gu1s — CS2 Stats
NL76561198098091844[U:1:137826116]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Red band among CSDB-tracked players (n=1,873), 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 |
|---|---|---|
| Headshot rate | 42.9% | 49.9% |
| Shot accuracy | 13.8% | 13.4% |
| Kill/death ratio | 1.33 | 1.12 |
| Match win rate | 45.4% | 48.4% |
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -10pp 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 ropz 92% playstyle similarity
Most alike: opening-duel success, utility contribution.
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
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
Reaction time. 614ms 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 7.2/10 (Strong), 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.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
| S | 26 | 18–8 | 69% | 0.02 | |
| A | 24 | 15–9 | 63% | 0.01 | |
| A | 14 | 8–6 | 57% | 0.01 | |
| B | 12 | 6–6 | 50% | 0.01 | |
| C | 10 | 4–6 | 40% | 0.02 | |
| A | 5 | 3–2 | 60% | -0.01 | |
| — | 3 | 2–1 | 67% | 0.02 | |
| — | 3 | 3–0 | 100% | 0.12 | |
| — | 2 | 1–1 | 50% | 0.05 | |
| office | — | 1 | 0–1 | 0% | 0.06 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (40% over 10). 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 resultsLWWWW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 345 | 50% | 1.08 | 15.0 |
| Anubis | 229 | 53% | 1.17 | 14.9 |
| Dust2 | 185 | 51% | 1.10 | 14.6 |
| Ancient | 184 | 51% | 1.14 | 15.2 |
| Inferno | 114 | 54% | 1.14 | 14.3 |
| Vertigo | 53 | 53% | 1.18 | 15.6 |
| Nuke | 50 | 54% | 1.07 | 14.4 |
| Train | 29 | 52% | 1.21 | 15.3 |
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.
- Grenades & UtilityGrenade Lineups →
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4955 — below the 0.5 mark we flag
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
40% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–10 | 0.04 | 16% | 27 Aug → | ||
| 9–13 | 0.07 | 20% | 26 Aug → | ||
| 13–6 | 0.08 | 17% | 28 Jul → | ||
| 7–13 | -0.04 | 15% | 27 Jul → | ||
| 13–1 | 0.09 | 20% | 21 Jun → | ||
| 9–13 | 0.05 | 21% | 6 Jun → | ||
| 13–5 | 0.06 | 21% | 5 Jun → | ||
| 8–13 | 0.03 | 38% | 5 Jun → | ||
| 16–13 | 0.05 | 19% | 8 May → | ||
| 16–14 | -0.04 | 11% | 8 May → | ||
| 2–13 | -0.02 | 25% | 3 May → | ||
| 13–6 | 0.12 | 21% | 3 May → | ||
| 4–13 | -0.03 | 16% | 22 Apr → | ||
| 4–13 | -0.08 | 19% | 20 Apr → | ||
| 13–4 | 0.01 | 7% | 19 Apr → | ||
| 13–5 | 0.03 | 50% | 19 Apr → | ||
| 13–7 | 0.02 | 18% | 17 Apr → | ||
| 16–14 | -0.01 | 23% | 16 Apr → | ||
| 13–8 | 0.07 | 21% | 15 Apr → | ||
| 13–7 | 0.08 | 17% | 13 Apr → | ||
| 3–13 | -0.06 | 25% | 10 Apr → | ||
| 13–6 | 0.05 | 23% | 10 Apr → | ||
| 13–4 | -0.03 | 28% | 9 Apr → | ||
| 13–5 | 0.05 | 15% | 7 Apr → | ||
| 13–6 | -0.00 | 17% | 31 Mar → | ||
| 13–2 | 0.01 | 14% | 31 Mar → | ||
| 13–0 | 0.06 | 6% | 31 Mar → | ||
| 10–13 | 0.00 | 15% | 30 Mar → | ||
| 10–13 | 0.04 | 24% | 24 Mar → | ||
| office | 5–13 | 0.06 | 13% | 24 Mar → | |
| 14–16 | -0.02 | 14% | 22 Mar → | ||
| 4–9 | 0.17 | 33% | 21 Mar → | ||
| 8–13 | 0.10 | 20% | 20 Mar → | ||
| 11–13 | -0.07 | 13% | 17 Mar → | ||
| 13–10 | 0.01 | 18% | 17 Mar → | ||
| 13–10 | 0.02 | 22% | 16 Mar → | ||
| 13–7 | -0.04 | 8% | 16 Mar → | ||
| 5–13 | -0.02 | 20% | 15 Mar → | ||
| 13–7 | 0.12 | 24% | 15 Mar → | ||
| 13–6 | 0.09 | 26% | 15 Mar → | ||
| 16–13 | 0.05 | 23% | 15 Mar → | ||
| 13–11 | 0.01 | 13% | 15 Mar → | ||
| 11–13 | 0.05 | 18% | 14 Mar → | ||
| 13–11 | -0.06 | 12% | 14 Mar → | ||
| 13–4 | 0.00 | 25% | 14 Mar → | ||
| 12–16 | 0.00 | 22% | 13 Mar → | ||
| 13–4 | 0.05 | 19% | 13 Mar → | ||
| 2–8 | 0.03 | 7% | 12 Mar → | ||
| 8–13 | 0.04 | 16% | 8 Mar → | ||
| 9–13 | -0.03 | 20% | 7 Mar → | ||
| 13–6 | 0.02 | 12% | 7 Mar → | ||
| 6–13 | -0.10 | 26% | 6 Mar → | ||
| 4–13 | -0.03 | 29% | 6 Mar → | ||
| 13–6 | 0.01 | 23% | 5 Mar → | ||
| 0–13 | -0.05 | 21% | 23 Feb → | ||
| 13–10 | 0.02 | 18% | 21 Feb → | ||
| 13–9 | -0.00 | 16% | 15 Feb → | ||
| 13–10 | -0.04 | 11% | 15 Feb → | ||
| 8–13 | 0.01 | 23% | 15 Feb → | ||
| 13–10 | -0.03 | 8% | 13 Feb → | ||
| 16–14 | 0.02 | 16% | 13 Feb → | ||
| 13–8 | -0.02 | 5% | 13 Feb → | ||
| 14–16 | -0.02 | 20% | 12 Feb → | ||
| 13–9 | -0.00 | 15% | 10 Feb → | ||
| 10–13 | -0.06 | 19% | 5 Feb → | ||
| 13–3 | 0.06 | 15% | 2 Feb → | ||
| 15–15 | 0.02 | 16% | 29 Jan → | ||
| 13–8 | 0.01 | 11% | 29 Jan → | ||
| 13–11 | 0.07 | 22% | 29 Jan → | ||
| 13–11 | 0.03 | 22% | 22 Jan → | ||
| 11–13 | 0.03 | 17% | 22 Jan → | ||
| 13–2 | 0.12 | 22% | 22 Jan → | ||
| 13–2 | 0.08 | 9% | 19 Jan → | ||
| 13–10 | 0.07 | 17% | 18 Jan → | ||
| 13–6 | 0.11 | 14% | 17 Jan → | ||
| 11–13 | 0.02 | 14% | 16 Jan → | ||
| 10–13 | -0.01 | 15% | 16 Jan → | ||
| 15–15 | -0.00 | 20% | 15 Jan → | ||
| 16–14 | -0.02 | 13% | 12 Jan → | ||
| 13–6 | 0.16 | 13% | 11 Jan → | ||
| 13–3 | 0.03 | 20% | 11 Jan → | ||
| 16–14 | -0.04 | 8% | 11 Jan → | ||
| 13–10 | 0.02 | 16% | 11 Jan → | ||
| 10–13 | 0.01 | 11% | 4 Jan → | ||
| 13–9 | 0.12 | 12% | 26 Dec → | ||
| 8–13 | -0.07 | 14% | 26 Dec → | ||
| 14–16 | 0.04 | 12% | 24 Dec → | ||
| 13–10 | -0.01 | 17% | 23 Dec → | ||
| 10–13 | -0.05 | 18% | 21 Dec → | ||
| 13–4 | -0.03 | 8% | 16 Dec → | ||
| 11–13 | 0.03 | 17% | 14 Dec → | ||
| 11–13 | 0.07 | 15% | 8 Dec → | ||
| 13–8 | 0.04 | 2% | 8 Dec → | ||
| 13–11 | -0.02 | 16% | 28 Nov → | ||
| 13–10 | -0.00 | 23% | 17 Nov → | ||
| 13–11 | 0.02 | 18% | 9 Nov → | ||
| 11–13 | 0.01 | 15% | 11 Oct → | ||
| 13–11 | 0.01 | 12% | 6 Oct → | ||
| 14–16 | -0.03 | 30% | 13 Sept → | ||
| 16–13 | -0.01 | 21% | 8 Sept → |
Match data via Leetify.