zakuuuuu — CS2 Stats
CA76561199474540898[U:1:1514275170]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Level 4 among CSDB-tracked players (n=2,669), 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 4 median | Level 5 median | vs Level 5 |
|---|---|---|---|---|
| Headshot rate | 46.8% | 42.7% | 43.7% | above |
| Shot accuracy | 4.5% | 10.8% | 11.8% | 7.3% short |
| Kill/death ratio | 1.44 | 1.00 | 1.02 | above |
| Match win rate | 55.1% | 44.1% | 45.0% | above |
This profile matches the typical Level 5 player on 3 of 4 comparable metrics.
Widest gap: Shot accuracy. That is the metric furthest from the Level 5 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +20pp win rate · -0.11 avg rating
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Sharp aimerReliable in 1v1s
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 m0NESY 90% playstyle similarity
Most alike: opening-fight frequency, aim profile.
Where you differ: higher opening-duel success; 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 99 — the mechanical foundation is a clear strength.
CT openings. 81% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
T openings. 69% T opening-duel success — entries that actually open the round.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
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 8.1/10 (Strong), 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 |
|---|---|---|---|---|---|
| B | 29 | 15–14 | 52% | 0.16 | |
| A | 22 | 13–9 | 59% | 0.12 | |
| S | 16 | 12–4 | 75% | 0.16 | |
| S | 12 | 8–4 | 67% | 0.13 | |
| C | 9 | 4–5 | 44% | 0.14 | |
| B | 6 | 3–3 | 50% | 0.15 | |
| — | 2 | 1–1 | 50% | 0.14 | |
| — | 2 | 2–0 | 100% | 0.24 | |
| office | — | 1 | 0–1 | 0% | 0.01 |
| — | 1 | 0–1 | 0% | 0.27 |
Across the last 100 tracked matches.
Ancient is currently your weakest sufficiently-sampled map (44% over 9). 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 resultsLLWLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 4 | 50% | 0.76 | 12.5 |
| Vertigo | 1 | 0% | 0.42 | 5.0 |
| Inferno | 1 | 0% | 0.79 | 15.0 |
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.
44% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–5 | 0.04 | 48% | 29 Aug → | ||
| 5–13 | 0.04 | 52% | 29 Aug → | ||
| 2–9 | -0.11 | 88% | 29 Aug → | ||
| office | 5–13 | 0.01 | 35% | 28 Aug → | |
| 13–6 | 0.10 | 43% | 28 Aug → | ||
| 2–9 | -0.07 | 38% | 28 Aug → | ||
| 3–9 | -0.01 | 54% | 28 Aug → | ||
| 9–3 | 0.27 | 36% | 28 Aug → | ||
| 2–9 | -0.17 | 19% | 28 Aug → | ||
| 13–3 | 0.06 | 35% | 27 Aug → | ||
| 3–13 | 0.09 | 58% | 27 Aug → | ||
| 9–13 | 0.27 | 48% | 4 Apr → | ||
| 13–6 | 0.16 | 55% | 3 Apr → | ||
| 5–13 | 0.07 | 55% | 3 Apr → | ||
| 6–5 | 0.02 | 50% | 3 Apr → | ||
| 2–13 | 0.13 | 50% | 1 Apr → | ||
| 10–13 | 0.17 | 42% | 1 Apr → | ||
| 1–13 | 0.14 | 24% | 31 Mar → | ||
| 8–13 | 0.14 | 51% | 29 Mar → | ||
| 13–7 | 0.07 | 25% | 29 Mar → | ||
| 15–15 | 0.26 | 52% | 28 Mar → | ||
| 13–6 | 0.26 | 39% | 28 Mar → | ||
| 13–5 | 0.22 | 65% | 27 Mar → | ||
| 1–13 | 0.03 | 35% | 24 Mar → | ||
| 12–12 | 0.11 | 45% | 23 Mar → | ||
| 13–7 | 0.26 | 45% | 23 Mar → | ||
| 4–13 | 0.13 | 52% | 23 Mar → | ||
| 7–13 | 0.07 | 56% | 22 Mar → | ||
| 13–9 | 0.26 | 48% | 22 Mar → | ||
| 5–13 | 0.13 | 31% | 22 Mar → | ||
| 13–11 | 0.24 | 43% | 21 Mar → | ||
| 13–7 | 0.20 | 53% | 21 Mar → | ||
| 13–9 | 0.28 | 39% | 21 Mar → | ||
| 13–10 | 0.13 | 55% | 21 Mar → | ||
| 8–13 | 0.14 | 56% | 21 Mar → | ||
| 10–13 | 0.16 | 44% | 20 Mar → | ||
| 13–10 | 0.38 | 46% | 20 Mar → | ||
| 7–13 | 0.20 | 42% | 17 Mar → | ||
| 0–13 | -0.05 | 29% | 17 Mar → | ||
| 13–9 | 0.14 | 25% | 17 Mar → | ||
| 9–13 | 0.15 | 51% | 16 Mar → | ||
| 9–13 | 0.16 | 32% | 16 Mar → | ||
| 12–12 | 0.18 | 50% | 15 Mar → | ||
| 10–13 | 0.18 | 46% | 15 Mar → | ||
| 13–4 | 0.20 | 22% | 14 Mar → | ||
| 13–11 | 0.20 | 33% | 14 Mar → | ||
| 12–12 | 0.18 | 38% | 12 Mar → | ||
| 13–5 | 0.08 | 29% | 12 Mar → | ||
| 13–5 | 0.00 | 35% | 11 Mar → | ||
| 6–13 | 0.15 | 34% | 11 Mar → | ||
| 9–13 | 0.07 | 27% | 10 Mar → | ||
| 12–12 | 0.18 | 21% | 10 Mar → | ||
| 5–2 | 0.16 | 13% | 10 Mar → | ||
| 13–9 | 0.25 | 31% | 10 Mar → | ||
| 13–3 | 0.31 | 31% | 10 Mar → | ||
| 13–5 | 0.29 | 35% | 10 Mar → | ||
| 13–11 | 0.18 | 37% | 8 Mar → | ||
| 13–7 | 0.17 | 26% | 7 Mar → | ||
| 13–8 | 0.18 | 35% | 7 Mar → | ||
| 13–8 | 0.29 | 29% | 6 Mar → | ||
| 13–8 | 0.12 | 34% | 3 Mar → | ||
| 9–0 | 0.12 | 30% | 3 Mar → | ||
| 6–13 | 0.15 | 29% | 3 Mar → | ||
| 13–4 | 0.20 | 40% | 1 Mar → | ||
| 13–11 | 0.13 | 35% | 28 Feb → | ||
| 13–7 | 0.20 | 38% | 28 Feb → | ||
| 13–1 | 0.24 | 35% | 28 Feb → | ||
| 9–6 | 0.17 | 27% | 24 Feb → | ||
| 13–2 | 0.19 | 36% | 24 Feb → | ||
| 9–4 | 0.26 | 46% | 24 Feb → | ||
| 9–5 | 0.26 | 41% | 24 Feb → | ||
| 9–2 | 0.32 | 41% | 24 Feb → | ||
| 9–3 | 0.09 | 28% | 24 Feb → | ||
| 9–7 | 0.23 | 47% | 24 Feb → | ||
| 11–13 | 0.13 | 43% | 23 Feb → | ||
| 13–5 | 0.21 | 30% | 23 Feb → | ||
| 9–6 | 0.22 | 41% | 23 Feb → | ||
| 8–13 | 0.12 | 22% | 21 Feb → | ||
| 6–13 | 0.11 | 23% | 21 Feb → | ||
| 13–5 | 0.10 | 35% | 21 Feb → | ||
| 13–10 | 0.24 | 41% | 21 Feb → | ||
| 5–13 | 0.18 | 30% | 21 Feb → | ||
| 13–10 | 0.16 | 42% | 20 Feb → | ||
| 5–9 | -0.13 | 9% | 24 Jan → | ||
| 1–9 | -0.18 | 5% | 24 Jan → | ||
| 13–4 | 0.12 | 17% | 13 Jan → | ||
| 13–4 | 0.24 | 42% | 12 Jan → | ||
| 13–9 | 0.22 | 33% | 12 Jan → | ||
| 13–8 | 0.15 | 45% | 11 Jan → | ||
| 13–5 | 0.10 | 44% | 10 Jan → | ||
| 15–15 | 0.16 | 38% | 6 Jan → | ||
| 13–10 | 0.17 | 33% | 6 Jan → | ||
| 13–2 | 0.14 | 38% | 6 Jan → | ||
| 13–8 | 0.12 | 33% | 6 Jan → | ||
| 10–13 | 0.14 | 34% | 6 Jan → | ||
| 13–7 | 0.10 | 39% | 5 Jan → | ||
| 13–1 | 0.19 | 28% | 5 Jan → | ||
| 13–1 | 0.13 | 43% | 5 Jan → | ||
| 13–3 | 0.32 | 54% | 5 Jan → | ||
| 7–13 | 0.16 | 34% | 5 Jan → |
Match data via Leetify.