–13 | 0.14 | 32% | 5 May → | ||
| 16–19 | 0.01 | 19% | 4 May → | ||
| 17–19 | 0.00 | 31% | 3 May → | ||
| 13–7 | -0.00 | 18% | 2 May → | ||
| 13–8 | -0.01 | 29% | 2 May → | ||
| 13–9 | -0.02 | 22% | 2 May → | ||
| 13–8 | 0.02 | 43% | 1 May → | ||
| 13–10 | -0.03 | 14% | 30 Apr → | ||
| 13–10 | -0.08 | 31% | 30 Apr → | ||
| 22–18 | 0.02 | 31% | 30 Apr → | ||
| 13–4 | 0.01 | 20% | 30 Apr → | ||
| 13–8 | 0.11 | 27% | 29 Apr → | ||
| 13–10 | 0.05 | 31% | 29 Apr → | ||
| 13–8 | 0.00 | 13% | 29 Apr → | ||
| 7–13 | -0.05 | 27% | 29 Apr → | ||
| 13–9 | -0.02 | 37% | 27 Apr → | ||
| 13–10 | -0.05 | 14% | 27 Apr → | ||
| 13–6 | -0.03 | 9% | 24 Apr → | ||
| 13–7 | -0.02 | 15% | 24 Apr → | ||
| 12–16 | -0.01 | 20% | 24 Apr → | ||
| 13–7 | -0.02 | 21% | 24 Apr → | ||
| 13–4 | 0.02 | 30% | 24 Apr → | ||
| 13–6 | 0.02 | 31% | 23 Apr → | ||
| 13–7 | 0.00 | 28% | 23 Apr → | ||
| 1–13 | 0.03 | 13% | 23 Apr → | ||
| 13–8 | -0.02 | 18% | 22 Apr → | ||
| 22–25 | -0.01 | 22% | 22 Apr → | ||
| 13–10 | -0.02 | 29% | 22 Apr → | ||
| 13–9 | -0.06 | 25% | 22 Apr → | ||
| 13–11 | 0.03 | 26% | 21 Apr → | ||
| 13–11 | 0.01 | 20% | 20 Apr → | ||
| 13–6 | 0.04 | 32% | 20 Apr → | ||
| 13–5 | 0.06 | 27% | 20 Apr → | ||
| 13–11 | -0.03 | 15% | 20 Apr → | ||
| 13–5 | 0.01 | 14% | 20 Apr → | ||
| 23–25 | -0.01 | 15% | 20 Apr → | ||
| 11–13 | -0.05 | 17% | 19 Apr → | ||
| 13–9 | -0.03 | 28% | 19 Apr → | ||
| 13–9 | 0.04 | 15% | 19 Apr → | ||
| 16–12 | 0.06 | 34% | 19 Apr → | ||
| 9–13 | -0.04 | 41% | 19 Apr → | ||
| 11–13 | -0.02 | 21% | 19 Apr → | ||
| 13–9 | 0.01 | 40% | 19 Apr → | ||
| 13–4 | 0.01 | 34% | 19 Apr → | ||
| 13–16 | -0.02 | 24% | 19 Apr → | ||
| 8–13 | -0.05 | 14% | 18 Apr → | ||
| 13–8 | 0.00 | 40% | 18 Apr → | ||
| 13–11 | 0.01 | 26% | 18 Apr → | ||
| 13–2 | -0.02 | 27% | 18 Apr → | ||
| 13–8 | -0.03 | 15% | 18 Apr → | ||
| 13–3 | 0.10 | 35% | 18 Apr → | ||
| 13–4 | -0.01 | 30% | 18 Apr → | ||
| 9–13 | 0.01 | 23% | 18 Apr → | ||
| 13–5 | 0.02 | 23% | 18 Apr → | ||
| 13–4 | 0.03 | 22% | 16 Apr → | ||
| 9–13 | -0.00 | 25% | 15 Apr → | ||
| 13–9 | 0.04 | 21% | 14 Apr → | ||
| 8–13 | -0.03 | 19% | 14 Apr → | ||
| 10–13 | -0.04 | 23% | 14 Apr → | ||
| 13–5 | 0.00 | 13% | 13 Apr → | ||
| 13–6 | 0.09 | 22% | 13 Apr → | ||
| 11–13 | 0.05 | 21% | 12 Apr → | ||
| 13–6 | 0.11 | 27% | 10 Apr → | ||
| 13–9 | 0.04 | 27% | 8 Apr → | ||
| 6–9 | -0.08 | 37% | 5 Apr → | ||
| 19–16 | -0.02 | 21% | 5 Apr → | ||
| 13–10 | -0.02 | 18% | 5 Apr → | ||
| 5–13 | -0.05 | 23% | 5 Apr → | ||
| 13–5 | 0.05 | 13% | 2 Apr → | ||
| 9–13 | -0.04 | 26% | 2 Apr → | ||
| 10–13 | 0.01 | 19% | 1 Apr → | ||
| 13–10 | -0.04 | 16% | 31 Mar → | ||
| 13–16 | 0.02 | 16% | 31 Mar → | ||
| 16–14 | 0.05 | 31% | 30 Mar → | ||
| 12–16 | -0.03 | 25% | 30 Mar → | ||
| 12–16 | -0.04 | 12% | 30 Mar → | ||
| 13–8 | -0.00 | 23% | 30 Mar → | ||
| 13–10 | 0.06 | 20% | 29 Mar → | ||
| 13–8 | -0.01 | 29% | 29 Mar → | ||
| 16–14 | -0.04 | 20% | 29 Mar → | ||
| 13–5 | 0.01 | 14% | 29 Mar → | ||
| 13–11 | -0.03 | 20% | 28 Mar → | ||
| 13–11 | -0.00 | 25% | 28 Mar → | ||
| 13–9 | 0.04 | 28% | 28 Mar → | ||
| 10–13 | 0.06 | 26% | 28 Mar → | ||
| 7–13 | -0.04 | 18% | 27 Mar → |
Match data via Leetify.
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