nyugodjék — CS2 Stats
76561199094762648[U:1:1134496920]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Pink band among CSDB-tracked players (n=9,423), 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 | Pink band median | Red band median | vs Red band |
|---|---|---|---|---|
| Headshot rate | 58.9% | 47.1% | 49.8% | above |
| Shot accuracy | 4.1% | 12.8% | 13.4% | 9.4% short |
| Kill/death ratio | 1.46 | 1.08 | 1.12 | above |
| Match win rate | 51.7% | 46.7% | 48.6% | above |
This profile matches the typical Red band player on 3 of 4 comparable metrics.
Widest gap: Shot accuracy. That is the metric furthest from the Red band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.
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: -10pp win rate · -0.00 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: positioning profile, opening-duel success.
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. 616ms 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 6.2/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 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 |
|---|---|---|---|---|---|
| C | 35 | 14–21 | 40% | -0.00 | |
| C | 27 | 10–17 | 37% | 0.00 | |
| S | 10 | 7–3 | 70% | -0.00 | |
| B | 8 | 4–4 | 50% | 0.01 | |
| A | 8 | 5–3 | 63% | 0.01 | |
| S | 6 | 4–2 | 67% | 0.01 | |
| — | 4 | 3–1 | 75% | 0.02 | |
| — | 2 | 0–2 | 0% | -0.02 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (37% over 27). Start with the 6 essential Inferno 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 resultsWLWLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 146 | 53% | 1.13 | 16.7 |
| Inferno | 74 | 50% | 1.21 | 17.8 |
| Dust2 | 54 | 57% | 1.11 | 16.2 |
| Ancient | 53 | 45% | 1.00 | 14.4 |
| Anubis | 49 | 53% | 1.13 | 16.0 |
| Nuke | 17 | 47% | 0.95 | 15.1 |
| Overpass | 16 | 38% | 0.96 | 18.1 |
| Vertigo | 12 | 50% | 0.94 | 14.5 |
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 36.0237% — 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.
37% win rate across 27 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 14–16 | -0.01 | 28% | 28 Aug → | ||
| 13–10 | 0.00 | 39% | 28 Aug → | ||
| 16–14 | 0.03 | 38% | 28 Aug → | ||
| 11–13 | -0.07 | 11% | 28 Aug → | ||
| 13–9 | 0.05 | 44% | 28 Aug → | ||
| 11–13 | -0.02 | 28% | 7 Jul → | ||
| 8–13 | -0.03 | 33% | 7 Jul → | ||
| 12–16 | -0.00 | 28% | 6 Jul → | ||
| 8–13 | -0.04 | 24% | 6 Jul → | ||
| 13–8 | -0.01 | 29% | 6 Jul → | ||
| 3–13 | -0.01 | 21% | 5 Jul → | ||
| 10–13 | -0.02 | 36% | 23 Jun → | ||
| 13–2 | -0.02 | 35% | 21 Jun → | ||
| 1–9 | -0.11 | 11% | 7 Jun → | ||
| 13–6 | 0.05 | 25% | 7 Jun → | ||
| 13–4 | 0.04 | 31% | 7 Jun → | ||
| 11–13 | 0.03 | 32% | 7 Jun → | ||
| 13–10 | -0.00 | 29% | 7 Jun → | ||
| 13–8 | 0.02 | 20% | 7 Jun → | ||
| 5–13 | -0.05 | 29% | 7 Jun → | ||
| 13–7 | 0.05 | 31% | 6 Jun → | ||
| 19–17 | -0.01 | 17% | 6 Jun → | ||
| 13–7 | -0.02 | 22% | 6 Jun → | ||
| 13–6 | 0.00 | 29% | 6 Jun → | ||
| 6–13 | -0.02 | 27% | 6 Jun → | ||
| 11–13 | -0.04 | 22% | 5 Jun → | ||
| 13–16 | 0.01 | 43% | 5 Jun → | ||
| 13–7 | -0.01 | 22% | 5 Jun → | ||
| 13–11 | 0.02 | 29% | 5 Jun → | ||
| 13–11 | 0.02 | 26% | 5 Jun → | ||
| 13–7 | 0.08 | 43% | 5 Jun → | ||
| 3–13 | -0.00 | 38% | 4 Jun → | ||
| 6–13 | 0.03 | 22% | 4 Jun → | ||
| 13–9 | 0.04 | 34% | 29 May → | ||
| 0–13 | -0.02 | 0% | 28 May → | ||
| 13–6 | 0.04 | 35% | 28 May → | ||
| 13–11 | 0.06 | 24% | 28 May → | ||
| 13–3 | -0.04 | 26% | 28 May → | ||
| 11–13 | 0.01 | 36% | 28 May → | ||
| 13–4 | 0.10 | 31% | 28 May → | ||
| 13–8 | 0.06 | 22% | 28 May → | ||
| 0–13 | -0.04 | 100% | 28 May → | ||
| 13–11 | 0.10 | 24% | 28 May → | ||
| 5–13 | 0.07 | 28% | 27 May → | ||
| 0–10 | -0.01 | 31% | 27 May → | ||
| 8–13 | -0.03 | 31% | 22 May → | ||
| 6–13 | -0.01 | 21% | 21 May → | ||
| 11–13 | -0.07 | 22% | 21 May → | ||
| 10–13 | -0.01 | 19% | 21 May → | ||
| 13–1 | 0.00 | 20% | 20 May → | ||
| 2–0 | 0.00 | 0% | 20 May → | ||
| 13–0 | 0.01 | 56% | 20 May → | ||
| 13–10 | -0.00 | 28% | 19 May → | ||
| 13–6 | 0.01 | 25% | 19 May → | ||
| 13–8 | -0.01 | 16% | 19 May → | ||
| 13–8 | -0.04 | 28% | 10 May → | ||
| 8–13 | -0.06 | 24% | 10 May → | ||
| 13–4 | 0.01 | 29% | 10 May → | ||
| 13–10 | 0.04 | 43% | 10 May → | ||
| 10–13 | -0.06 | 25% | 9 May → | ||
| 17–19 | -0.02 | 20% | 9 May → | ||
| 4–13 | -0.08 | 21% | 9 May → | ||
| 9–13 | -0.03 | 19% | 9 May → | ||
| 8–13 | 0.04 | 18% | 9 May → | ||
| 14–16 | -0.01 | 20% | 8 May → | ||
| 20–22 | 0.00 | 22% | 8 May → | ||
| 8–13 | -0.02 | 21% | 8 May → | ||
| 11–13 | 0.02 | 22% | 8 May → | ||
| 4–13 | 0.03 | 37% | 8 May → | ||
| 5–13 | 0.03 | 36% | 11 Apr → | ||
| 11–13 | -0.05 | 38% | 11 Apr → | ||
| 13–10 | 0.03 | 35% | 11 Apr → | ||
| 13–10 | -0.01 | 42% | 11 Apr → | ||
| 2–13 | 0.02 | 25% | 10 Apr → | ||
| 16–13 | -0.05 | 21% | 9 Apr → | ||
| 12–12 | 0.00 | 16% | 9 Apr → | ||
| 13–6 | 0.00 | 22% | 3 Apr → | ||
| 13–7 | 0.01 | 27% | 2 Apr → | ||
| 9–13 | -0.06 | 31% | 2 Apr → | ||
| 13–6 | 0.11 | 32% | 21 Mar → | ||
| 19–16 | 0.08 | 27% | 14 Mar → | ||
| 10–13 | -0.03 | 14% | 14 Mar → | ||
| 9–13 | -0.03 | 22% | 1 Mar → | ||
| 7–13 | -0.05 | 26% | 1 Mar → | ||
| 2–13 | -0.04 | 24% | 1 Mar → | ||
| 7–13 | -0.03 | 35% | 28 Feb → | ||
| 13–9 | 0.03 | 18% | 28 Feb → | ||
| 12–12 | -0.06 | 17% | 28 Feb → | ||
| 13–2 | -0.03 | 45% | 28 Feb → | ||
| 13–2 | 0.00 | 20% | 28 Feb → | ||
| 6–13 | 0.02 | 29% | 22 Feb → | ||
| 7–13 | -0.08 | 38% | 22 Feb → | ||
| 8–13 | -0.05 | 40% | 22 Feb → | ||
| 13–10 | 0.12 | 32% | 21 Feb → | ||
| 13–9 | 0.04 | 41% | 21 Feb → | ||
| 4–13 | -0.04 | 33% | 21 Feb → | ||
| 13–11 | 0.09 | 31% | 21 Feb → | ||
| 13–4 | 0.16 | 29% | 21 Feb → | ||
| 6–13 | -0.02 | 26% | 4 Feb → | ||
| 7–13 | -0.03 | 27% | 4 Feb → |
Match data via Leetify.