Venca Vokurka — CS2 Stats
76561198844943116[U:1:884677388]Steam profile ↗✓ 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 | 44.4% | 52.8% |
| Shot accuracy | 11.8% | 13.7% |
| Kill/death ratio | 0.93 | 1.08 |
| Match win rate | 42.2% | 49.2% |
Share this profile
The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +0pp win rate · +0.02 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
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 b1t 92% playstyle similarity
Most alike: opening-fight frequency, positioning profile.
Where you differ: 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. 567ms 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 5.8/10 (Solid), 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 |
|---|---|---|---|---|---|
| A | 25 | 16–9 | 64% | 0.03 | |
| A | 21 | 12–9 | 57% | 0.02 | |
| D | 16 | 4–12 | 25% | 0.01 | |
| A | 10 | 6–4 | 60% | 0.00 | |
| C | 10 | 4–6 | 40% | 0.02 | |
| D | 8 | 1–7 | 13% | -0.02 | |
| — | 4 | 1–3 | 25% | -0.02 | |
| — | 3 | 0–3 | 0% | 0.04 | |
| — | 2 | 2–0 | 100% | 0.02 | |
| alpine | — | 1 | 0–1 | 0% | -0.03 |
Across the last 100 tracked matches.
Nuke is currently your weakest sufficiently-sampled map (13% over 8). Start with the 6 essential Nuke 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 resultsWLLLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 234 | 53% | 1.21 | 17.3 |
| Inferno | 118 | 52% | 1.31 | 18.4 |
| Ancient | 99 | 57% | 1.22 | 17.9 |
| Dust2 | 94 | 44% | 1.11 | 16.8 |
| Anubis | 55 | 53% | 1.19 | 17.2 |
| Nuke | 46 | 54% | 1.16 | 17.2 |
| Overpass | 15 | 47% | 1.01 | 15.9 |
| Train | 9 | 33% | 1.18 | 20.7 |
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.
Recommended for you
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
13% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–16 | 0.02 | 20% | 16 Aug → | ||
| 6–13 | -0.02 | 18% | 15 Aug → | ||
| 9–13 | 0.09 | 34% | 14 Aug → | ||
| 8–13 | -0.03 | 20% | 11 Aug → | ||
| 8–13 | -0.01 | 17% | 9 Aug → | ||
| 14–16 | -0.03 | 21% | 9 Aug → | ||
| 8–13 | 0.04 | 28% | 8 Aug → | ||
| 13–8 | 0.00 | 23% | 5 Aug → | ||
| 13–0 | 0.05 | 35% | 24 Jul → | ||
| 13–5 | 0.12 | 20% | 23 Jul → | ||
| 11–13 | -0.00 | 14% | 6 Jul → | ||
| 6–13 | -0.01 | 31% | 6 Jul → | ||
| 9–13 | -0.03 | 15% | 6 Jul → | ||
| 15–15 | 0.02 | 20% | 6 Jul → | ||
| 4–9 | 0.01 | 21% | 6 Jul → | ||
| 14–16 | -0.05 | 20% | 5 Jul → | ||
| 12–12 | 0.01 | 33% | 3 Jul → | ||
| 13–4 | 0.13 | 23% | 3 Jul → | ||
| 9–2 | -0.04 | 33% | 3 Jul → | ||
| 13–2 | 0.03 | 27% | 3 Jul → | ||
| 7–9 | -0.02 | 15% | 24 Jun → | ||
| 13–5 | -0.03 | 13% | 22 Jun → | ||
| 10–13 | -0.03 | 18% | 20 Jun → | ||
| 15–15 | -0.08 | 16% | 20 Jun → | ||
| 5–13 | -0.04 | 26% | 13 Jun → | ||
| 6–0 | 0.06 | 7% | 13 Jun → | ||
| 13–7 | 0.04 | 24% | 13 Jun → | ||
| 13–4 | 0.08 | 22% | 13 Jun → | ||
| 13–5 | 0.01 | 27% | 10 Jun → | ||
| 13–16 | 0.03 | 30% | 10 Jun → | ||
| 13–11 | 0.02 | 26% | 7 Jun → | ||
| 13–11 | 0.03 | 23% | 6 Jun → | ||
| 15–15 | 0.07 | 20% | 5 Jun → | ||
| 13–7 | 0.02 | 33% | 31 May → | ||
| 13–1 | 0.02 | 27% | 15 May → | ||
| 13–10 | 0.06 | 21% | 15 May → | ||
| 9–13 | -0.01 | 16% | 2 May → | ||
| 8–13 | 0.07 | 25% | 2 May → | ||
| 8–13 | 0.08 | 18% | 2 May → | ||
| 8–13 | 0.06 | 31% | 2 May → | ||
| 9–7 | 0.03 | 31% | 25 Apr → | ||
| 13–9 | 0.00 | 15% | 25 Apr → | ||
| 8–13 | -0.04 | 21% | 25 Apr → | ||
| 13–5 | 0.09 | 15% | 23 Apr → | ||
| 9–13 | -0.01 | 14% | 22 Apr → | ||
| 13–8 | 0.04 | 22% | 17 Apr → | ||
| 13–9 | 0.02 | 19% | 16 Apr → | ||
| 16–13 | 0.00 | 20% | 14 Apr → | ||
| 13–3 | 0.04 | 17% | 11 Apr → | ||
| 14–16 | 0.03 | 13% | 11 Apr → | ||
| 8–13 | -0.01 | 13% | 6 Apr → | ||
| 8–11 | 0.04 | 11% | 6 Apr → | ||
| 9–13 | -0.00 | 25% | 30 Mar → | ||
| 8–13 | -0.01 | 16% | 22 Mar → | ||
| 5–13 | 0.22 | 22% | 14 Mar → | ||
| 10–13 | 0.03 | 26% | 14 Mar → | ||
| 7–13 | 0.11 | 27% | 14 Mar → | ||
| 13–3 | -0.00 | 30% | 7 Mar → | ||
| 13–7 | 0.05 | 31% | 3 Mar → | ||
| alpine | 12–12 | -0.03 | 11% | 1 Mar → | |
| 7–6 | 0.05 | 14% | 1 Mar → | ||
| 13–7 | 0.05 | 18% | 27 Feb → | ||
| 13–6 | 0.10 | 23% | 21 Feb → | ||
| 13–6 | 0.03 | 16% | 21 Feb → | ||
| 13–10 | -0.00 | 17% | 20 Feb → | ||
| 7–13 | -0.06 | 33% | 18 Feb → | ||
| 13–10 | 0.00 | 7% | 12 Feb → | ||
| 10–13 | 0.00 | 16% | 12 Feb → | ||
| 13–10 | 0.05 | 11% | 11 Feb → | ||
| 2–13 | -0.03 | 24% | 11 Feb → | ||
| 7–13 | 0.03 | 30% | 11 Feb → | ||
| 7–13 | -0.09 | 19% | 11 Feb → | ||
| 5–13 | 0.05 | 41% | 11 Feb → | ||
| 7–13 | -0.08 | 7% | 10 Feb → | ||
| 13–10 | 0.03 | 14% | 10 Feb → | ||
| 9–13 | 0.00 | 16% | 10 Feb → | ||
| 8–6 | -0.03 | 22% | 8 Feb → | ||
| 7–13 | -0.02 | 20% | 7 Feb → | ||
| 17–19 | -0.01 | 9% | 5 Feb → | ||
| 13–9 | -0.01 | 23% | 3 Feb → | ||
| 8–13 | -0.00 | 19% | 2 Feb → | ||
| 2–11 | -0.06 | 31% | 30 Jan → | ||
| 9–13 | 0.13 | 27% | 30 Jan → | ||
| 13–10 | -0.03 | 9% | 28 Jan → | ||
| 1–8 | -0.04 | 20% | 28 Jan → | ||
| 7–13 | -0.08 | 9% | 28 Jan → | ||
| 13–5 | 0.05 | 10% | 28 Jan → | ||
| 13–9 | -0.04 | 19% | 28 Jan → | ||
| 4–13 | 0.01 | 16% | 28 Jan → | ||
| 6–13 | -0.05 | 13% | 28 Jan → | ||
| 3–13 | -0.08 | 13% | 27 Jan → | ||
| 13–11 | -0.04 | 20% | 27 Jan → | ||
| 16–13 | 0.05 | 8% | 27 Jan → | ||
| 13–7 | 0.01 | 15% | 27 Jan → | ||
| 13–5 | 0.06 | 15% | 25 Jan → | ||
| 13–5 | 0.04 | 22% | 25 Jan → | ||
| 13–8 | 0.00 | 8% | 24 Jan → | ||
| 13–8 | 0.03 | 14% | 19 Jan → | ||
| 13–10 | 0.00 | 17% | 18 Jan → | ||
| 13–8 | 0.00 | 11% | 15 Jan → |
Match data via Leetify.