Dorkan — CS2 Stats
76561198082624467[U:1:122358739]Steam profile ↗✓ No bans
What changed since last observed
CSDB last observed this profile on 10 Sep 2026 (8 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. 38 days played since 6 Jul 2026. 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
Faceit ELO
- At peak — 2,641
- Next: 3,000 ELO at 3,000 — 359 to go
- Reached: 2,500 ELO · Level 10 · Level 9 · Level 8
- 2,500 ELO first seen 2026-08-30
- Level 10 first seen 2026-08-30
Premier CS Rating
- At peak — 26,737
- Next: Gold band at 30,000 — 3,263 to go
- Reached: Red band · Pink band · Purple band · Blue band
- Red band first seen 2026-09-10
- Pink band first seen 2026-09-10
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: +30pp win rate · −0.00 avg rating · +1.7pp headshot accuracy · +5ms reaction
Win rate up 30pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (−0.00), so results shifted more than performance did.
Last 5 · 10 · 20 matches
Last 5
- 4–1 · 80% win rate
- Avg rating 0.03
- Avg headshot accuracy 14%
- Avg reaction 541ms
Last 10
- 7–3 · 70% win rate
- Avg rating 0.01
- Avg headshot accuracy 19%
- Avg reaction 524ms
Last 20
- 11–9 · 55% win rate
- Avg rating 0.01
- Avg headshot accuracy 18%
- Avg reaction 522ms
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 (+1.3 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 jL 98% 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
Areas to improve
Preaim. Mechanical aim is strong but the crosshair sits 10.1° off target when enemies appear — placement, not flicking, is the bigger win available.
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 6.4/10 (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 |
|---|---|---|---|---|---|
 ancient | S | 21 | 15–6 | 71% | 0.01 |
 inferno | A | 20 | 11–9 | 55% | -0.01 |
 anubis | D | 19 | 5–14 | 26% | -0.02 |
 cache | S | 15 | 12–3 | 80% | -0.00 |
 dust2 | B | 12 | 6–6 | 50% | -0.01 |
 mirage | S | 7 | 6–1 | 86% | 0.02 |
 nuke | D | 6 | 2–4 | 33% | 0.01 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (26% over 19). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWLLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Inferno | 205 | 55% | 1.15 | 16.0 |
| Anubis | 200 | 48% | 1.05 | 16.5 |
| Ancient | 193 | 63% | 1.13 | 16.6 |
| Dust2 | 126 | 49% | 1.04 | 15.4 |
| Mirage | 93 | 45% | 1.16 | 15.6 |
| Nuke | 76 | 43% | 1.08 | 16.1 |
| Cache | 55 | 64% | 1.21 | 16.0 |
| Overpass | 42 | 55% | 1.19 | 16.9 |
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 0.4431 — 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.
26% win rate across 19 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| anubis | 13–4 | 0.03 | 20% | 12 Sept → | |
| dust2 | 13–8 | 0.05 | 14% | 12 Sept → | |
| inferno | 13–3 | 0.12 | 15% | 12 Sept → | |
| anubis | 6–13 | -0.07 | 8% | 12 Sept → | |
| mirage | 13–9 | 0.04 | 13% | 11 Sept → | |
| dust2 | 5–13 | -0.02 | 33% | 11 Sept → | |
| inferno | 13–6 | -0.01 | 10% | 11 Sept → | |
| ancient | 13–8 | 0.01 | 22% | 11 Sept → | |
| cache | 4–13 | -0.05 | 22% | 5 Sept → | |
| cache | 13–9 | -0.02 | 30% | 4 Sept → | |
| ancient | 10–13 | 0.04 | 15% | 3 Sept → | |
| ancient | 8–13 | 0.03 | 11% | 2 Sept → | |
| dust2 | 11–13 | -0.05 | 19% | 2 Sept → | |
| anubis | 2–13 | -0.02 | 16% | 30 Aug → | |
| cache | 9–13 | -0.04 | 23% | 29 Aug → | |
| anubis | 16–19 | -0.02 | 23% | 29 Aug → | |
| ancient | 13–8 | 0.06 | 18% | 23 Aug → | |
| cache | 13–6 | 0.07 | 27% | 23 Aug → | |
| mirage | 13–6 | 0.04 | 13% | 23 Aug → | |
| cache | 13–11 | -0.00 | 6% | 22 Aug → | |
| ancient | 13–11 | -0.02 | 20% | 21 Aug → | |
| cache | 8–13 | 0.00 | 27% | 19 Aug → | |
| inferno | 12–16 | 0.01 | 16% | 16 Aug → | |
| ancient | 10–13 | 0.01 | 19% | 16 Aug → | |
| mirage | 13–9 | 0.01 | 17% | 15 Aug → | |
| anubis | 14–16 | -0.01 | 17% | 14 Aug → | |
| inferno | 16–13 | 0.07 | 27% | 13 Aug → | |
| anubis | 11–13 | 0.01 | 30% | 13 Aug → | |
| nuke | 5–13 | 0.03 | 20% | 10 Aug → | |
| mirage | 6–13 | -0.01 | 22% | 10 Aug → | |
| anubis | 13–9 | 0.07 | 29% | 10 Aug → | |
| ancient | 13–8 | 0.06 | 19% | 10 Aug → | |
| inferno | 7–13 | -0.05 | 10% | 10 Aug → | |
| anubis | 2–13 | -0.09 | 12% | 10 Aug → | |
| anubis | 9–13 | -0.00 | 16% | 7 Aug → | |
| inferno | 13–9 | 0.02 | 15% | 5 Aug → | |
| nuke | 3–13 | -0.04 | 6% | 5 Aug → | |
| ancient | 13–9 | -0.00 | 17% | 4 Aug → | |
| cache | 16–12 | 0.02 | 16% | 3 Aug → | |
| inferno | 13–10 | -0.01 | 21% | 3 Aug → | |
| mirage | 13–10 | 0.02 | 17% | 3 Aug → | |
| dust2 | 13–6 | -0.00 | 16% | 2 Aug → | |
| ancient | 13–11 | -0.05 | 11% | 2 Aug → | |
| inferno | 13–3 | -0.01 | 11% | 1 Aug → | |
| ancient | 13–8 | -0.03 | 26% | 1 Aug → | |
| anubis | 11–13 | -0.02 | 18% | 1 Aug → | |
| anubis | 10–13 | -0.02 | 20% | 1 Aug → | |
| inferno | 5–13 | -0.03 | 24% | 1 Aug → | |
| ancient | 13–10 | -0.03 | 21% | 1 Aug → | |
| nuke | 13–8 | 0.07 | 32% | 1 Aug → | |
| anubis | 7–13 | -0.04 | 19% | 1 Aug → | |
| dust2 | 8–13 | -0.03 | 10% | 1 Aug → | |
| cache | 13–10 | -0.02 | 30% | 31 Jul → | |
| cache | 13–9 | 0.02 | 15% | 28 Jul → | |
| inferno | 7–13 | -0.07 | 14% | 28 Jul → | |
| anubis | 1–13 | -0.09 | 9% | 22 Jul → | |
| anubis | 13–9 | 0.03 | 16% | 20 Jul → | |
| cache | 13–7 | 0.00 | 19% | 20 Jul → | |
| inferno | 1–13 | -0.09 | 17% | 20 Jul → | |
| nuke | 9–13 | -0.01 | 17% | 19 Jul → | |
| dust2 | 13–10 | 0.07 | 22% | 19 Jul → | |
| ancient | 16–13 | -0.01 | 15% | 19 Jul → | |
| inferno | 11–13 | -0.03 | 13% | 19 Jul → | |
| dust2 | 0–13 | -0.10 | 0% | 19 Jul → | |
| anubis | 10–13 | -0.04 | 13% | 18 Jul → | |
| inferno | 13–7 | 0.00 | 35% | 18 Jul → | |
| ancient | 13–8 | 0.10 | 26% | 18 Jul → | |
| anubis | 13–5 | -0.07 | 13% | 18 Jul → | |
| cache | 13–2 | 0.02 | 13% | 18 Jul → | |
| dust2 | 11–13 | -0.03 | 19% | 14 Jul → | |
| inferno | 3–13 | -0.06 | 25% | 14 Jul → | |
| anubis | 5–13 | -0.06 | 24% | 13 Jul → | |
| ancient | 13–9 | 0.01 | 16% | 13 Jul → | |
| dust2 | 13–6 | 0.00 | 7% | 13 Jul → | |
| nuke | 5–13 | -0.06 | 22% | 13 Jul → | |
| cache | 13–3 | 0.00 | 14% | 13 Jul → | |
| dust2 | 13–4 | -0.01 | 19% | 13 Jul → | |
| dust2 | 7–13 | -0.04 | 12% | 12 Jul → | |
| ancient | 9–13 | -0.01 | 17% | 12 Jul → | |
| inferno | 10–13 | -0.04 | 11% | 12 Jul → | |
| anubis | 11–13 | 0.10 | 18% | 12 Jul → | |
| inferno | 16–12 | -0.04 | 10% | 11 Jul → | |
| mirage | 13–8 | -0.00 | 18% | 11 Jul → | |
| inferno | 7–13 | -0.00 | 18% | 11 Jul → | |
| ancient | 3–13 | -0.01 | 24% | 11 Jul → | |
| inferno | 13–8 | -0.03 | 25% | 10 Jul → | |
| cache | 13–9 | -0.03 | 19% | 10 Jul → | |
| ancient | 13–5 | 0.10 | 17% | 10 Jul → | |
| cache | 13–6 | 0.01 | 23% | 9 Jul → | |
| ancient | 13–6 | 0.03 | 13% | 9 Jul → | |
| anubis | 13–4 | 0.03 | 16% | 9 Jul → | |
| inferno | 13–7 | 0.00 | 11% | 8 Jul → | |
| ancient | 19–15 | -0.06 | 11% | 8 Jul → | |
| mirage | 13–7 | 0.06 | 8% | 7 Jul → | |
| ancient | 8–0 | 0.09 | 19% | 7 Jul → | |
| inferno | 13–11 | 0.08 | 22% | 7 Jul → | |
| dust2 | 13–6 | 0.09 | 17% | 7 Jul → | |
| nuke | 13–9 | 0.04 | 23% | 7 Jul → | |
| cache | 13–7 | 0.02 | 20% | 7 Jul → | |
| ancient | 5–13 | -0.05 | 10% | 6 Jul → |
Match data via Leetify.
