zau — CS2 Stats
76561197979094994[U:1:18829266]Steam profile ↗✓ No bans
What changed since last observed
CSDB last observed this profile on 13 Sep 2026 (4 days ago). Ranks are recorded once per day this page is viewed.
CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 24 days played since 11 Aug 2026. Come back after the next session and the change shows above.
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Rating over time
Premier CS Rating
- 2,400 below peak (29,497)
- +1,018 over 30 days · improving
- Next: Gold band at 30,000 — 2,903 to go
- Reached: Red band · Pink band · Purple band · Blue band
- Red band first seen 2026-09-02
- Pink band first seen 2026-09-02
Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.
How this compares with the same rank
Median values for Red band among CSDB-tracked players (n=12,475), 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 | Red band median | Gold band median | vs Gold band |
|---|---|---|---|---|
| Headshot rate | 39.0% | 49.2% | 50.3% | 11.3% short |
| Shot accuracy | 17.1% | 13.4% | 11.5% | above |
| Kill/death ratio | 1.38 | 1.12 | 1.18 | above |
| Match win rate | 55.9% | 48.5% | 51.9% | above |
This profile matches the typical Gold band player on 3 of 4 comparable metrics.
Widest gap: Headshot rate. That is the metric furthest from the Gold band 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: −10pp win rate · −0.07 avg rating · −4.2pp headshot accuracy · −33ms reaction
Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.
Last 5 · 10 · 20 matches
Last 5
- 4–1 · 80% win rate
- Avg rating 0.10
- Avg headshot accuracy 37%
- Avg reaction 353ms
Last 10
- 4–6 · 40% win rate
- Avg rating 0.02
- Avg headshot accuracy 30%
- Avg reaction 308ms
Last 20
- 9–11 · 45% win rate
- Avg rating 0.05
- Avg headshot accuracy 32%
- Avg reaction 324ms
Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.
Player DNA
Primary style: All-Rounder — No style dimension stands clear of the others in this profile.
Sharp aimerExcellent counter-strafingEffective flashesLimited 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.
What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.
Your pro match
Plays most like b1t 79% playstyle similarity
Most alike: opening-duel success, aim 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 100 — the mechanical foundation is a clear strength.
Areas to improve
Positioning. Positioning trails aim by 52 points — deaths here waste a strong aim profile.
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 6.9/10 (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.
Personal bests
Across the last 100 tracked matches.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
 dust2 | B | 46 | 25–21 | 54% | 0.03 |
 mirage | S | 24 | 18–6 | 75% | 0.06 |
 inferno | S | 17 | 16–1 | 94% | 0.24 |
 anubis | — | 4 | 2–2 | 50% | 0.09 |
| office | — | 3 | 3–0 | 100% | 0.27 |
 cache | — | 3 | 2–1 | 67% | 0.02 |
 train | — | 2 | 2–0 | 100% | 0.11 |
 ancient | — | 1 | 1–0 | 100% | 0.00 |
Across the last 100 tracked matches.
Dust 2 is currently your weakest sufficiently-sampled map (54% over 46). Start with the 6 essential Dust 2 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.
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.
- Grenades & UtilityGrenade Lineups →
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 2.7266 — below the 4 mark we flag
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| dust2 | 13–1 | 0.17 | 34% | 17 Sept → | |
| mirage | 13–11 | 0.01 | 45% | 17 Sept → | |
| anubis | 13–0 | 0.20 | 47% | 16 Sept → | |
| anubis | 13–9 | 0.23 | 42% | 16 Sept → | |
| mirage | 3–13 | -0.12 | 18% | 13 Sept → | |
| anubis | 2–13 | -0.09 | 67% | 12 Sept → | |
| mirage | 1–13 | -0.04 | 0% | 12 Sept → | |
| dust2 | 0–5 | -0.07 | 0% | 12 Sept → | |
| dust2 | 3–10 | -0.09 | 0% | 10 Sept → | |
| mirage | 1–13 | -0.05 | 46% | 9 Sept → | |
| mirage | 13–0 | 0.06 | 26% | 9 Sept → | |
| dust2 | 4–13 | -0.03 | 36% | 9 Sept → | |
| anubis | 8–13 | 0.01 | 51% | 9 Sept → | |
| office | 13–4 | 0.21 | 29% | 8 Sept → | |
| dust2 | 6–13 | -0.03 | 57% | 8 Sept → | |
| mirage | 13–2 | 0.15 | 57% | 7 Sept → | |
| office | 13–4 | 0.38 | 50% | 2 Sept → | |
| office | 13–6 | 0.21 | 34% | 2 Sept → | |
| dust2 | 1–13 | -0.06 | 0% | 1 Sept → | |
| dust2 | 0–2 | -0.01 | 0% | 1 Sept → | |
| mirage | 0–3 | -0.01 | 0% | 1 Sept → | |
| inferno | 9–2 | 0.21 | 15% | 1 Sept → | |
| dust2 | 0–13 | -0.06 | 33% | 1 Sept → | |
| dust2 | 16–12 | -0.08 | 40% | 31 Aug → | |
| dust2 | 2–13 | -0.06 | 50% | 31 Aug → | |
| mirage | 0–2 | -0.06 | 33% | 31 Aug → | |
| mirage | 13–2 | 0.19 | 45% | 30 Aug → | |
| dust2 | 12–12 | -0.02 | 37% | 30 Aug → | |
| dust2 | 10–13 | -0.12 | 21% | 29 Aug → | |
| dust2 | 2–4 | -0.12 | 28% | 29 Aug → | |
| dust2 | 13–9 | 0.11 | 40% | 29 Aug → | |
| dust2 | 3–6 | 0.05 | 40% | 28 Aug → | |
| dust2 | 13–2 | 0.13 | 26% | 28 Aug → | |
| dust2 | 13–4 | 0.16 | 21% | 27 Aug → | |
| dust2 | 10–13 | 0.05 | 24% | 27 Aug → | |
| dust2 | 7–13 | 0.01 | 16% | 27 Aug → | |
| dust2 | 13–6 | 0.11 | 28% | 27 Aug → | |
| dust2 | 13–6 | 0.06 | 31% | 27 Aug → | |
| mirage | 13–4 | 0.19 | 15% | 27 Aug → | |
| dust2 | 11–13 | 0.05 | 26% | 27 Aug → | |
| mirage | 13–5 | 0.02 | 20% | 26 Aug → | |
| inferno | 9–4 | 0.20 | 31% | 26 Aug → | |
| dust2 | 13–11 | 0.12 | 18% | 26 Aug → | |
| mirage | 13–3 | 0.17 | 29% | 26 Aug → | |
| dust2 | 13–1 | 0.02 | 34% | 26 Aug → | |
| mirage | 13–2 | 0.10 | 35% | 26 Aug → | |
| dust2 | 13–3 | 0.19 | 39% | 26 Aug → | |
| mirage | 13–3 | 0.10 | 48% | 26 Aug → | |
| cache | 6–0 | -0.01 | 48% | 26 Aug → | |
| cache | 13–0 | 0.06 | 59% | 26 Aug → | |
| dust2 | 13–4 | 0.09 | 49% | 25 Aug → | |
| dust2 | 13–4 | 0.12 | 17% | 25 Aug → | |
| dust2 | 13–6 | 0.06 | 12% | 25 Aug → | |
| dust2 | 13–3 | 0.06 | 18% | 25 Aug → | |
| dust2 | 13–8 | 0.05 | 27% | 24 Aug → | |
| dust2 | 4–13 | 0.05 | 24% | 24 Aug → | |
| dust2 | 13–4 | 0.06 | 18% | 23 Aug → | |
| mirage | 13–4 | 0.14 | 18% | 23 Aug → | |
| dust2 | 1–13 | -0.12 | 40% | 23 Aug → | |
| inferno | 5–0 | 0.00 | 0% | 21 Aug → | |
| dust2 | 0–3 | 0.00 | 0% | 21 Aug → | |
| dust2 | 13–3 | 0.10 | 28% | 21 Aug → | |
| dust2 | 13–1 | 0.11 | 19% | 21 Aug → | |
| mirage | 5–1 | 0.07 | 12% | 21 Aug → | |
| dust2 | 13–8 | 0.08 | 26% | 21 Aug → | |
| mirage | 13–1 | 0.10 | 30% | 21 Aug → | |
| dust2 | 13–1 | 0.11 | 29% | 20 Aug → | |
| mirage | 13–2 | 0.09 | 45% | 20 Aug → | |
| dust2 | 13–3 | 0.09 | 42% | 20 Aug → | |
| mirage | 13–2 | 0.07 | 33% | 20 Aug → | |
| dust2 | 13–1 | 0.06 | 30% | 20 Aug → | |
| mirage | 13–2 | 0.07 | 35% | 20 Aug → | |
| inferno | 13–3 | 0.00 | 0% | 14 Aug → | |
| inferno | 9–1 | 0.38 | 45% | 14 Aug → | |
| inferno | 9–6 | 0.14 | 38% | 14 Aug → | |
| inferno | 9–1 | 0.38 | 28% | 14 Aug → | |
| inferno | 9–2 | 0.13 | 40% | 14 Aug → | |
| inferno | 9–1 | 0.35 | 34% | 14 Aug → | |
| dust2 | 16–14 | 0.15 | 39% | 14 Aug → | |
| dust2 | 13–8 | 0.15 | 36% | 14 Aug → | |
| cache | 0–2 | 0.00 | 0% | 12 Aug → | |
| mirage | 9–7 | 0.14 | 40% | 12 Aug → | |
| dust2 | 13–8 | 0.06 | 36% | 12 Aug → | |
| mirage | 13–3 | 0.23 | 24% | 12 Aug → | |
| train | 13–2 | 0.06 | 33% | 12 Aug → | |
| train | 13–5 | 0.17 | 27% | 12 Aug → | |
| inferno | 9–1 | 0.38 | 22% | 12 Aug → | |
| inferno | 9–2 | 0.24 | 34% | 12 Aug → | |
| inferno | 9–2 | 0.32 | 19% | 12 Aug → | |
| ancient | 13–4 | 0.00 | 0% | 11 Aug → | |
| dust2 | 0–13 | -0.01 | 0% | 11 Aug → | |
| mirage | 0–13 | -0.03 | 0% | 11 Aug → | |
| mirage | 13–0 | -0.18 | 0% | 11 Aug → | |
| dust2 | 1–8 | -0.08 | 0% | 11 Aug → | |
| dust2 | 0–13 | -0.10 | 0% | 11 Aug → | |
| inferno | 9–1 | 0.46 | 54% | 11 Aug → | |
| inferno | 9–4 | 0.19 | 42% | 11 Aug → | |
| inferno | 5–9 | 0.08 | 20% | 11 Aug → | |
| inferno | 9–1 | 0.32 | 28% | 11 Aug → | |
| inferno | 9–0 | 0.37 | 21% | 11 Aug → |
Match data via Leetify.
