Qweall — CS2 Stats
ZW76561199075616105[U:1:1115350377]Steam profile ↗✓ No bans
What changed since last observed
CSDB last observed this profile on 30 Aug 2026 (39 days ago). Ranks are recorded once per day this page is viewed.
Rating over time
Faceit ELO
- At peak — 3,026
- Next: 3,500 ELO at 3,500 — 474 to go
- Reached: 3,000 ELO · 2,500 ELO · Level 10 · Level 9
- 3,000 ELO first seen 2026-08-30
- 2,500 ELO first seen 2026-08-30
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.
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: −40pp win rate · −0.04 avg rating · −7.2pp headshot accuracy · +61ms reaction
Win rate down 40pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).
Last 5 · 10 · 20 matches
Last 5
- 2–3 · 40% win rate
- Avg rating -0.06
- Avg headshot accuracy 17%
- Avg reaction 555ms
Last 10
- 2–8 · 20% win rate
- Avg rating -0.05
- Avg headshot accuracy 14%
- Avg reaction 597ms
Last 20
- 8–12 · 40% win rate
- Avg rating -0.03
- Avg headshot accuracy 18%
- Avg reaction 566ms
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: Support — Utility contribution stands above the rest of this profile (+1.1 against its own average).
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 device 96% playstyle similarity
Most alike: opening-duel success, utility contribution.
Where you differ: lower aim profile; lower positioning 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
Positioning. Positioning trails aim by 31 points — deaths here waste a strong aim profile.
T-side openings. Opening success drops from 48% on CT to 33% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 563ms 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 6.1/10 (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 | C | 19 | 7–12 | 37% | 0.02 |
 mirage | A | 18 | 10–8 | 56% | -0.00 |
 nuke | B | 17 | 8–9 | 47% | -0.00 |
 inferno | S | 17 | 12–5 | 71% | 0.10 |
 ancient | A | 10 | 6–4 | 60% | 0.03 |
 anubis | — | 4 | 1–3 | 25% | 0.02 |
| palais | — | 4 | 4–0 | 100% | 0.10 |
 vertigo | — | 4 | 2–2 | 50% | 0.08 |
 train | — | 3 | 1–2 | 33% | 0.04 |
 overpass | — | 1 | 1–0 | 100% | 0.04 |
| agency | — | 1 | 1–0 | 100% | -0.01 |
| brewery | — | 1 | 0–1 | 0% | -0.01 |
| memento | — | 1 | 0–1 | 0% | 0.01 |
Across the last 100 tracked matches.
Dust 2 is currently your weakest sufficiently-sampled map (37% over 19). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsLWLLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 568 | 50% | 1.00 | 15.9 |
| Ancient | 318 | 57% | 1.06 | 16.2 |
| Dust2 | 298 | 57% | 1.09 | 17.0 |
| Anubis | 280 | 52% | 1.04 | 16.3 |
| Nuke | 143 | 55% | 1.07 | 16.2 |
| Vertigo | 56 | 50% | 1.03 | 15.4 |
| Train | 50 | 66% | 1.15 | 17.6 |
| Overpass | 22 | 59% | 1.00 | 15.6 |
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 32.9298% — 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 19 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| mirage | 13–10 | -0.01 | 17% | 16 May → | |
| nuke | 2–13 | -0.14 | 17% | 16 May → | |
| dust2 | 5–13 | 0.00 | 17% | 16 May → | |
| nuke | 2–13 | -0.14 | 17% | 16 May → | |
| mirage | 13–10 | -0.01 | 17% | 16 May → | |
| dust2 | 5–13 | 0.00 | 17% | 16 May → | |
| nuke | 8–13 | -0.05 | 13% | 16 May → | |
| dust2 | 6–13 | -0.05 | 8% | 16 May → | |
| dust2 | 6–13 | -0.05 | 8% | 16 May → | |
| nuke | 8–13 | -0.05 | 13% | 16 May → | |
| nuke | 13–7 | -0.01 | 30% | 15 May → | |
| nuke | 6–13 | 0.07 | 24% | 15 May → | |
| mirage | 13–8 | 0.00 | 15% | 15 May → | |
| dust2 | 9–13 | 0.02 | 14% | 15 May → | |
| dust2 | 6–13 | -0.06 | 26% | 15 May → | |
| mirage | 7–13 | -0.04 | 19% | 23 Mar → | |
| nuke | 13–1 | -0.02 | 20% | 23 Mar → | |
| mirage | 13–7 | -0.01 | 25% | 19 Mar → | |
| dust2 | 13–11 | 0.01 | 24% | 31 Jan → | |
| mirage | 13–5 | -0.02 | 17% | 31 Jan → | |
| mirage | 10–13 | -0.00 | 22% | 31 Jan → | |
| nuke | 3–13 | -0.03 | 15% | 29 Jan → | |
| train | 11–13 | 0.01 | 20% | 28 Oct → | |
| nuke | 8–13 | 0.01 | 24% | 21 Oct → | |
| ancient | 13–10 | -0.06 | 29% | 20 Oct → | |
| mirage | 11–13 | -0.03 | 22% | 19 Sept → | |
| inferno | 8–8 | 0.04 | 25% | 17 Sept → | |
| dust2 | 6–13 | 0.03 | 17% | 8 Sept → | |
| mirage | 4–13 | -0.06 | 5% | 7 Sept → | |
| inferno | 9–6 | 0.10 | 22% | 7 Sept → | |
| dust2 | 6–13 | 0.01 | 23% | 7 Sept → | |
| inferno | 8–13 | 0.08 | 22% | 6 Sept → | |
| mirage | 8–13 | -0.02 | 33% | 6 Sept → | |
| overpass | 13–6 | 0.04 | 17% | 3 Sept → | |
| ancient | 12–16 | -0.02 | 28% | 31 Aug → | |
| ancient | 10–13 | 0.02 | 11% | 30 Aug → | |
| ancient | 13–11 | -0.04 | 35% | 30 Aug → | |
| nuke | 13–9 | 0.04 | 30% | 29 Aug → | |
| ancient | 13–4 | 0.19 | 31% | 29 Aug → | |
| mirage | 13–7 | 0.07 | 38% | 29 Aug → | |
| nuke | 13–6 | 0.03 | 18% | 27 Jul → | |
| agency | 13–10 | -0.01 | 34% | 21 Jul → | |
| mirage | 5–13 | -0.06 | 13% | 21 Jul → | |
| mirage | 13–9 | 0.02 | 18% | 1 Jul → | |
| brewery | 4–9 | -0.01 | 13% | 9 Jun → | |
| dust2 | 13–9 | 0.02 | 32% | 29 May → | |
| mirage | 7–13 | 0.03 | 26% | 25 May → | |
| nuke | 9–13 | -0.04 | 2% | 25 May → | |
| dust2 | 13–9 | 0.05 | 32% | 25 May → | |
| dust2 | 13–9 | 0.11 | 27% | 25 May → | |
| train | 13–9 | 0.09 | 30% | 25 May → | |
| ancient | 13–6 | 0.10 | 16% | 25 May → | |
| inferno | 13–6 | -0.02 | 26% | 25 May → | |
| dust2 | 11–13 | 0.10 | 19% | 25 May → | |
| anubis | 13–16 | 0.01 | 21% | 21 May → | |
| ancient | 11–13 | -0.02 | 16% | 20 May → | |
| ancient | 16–13 | 0.04 | 23% | 15 May → | |
| ancient | 13–9 | 0.04 | 19% | 3 May → | |
| inferno | 16–13 | 0.06 | 24% | 4 Apr → | |
| mirage | 13–5 | 0.05 | 18% | 20 Feb → | |
| palais | 9–4 | 0.20 | 21% | 24 Jan → | |
| nuke | 9–4 | 0.23 | 15% | 24 Jan → | |
| palais | 9–7 | 0.11 | 16% | 24 Jan → | |
| inferno | 9–5 | 0.05 | 29% | 24 Jan → | |
| inferno | 9–3 | 0.20 | 16% | 24 Jan → | |
| palais | 9–5 | 0.10 | 34% | 24 Jan → | |
| nuke | 8–8 | 0.12 | 29% | 24 Jan → | |
| inferno | 9–3 | 0.33 | 12% | 24 Jan → | |
| palais | 9–6 | -0.01 | 27% | 24 Jan → | |
| vertigo | 9–13 | -0.05 | 20% | 22 Jan → | |
| mirage | 13–9 | 0.07 | 25% | 21 Jan → | |
| vertigo | 6–13 | -0.06 | 10% | 21 Jan → | |
| mirage | 4–13 | -0.04 | 27% | 21 Jan → | |
| dust2 | 13–9 | 0.05 | 32% | 21 Jan → | |
| dust2 | 11–13 | 0.03 | 13% | 17 Jan → | |
| dust2 | 8–13 | 0.01 | 24% | 17 Jan → | |
| nuke | 13–9 | 0.00 | 25% | 17 Jan → | |
| train | 12–12 | 0.01 | 26% | 14 Jan → | |
| dust2 | 13–8 | 0.05 | 25% | 14 Jan → | |
| dust2 | 5–2 | -0.06 | 40% | 14 Jan → | |
| nuke | 13–7 | -0.03 | 25% | 13 Jan → | |
| anubis | 13–7 | -0.00 | 27% | 13 Jan → | |
| vertigo | 9–4 | 0.16 | 3% | 12 Jan → | |
| inferno | 9–4 | 0.07 | 7% | 12 Jan → | |
| anubis | 11–13 | 0.09 | 22% | 12 Jan → | |
| mirage | 13–11 | -0.03 | 33% | 12 Jan → | |
| ancient | 5–13 | 0.02 | 20% | 12 Jan → | |
| anubis | 4–13 | -0.02 | 36% | 19 Nov → | |
| dust2 | 9–13 | 0.05 | 31% | 19 Nov → | |
| inferno | 8–8 | -0.02 | 25% | 6 Nov → | |
| inferno | 9–0 | 0.34 | 18% | 6 Nov → | |
| inferno | 8–8 | 0.13 | 37% | 6 Nov → | |
| inferno | 6–9 | -0.05 | 15% | 5 Nov → | |
| inferno | 9–3 | 0.13 | 24% | 5 Nov → | |
| inferno | 9–1 | 0.01 | 9% | 5 Nov → | |
| memento | 6–9 | 0.01 | 15% | 5 Nov → | |
| vertigo | 9–1 | 0.27 | 37% | 5 Nov → | |
| nuke | 9–7 | -0.00 | 14% | 5 Nov → | |
| inferno | 9–2 | 0.11 | 33% | 5 Nov → | |
| inferno | 9–4 | 0.19 | 16% | 5 Nov → |
Match data via Leetify.
Recent teammates
Milestones
This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.