Quasar — CS2 Stats
76561198093422458[U:1:133156730]✓ No bans
How this compares with the same rank
Median values for Blue band among CSDB-tracked players (n=2,468), 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 | Blue band median | Purple band median | vs Purple band |
|---|---|---|---|---|
| Headshot rate | 2.5% | 41.4% | 44.2% | 41.8% short |
| Shot accuracy | 17.8% | 9.0% | 11.6% | above |
| Kill/death ratio | 1.07 | 0.97 | 1.03 | above |
| Match win rate | 53.4% | 43.7% | 45.2% | above |
This profile matches the typical Purple band player on 3 of 4 comparable metrics.
Widest gap: Headshot rate. That is the metric furthest from the Purple 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: -30pp win rate · -0.00 avg rating
Player DNA
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 NiKo 75% playstyle similarity
Most alike: opening-fight frequency, opening-duel success.
Where you differ: lower aim profile; 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
Areas to improve
Reaction time. 662ms 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 4.3/10 (Developing), 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 |
|---|---|---|---|---|---|
| C | 31 | 11–20 | 35% | -0.01 | |
| C | 19 | 7–12 | 37% | -0.03 | |
| B | 15 | 7–8 | 47% | -0.01 | |
| S | 9 | 6–3 | 67% | 0.00 | |
| D | 9 | 2–7 | 22% | -0.02 | |
| C | 9 | 4–5 | 44% | -0.00 | |
| D | 6 | 2–4 | 33% | -0.04 | |
| jura | — | 1 | 0–1 | 0% | -0.10 |
| — | 1 | 1–0 | 100% | -0.04 |
Across the last 100 tracked matches.
Ancient is currently your weakest sufficiently-sampled map (22% 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.
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 MechanicsAim Training →
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 12.4948° — above the 12° mark we flag
- Best CS2 CrosshairAim Training →
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 14.8804% — below the 15% mark we flag
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
22% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–8 | -0.03 | 13% | 4 Dec → | ||
| 8–13 | 0.04 | 11% | 2 Dec → | ||
| 3–13 | -0.04 | 6% | 3 Jul → | ||
| 13–6 | 0.02 | 9% | 2 Jul → | ||
| 13–6 | -0.00 | 20% | 19 Jun → | ||
| 3–13 | -0.09 | 15% | 22 May → | ||
| 13–11 | -0.02 | 20% | 15 May → | ||
| 6–13 | -0.03 | 12% | 9 May → | ||
| jura | 1–13 | -0.10 | 3% | 8 May → | |
| 9–13 | -0.08 | 16% | 23 Apr → | ||
| 13–11 | -0.04 | 12% | 15 Apr → | ||
| 14–16 | -0.01 | 19% | 14 Apr → | ||
| 13–10 | 0.02 | 13% | 10 Apr → | ||
| 4–13 | -0.09 | 23% | 7 Apr → | ||
| 10–13 | -0.07 | 9% | 3 Apr → | ||
| 13–8 | -0.04 | 17% | 2 Apr → | ||
| 13–3 | 0.01 | 13% | 27 Mar → | ||
| 13–10 | -0.08 | 12% | 23 Mar → | ||
| 13–10 | -0.05 | 13% | 20 Mar → | ||
| 13–9 | 0.04 | 12% | 20 Mar → | ||
| 12–12 | 0.00 | 8% | 19 Mar → | ||
| 5–13 | -0.05 | 10% | 13 Mar → | ||
| 9–13 | -0.05 | 14% | 12 Mar → | ||
| 8–13 | -0.08 | 19% | 3 Mar → | ||
| 13–11 | -0.02 | 18% | 22 Feb → | ||
| 12–12 | -0.04 | 13% | 20 Feb → | ||
| 13–9 | 0.02 | 16% | 17 Feb → | ||
| 5–13 | -0.06 | 23% | 12 Feb → | ||
| 5–13 | 0.00 | 32% | 5 Feb → | ||
| 13–9 | -0.02 | 23% | 23 Jan → | ||
| 13–1 | 0.07 | 17% | 11 Jan → | ||
| 5–13 | -0.05 | 10% | 26 Dec → | ||
| 12–12 | -0.05 | 13% | 24 Dec → | ||
| 13–5 | 0.03 | 20% | 24 Dec → | ||
| 13–7 | -0.04 | 12% | 23 Dec → | ||
| 13–4 | -0.01 | 17% | 22 Dec → | ||
| 13–10 | -0.02 | 14% | 21 Dec → | ||
| 13–11 | 0.06 | 14% | 20 Dec → | ||
| 4–13 | -0.05 | 21% | 20 Dec → | ||
| 8–13 | -0.01 | 13% | 20 Dec → | ||
| 13–4 | 0.02 | 15% | 16 Dec → | ||
| 13–4 | 0.01 | 24% | 15 Dec → | ||
| 13–10 | 0.00 | 21% | 11 Dec → | ||
| 8–13 | 0.05 | 14% | 3 Dec → | ||
| 12–12 | -0.01 | 13% | 2 Dec → | ||
| 5–13 | -0.08 | 14% | 24 Nov → | ||
| 8–13 | 0.03 | 11% | 21 Nov → | ||
| 14–16 | -0.05 | 23% | 21 Nov → | ||
| 13–11 | -0.04 | 10% | 18 Nov → | ||
| 10–13 | 0.04 | 15% | 15 Nov → | ||
| 12–12 | 0.03 | 12% | 12 Nov → | ||
| 2–13 | -0.09 | 19% | 11 Nov → | ||
| 1–13 | -0.11 | 17% | 8 Nov → | ||
| 13–9 | 0.01 | 6% | 8 Nov → | ||
| 13–9 | -0.04 | 15% | 7 Nov → | ||
| 9–13 | -0.02 | 16% | 5 Nov → | ||
| 1–5 | -0.11 | 0% | 3 Nov → | ||
| 8–13 | 0.01 | 23% | 30 Oct → | ||
| 12–12 | -0.01 | 13% | 24 Oct → | ||
| 9–13 | 0.07 | 14% | 24 Oct → | ||
| 12–12 | 0.01 | 14% | 24 Oct → | ||
| 5–13 | -0.11 | 10% | 22 Oct → | ||
| 13–16 | -0.01 | 15% | 21 Oct → | ||
| 5–13 | -0.02 | 19% | 18 Oct → | ||
| 13–11 | -0.05 | 13% | 16 Oct → | ||
| 13–7 | 0.02 | 17% | 16 Oct → | ||
| 11–13 | -0.01 | 10% | 14 Oct → | ||
| 2–13 | -0.08 | 6% | 13 Oct → | ||
| 9–13 | 0.01 | 24% | 9 Oct → | ||
| 13–8 | 0.02 | 23% | 7 Oct → | ||
| 4–13 | -0.03 | 17% | 4 Oct → | ||
| 13–16 | -0.00 | 9% | 3 Oct → | ||
| 13–3 | 0.01 | 9% | 2 Oct → | ||
| 6–13 | -0.06 | 14% | 2 Oct → | ||
| 13–3 | 0.02 | 25% | 2 Oct → | ||
| 7–13 | 0.05 | 13% | 1 Oct → | ||
| 9–13 | -0.05 | 1% | 1 Oct → | ||
| 13–9 | 0.04 | 10% | 30 Sept → | ||
| 13–3 | 0.02 | 17% | 27 Sept → | ||
| 10–13 | -0.03 | 7% | 26 Sept → | ||
| 13–10 | 0.03 | 16% | 25 Sept → | ||
| 4–13 | 0.04 | 4% | 24 Sept → | ||
| 13–4 | 0.07 | 19% | 23 Sept → | ||
| 12–12 | -0.07 | 8% | 22 Sept → | ||
| 13–4 | -0.03 | 14% | 21 Sept → | ||
| 6–13 | -0.05 | 12% | 20 Sept → | ||
| 7–13 | -0.02 | 6% | 19 Sept → | ||
| 5–13 | -0.03 | 17% | 18 Sept → | ||
| 11–13 | -0.02 | 10% | 18 Sept → | ||
| 8–13 | -0.05 | 16% | 18 Sept → | ||
| 10–13 | 0.01 | 17% | 17 Sept → | ||
| 13–11 | -0.03 | 23% | 17 Sept → | ||
| 8–13 | -0.06 | 11% | 16 Sept → | ||
| 5–13 | 0.06 | 10% | 16 Sept → | ||
| 11–13 | -0.03 | 21% | 14 Sept → | ||
| 12–12 | 0.01 | 11% | 13 Sept → | ||
| 12–12 | -0.04 | 17% | 12 Sept → | ||
| 13–2 | 0.08 | 26% | 11 Sept → | ||
| 13–6 | 0.01 | 16% | 11 Sept → | ||
| 13–8 | 0.02 | 17% | 10 Sept → |
Match data via Leetify.