skullz — CS2 Stats
PRO“sku11z”Imperial EsportsBrazilRiflerSettings & gear profile →
BR76561198118646644[U:1:158380916]Steam profile ↗✓ No bans
What changed since last observed
CSDB last observed this profile on 18 Sep 2026 (4 days ago). Ranks are recorded once per day this page is viewed.
No change since then — still 1,314 tracked matches. Play, then come back: the next observation lands here.
CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 42 days played since 9 Nov 2025. Come back after the next session and the change shows above.
Is this you? Sign in with Steam to claim it and connect match tracking →
Rating over time
Premier is CSDB’s own observation — it builds from the day a profile is first 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: −10pp win rate · +0.00 avg rating · −1.5pp headshot accuracy · −82ms 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
- 3–2 · 60% win rate
- Avg rating 0.07
- Avg headshot accuracy 34%
- Avg reaction 541ms
Last 10
- 6–3–1 · 60% win rate
- Avg rating 0.08
- Avg headshot accuracy 33%
- Avg reaction 520ms
Last 20
- 13–6–1 · 65% win rate
- Avg rating 0.08
- Avg headshot accuracy 34%
- Avg reaction 561ms
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: Positional Player — Positioning stands above the rest of this profile (+2.1 against its own average).
Sharp aimerStrong CT-side openerStrong positioning
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 donk 97% playstyle similarity
Most alike: positioning profile, 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
Strengths
Aim. Aim score of 95 — the mechanical foundation is a clear strength.
CT openings. 70% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
T-side openings. Opening success drops from 70% on CT to 43% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 551ms 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 8.3/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.00 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 |
|---|---|---|---|---|---|
 mirage | A | 25 | 16–9 | 64% | 0.02 |
 dust2 | A | 21 | 12–9 | 57% | 0.04 |
 nuke | B | 17 | 9–8 | 53% | 0.04 |
 inferno | C | 9 | 4–5 | 44% | -0.02 |
 overpass | D | 9 | 3–6 | 33% | -0.02 |
 cache | B | 6 | 3–3 | 50% | 0.07 |
 train | B | 6 | 3–3 | 50% | -0.00 |
 anubis | — | 4 | 4–0 | 100% | 0.06 |
 ancient | — | 2 | 1–1 | 50% | 0.08 |
| boulder | — | 1 | 0–1 | 0% | -0.06 |
Across the last 100 tracked matches.
Overpass is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Overpass lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWLWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 44 | 66% | 1.44 | 17.9 |
| Ancient | 25 | 84% | 1.80 | 17.8 |
| Nuke | 23 | 74% | 1.38 | 16.3 |
| Dust2 | 23 | 74% | 1.76 | 19.1 |
| Anubis | 21 | 62% | 1.48 | 16.0 |
| Inferno | 13 | 77% | 1.37 | 18.9 |
| Overpass | 10 | 50% | 2.31 | 16.1 |
| Train | 5 | 100% | 1.50 | 18.4 |
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.
33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| mirage | 13–9 | 0.06 | 41% | 18 Sept → | |
| dust2 | 5–13 | 0.04 | 38% | 18 Sept → | |
| cache | 13–11 | 0.08 | 38% | 16 Sept → | |
| mirage | 13–9 | 0.11 | 29% | 14 Sept → | |
| nuke | 14–16 | 0.04 | 23% | 13 Sept → | |
| mirage | 15–15 | 0.06 | 40% | 13 Sept → | |
| mirage | 13–3 | 0.05 | 28% | 13 Sept → | |
| dust2 | 13–10 | 0.16 | 33% | 13 Sept → | |
| dust2 | 13–6 | 0.10 | 39% | 1 Sept → | |
| nuke | 9–13 | 0.08 | 21% | 14 Jul → | |
| boulder | 1–13 | -0.06 | 24% | 14 Jul → | |
| cache | 13–7 | 0.01 | 27% | 14 Jul → | |
| dust2 | 16–12 | 0.14 | 37% | 14 Jul → | |
| cache | 13–9 | 0.13 | 38% | 23 Jun → | |
| dust2 | 13–3 | 0.28 | 46% | 23 Jun → | |
| dust2 | 13–7 | 0.03 | 50% | 22 Jun → | |
| mirage | 13–11 | 0.03 | 29% | 22 Jun → | |
| nuke | 11–13 | 0.08 | 36% | 22 Jun → | |
| mirage | 0–13 | -0.03 | 26% | 22 Jun → | |
| ancient | 13–7 | 0.15 | 30% | 22 Jun → | |
| nuke | 13–8 | 0.21 | 38% | 22 Jun → | |
| cache | 10–13 | 0.07 | 46% | 22 Jun → | |
| dust2 | 13–2 | 0.14 | 55% | 20 Jun → | |
| inferno | 13–8 | 0.09 | 26% | 19 Jun → | |
| mirage | 13–9 | 0.04 | 28% | 17 Jun → | |
| ancient | 5–13 | 0.02 | 38% | 17 Jun → | |
| mirage | 13–10 | 0.15 | 38% | 16 Jun → | |
| dust2 | 16–12 | 0.12 | 34% | 16 Jun → | |
| anubis | 13–7 | 0.07 | 30% | 2 Jun → | |
| dust2 | 11–13 | 0.03 | 25% | 4 May → | |
| train | 12–12 | 0.10 | 33% | 4 May → | |
| cache | 11–13 | 0.08 | 28% | 4 May → | |
| cache | 4–13 | 0.03 | 20% | 30 Apr → | |
| mirage | 13–10 | -0.03 | 33% | 21 Feb → | |
| nuke | 3–13 | -0.04 | 19% | 21 Feb → | |
| inferno | 1–13 | -0.10 | 27% | 21 Feb → | |
| anubis | 13–5 | 0.11 | 28% | 19 Feb → | |
| mirage | 13–11 | -0.01 | 17% | 19 Feb → | |
| overpass | 6–13 | -0.02 | 23% | 18 Feb → | |
| dust2 | 11–13 | -0.00 | 20% | 18 Feb → | |
| mirage | 13–6 | 0.08 | 19% | 18 Feb → | |
| dust2 | 13–8 | 0.01 | 33% | 18 Feb → | |
| inferno | 8–13 | -0.07 | 19% | 7 Feb → | |
| nuke | 13–6 | 0.04 | 46% | 7 Feb → | |
| dust2 | 9–13 | -0.04 | 19% | 7 Feb → | |
| mirage | 13–5 | -0.02 | 26% | 6 Feb → | |
| nuke | 13–5 | -0.03 | 12% | 6 Feb → | |
| overpass | 3–13 | -0.06 | 18% | 31 Jan → | |
| nuke | 17–19 | -0.00 | 23% | 31 Jan → | |
| anubis | 16–14 | 0.05 | 20% | 29 Jan → | |
| overpass | 5–13 | -0.03 | 17% | 29 Jan → | |
| dust2 | 10–13 | -0.02 | 9% | 29 Jan → | |
| dust2 | 13–0 | 0.03 | 23% | 29 Jan → | |
| mirage | 13–1 | 0.06 | 19% | 29 Jan → | |
| overpass | 17–19 | -0.02 | 32% | 22 Jan → | |
| nuke | 2–6 | 0.00 | 27% | 22 Jan → | |
| nuke | 11–10 | 0.05 | 30% | 22 Jan → | |
| anubis | 13–9 | 0.00 | 14% | 22 Jan → | |
| overpass | 13–5 | -0.04 | 21% | 22 Jan → | |
| nuke | 7–13 | -0.02 | 29% | 22 Jan → | |
| overpass | 13–10 | 0.02 | 17% | 22 Jan → | |
| mirage | 10–13 | -0.06 | 15% | 22 Jan → | |
| nuke | 10–13 | -0.00 | 18% | 17 Jan → | |
| inferno | 10–13 | 0.01 | 17% | 17 Jan → | |
| nuke | 13–5 | 0.05 | 21% | 16 Jan → | |
| inferno | 13–10 | -0.03 | 24% | 16 Jan → | |
| inferno | 16–13 | -0.02 | 17% | 16 Jan → | |
| mirage | 10–13 | -0.01 | 24% | 16 Jan → | |
| inferno | 13–5 | 0.05 | 23% | 14 Jan → | |
| mirage | 13–9 | 0.01 | 33% | 14 Jan → | |
| mirage | 10–15 | 0.04 | 25% | 10 Jan → | |
| mirage | 13–7 | 0.08 | 38% | 9 Jan → | |
| mirage | 15–17 | 0.06 | 23% | 8 Jan → | |
| nuke | 17–13 | 0.13 | 29% | 5 Jan → | |
| mirage | 13–6 | 0.01 | 22% | 5 Jan → | |
| dust2 | 6–15 | -0.05 | 14% | 5 Jan → | |
| inferno | 8–13 | -0.06 | 29% | 6 Dec → | |
| dust2 | 10–13 | -0.01 | 20% | 6 Dec → | |
| mirage | 1–13 | -0.07 | 18% | 5 Dec → | |
| dust2 | 5–13 | -0.04 | 13% | 4 Dec → | |
| dust2 | 16–14 | 0.01 | 15% | 4 Dec → | |
| mirage | 13–11 | -0.04 | 8% | 1 Dec → | |
| dust2 | 2–13 | -0.07 | 28% | 1 Dec → | |
| train | 13–11 | -0.04 | 14% | 1 Dec → | |
| dust2 | 13–10 | 0.02 | 23% | 30 Nov → | |
| mirage | 10–13 | 0.03 | 23% | 29 Nov → | |
| nuke | 13–5 | 0.02 | 19% | 29 Nov → | |
| nuke | 13–8 | 0.04 | 30% | 27 Nov → | |
| train | 13–5 | 0.01 | 22% | 27 Nov → | |
| mirage | 16–12 | -0.03 | 15% | 26 Nov → | |
| nuke | 13–8 | -0.01 | 18% | 26 Nov → | |
| train | 7–13 | -0.04 | 31% | 25 Nov → | |
| train | 3–13 | -0.05 | 44% | 25 Nov → | |
| inferno | 6–13 | -0.03 | 17% | 24 Nov → | |
| dust2 | 13–11 | 0.04 | 34% | 24 Nov → | |
| overpass | 8–13 | -0.02 | 31% | 19 Nov → | |
| overpass | 8–13 | -0.04 | 25% | 9 Nov → | |
| mirage | 9–13 | -0.02 | 21% | 9 Nov → | |
| train | 13–5 | -0.00 | 18% | 9 Nov → | |
| overpass | 13–5 | 0.06 | 17% | 9 Nov → |
Match data via Leetify.
