abcent0 — CS2 Stats
76561198274513992[U:1:314248264]Steam profile ↗✓ No bans
What changed since last observed
CSDB last observed this profile on 14 Jun 2026 (98 days ago). Ranks are recorded once per day this page is viewed.
No change since then. 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. 59 days played since 14 Oct 2025. Come back after the next session and the change shows above.
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Rating over time
Faceit ELO
- At peak — 3,156
- Next: 3,500 ELO at 3,500 — 344 to go
- Reached: 3,000 ELO · 2,500 ELO · Level 10 · Level 9
Premier CS Rating
- 9,388 below peak (29,999)
- -1,526 over 90 days
- Next: Red band at 25,000 — 4,389 to go
- Reached: Red band · Pink band · Purple band · Blue band
Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +10pp win rate · −0.03 avg rating · −3.4pp headshot accuracy · −124ms 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
- 4–1 · 80% win rate
- Avg rating 0.07
- Avg headshot accuracy 39%
- Avg reaction 523ms
Last 10
- 7–3 · 70% win rate
- Avg rating 0.01
- Avg headshot accuracy 28%
- Avg reaction 498ms
Last 20
- 13–5–2 · 65% win rate
- Avg rating 0.03
- Avg headshot accuracy 30%
- Avg reaction 560ms
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 (+1.6 against its own average).
Sharp aimerExcellent counter-strafingStrong CT-side opener
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 s1mple 90% playstyle similarity
Most alike: utility contribution, 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 94 — the mechanical foundation is a clear strength.
Counter-strafing. 91% of shots taken properly stopped — movement discipline most players never reach.
CT openings. 67% 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 67% on CT to 38% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 613ms 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 8.1/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.02 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 | A | 31 | 17–14 | 55% | 0.01 |
 mirage | A | 28 | 18–10 | 64% | 0.01 |
 cache | B | 12 | 6–6 | 50% | 0.03 |
 nuke | A | 9 | 5–4 | 56% | 0.04 |
 ancient | A | 8 | 5–3 | 63% | 0.01 |
 inferno | — | 3 | 1–2 | 33% | -0.05 |
 train | — | 3 | 3–0 | 100% | 0.09 |
| office | — | 2 | 2–0 | 100% | 0.11 |
 anubis | — | 2 | 0–2 | 0% | -0.04 |
 overpass | — | 1 | 0–1 | 0% | 0.05 |
 vertigo | — | 1 | 1–0 | 100% | 0.19 |
Across the last 100 tracked matches.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWLLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 499 | 54% | 1.17 | 17.4 |
| Anubis | 188 | 52% | 1.14 | 16.3 |
| Ancient | 179 | 56% | 1.17 | 18.5 |
| Dust2 | 151 | 51% | 1.14 | 16.4 |
| Vertigo | 69 | 45% | 1.08 | 16.1 |
| Nuke | 59 | 47% | 1.21 | 17.7 |
| Inferno | 24 | 42% | 1.10 | 16.6 |
| Overpass | 20 | 50% | 1.24 | 17.6 |
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 37.8456% — below the 40% mark we flag
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| nuke | 9–5 | 0.04 | 29% | 9 Sept → | |
| nuke | 9–3 | 0.22 | 42% | 27 Aug → | |
| cache | 13–5 | 0.05 | 35% | 20 Aug → | |
| mirage | 8–13 | 0.00 | 48% | 17 Aug → | |
| dust2 | 13–3 | 0.05 | 39% | 17 Aug → | |
| nuke | 0–3 | -0.19 | 0% | 26 Jun → | |
| mirage | 13–3 | -0.01 | 29% | 18 Jun → | |
| cache | 9–13 | -0.03 | 35% | 15 Jun → | |
| dust2 | 13–9 | -0.07 | 0% | 14 Jun → | |
| mirage | 13–4 | 0.05 | 23% | 13 May → | |
| ancient | 13–9 | -0.01 | 18% | 12 May → | |
| cache | 13–5 | 0.04 | 40% | 11 May → | |
| cache | 13–5 | 0.03 | 22% | 9 May → | |
| cache | 0–2 | -0.02 | 0% | 7 May → | |
| mirage | 13–7 | 0.07 | 29% | 7 May → | |
| mirage | 13–1 | 0.10 | 40% | 7 May → | |
| nuke | 6–13 | 0.07 | 50% | 6 May → | |
| cache | 12–12 | 0.06 | 30% | 6 May → | |
| cache | 12–12 | 0.02 | 47% | 6 May → | |
| cache | 13–7 | 0.05 | 40% | 5 May → | |
| cache | 13–6 | 0.11 | 22% | 5 May → | |
| mirage | 4–13 | 0.02 | 24% | 4 May → | |
| cache | 13–4 | 0.15 | 27% | 1 May → | |
| cache | 10–13 | -0.09 | 25% | 1 May → | |
| cache | 2–13 | -0.01 | 26% | 30 Apr → | |
| office | 13–9 | 0.08 | 13% | 27 Apr → | |
| mirage | 13–11 | -0.03 | 20% | 4 Apr → | |
| mirage | 13–8 | -0.03 | 23% | 15 Mar → | |
| inferno | 0–4 | -0.11 | 0% | 15 Mar → | |
| anubis | 1–6 | -0.05 | 8% | 15 Mar → | |
| dust2 | 16–13 | 0.03 | 20% | 14 Mar → | |
| anubis | 12–12 | -0.03 | 27% | 13 Mar → | |
| dust2 | 3–13 | -0.06 | 50% | 12 Feb → | |
| dust2 | 10–13 | 0.07 | 35% | 10 Feb → | |
| dust2 | 7–13 | -0.01 | 18% | 4 Feb → | |
| dust2 | 6–13 | 0.04 | 44% | 25 Jan → | |
| dust2 | 6–13 | -0.04 | 19% | 18 Jan → | |
| mirage | 13–4 | 0.04 | 35% | 16 Jan → | |
| dust2 | 5–13 | -0.11 | 17% | 13 Jan → | |
| dust2 | 13–3 | -0.02 | 22% | 12 Jan → | |
| office | 13–8 | 0.14 | 34% | 3 Jan → | |
| mirage | 13–10 | 0.01 | 32% | 2 Jan → | |
| dust2 | 13–6 | 0.05 | 39% | 2 Jan → | |
| train | 13–7 | 0.11 | 21% | 1 Jan → | |
| nuke | 2–13 | 0.03 | 36% | 1 Jan → | |
| ancient | 3–7 | -0.07 | 36% | 29 Dec → | |
| dust2 | 0–13 | -0.11 | 25% | 25 Dec → | |
| dust2 | 9–13 | 0.14 | 28% | 24 Dec → | |
| mirage | 13–16 | 0.00 | 33% | 14 Dec → | |
| dust2 | 7–13 | -0.01 | 29% | 11 Dec → | |
| nuke | 13–7 | 0.02 | 21% | 15 Nov → | |
| nuke | 13–1 | 0.07 | 39% | 15 Nov → | |
| ancient | 3–13 | -0.00 | 33% | 15 Nov → | |
| mirage | 1–8 | -0.08 | 17% | 13 Nov → | |
| dust2 | 13–11 | 0.11 | 37% | 13 Nov → | |
| dust2 | 11–13 | -0.04 | 48% | 11 Nov → | |
| ancient | 6–13 | 0.02 | 23% | 11 Nov → | |
| train | 13–2 | 0.07 | 38% | 11 Nov → | |
| dust2 | 13–1 | 0.09 | 29% | 10 Nov → | |
| ancient | 13–2 | -0.01 | 47% | 9 Nov → | |
| dust2 | 6–13 | -0.00 | 47% | 9 Nov → | |
| dust2 | 13–2 | 0.02 | 57% | 9 Nov → | |
| dust2 | 13–7 | 0.02 | 50% | 8 Nov → | |
| mirage | 1–13 | -0.08 | 33% | 6 Nov → | |
| nuke | 4–0 | 0.02 | 40% | 6 Nov → | |
| ancient | 13–8 | 0.06 | 63% | 6 Nov → | |
| mirage | 13–2 | 0.15 | 37% | 6 Nov → | |
| nuke | 5–12 | 0.04 | 40% | 5 Nov → | |
| dust2 | 13–10 | 0.11 | 42% | 31 Oct → | |
| inferno | 8–13 | -0.02 | 11% | 30 Oct → | |
| mirage | 10–4 | 0.08 | 39% | 29 Oct → | |
| ancient | 13–7 | 0.02 | 31% | 29 Oct → | |
| mirage | 0–6 | -0.01 | 50% | 29 Oct → | |
| dust2 | 13–5 | 0.07 | 32% | 29 Oct → | |
| mirage | 13–4 | 0.04 | 24% | 28 Oct → | |
| mirage | 13–7 | -0.01 | 25% | 28 Oct → | |
| ancient | 13–6 | 0.09 | 33% | 28 Oct → | |
| mirage | 15–15 | -0.04 | 31% | 28 Oct → | |
| mirage | 13–10 | 0.06 | 38% | 28 Oct → | |
| overpass | 11–13 | 0.05 | 36% | 26 Oct → | |
| mirage | 13–6 | 0.12 | 42% | 25 Oct → | |
| mirage | 4–13 | -0.01 | 37% | 25 Oct → | |
| mirage | 13–8 | 0.09 | 35% | 24 Oct → | |
| train | 13–2 | 0.08 | 26% | 24 Oct → | |
| dust2 | 9–13 | -0.03 | 23% | 24 Oct → | |
| mirage | 8–13 | -0.01 | 21% | 24 Oct → | |
| mirage | 13–11 | -0.01 | 43% | 23 Oct → | |
| vertigo | 9–2 | 0.19 | 59% | 20 Oct → | |
| mirage | 0–13 | -0.07 | 36% | 20 Oct → | |
| dust2 | 9–13 | -0.08 | 38% | 20 Oct → | |
| dust2 | 6–13 | -0.08 | 16% | 16 Oct → | |
| dust2 | 13–10 | 0.02 | 37% | 16 Oct → | |
| dust2 | 13–3 | 0.11 | 25% | 16 Oct → | |
| dust2 | 13–7 | 0.13 | 35% | 16 Oct → | |
| inferno | 13–11 | -0.01 | 22% | 16 Oct → | |
| dust2 | 13–8 | 0.04 | 34% | 16 Oct → | |
| mirage | 13–5 | 0.02 | 36% | 15 Oct → | |
| dust2 | 13–6 | 0.01 | 29% | 15 Oct → | |
| dust2 | 13–6 | 0.00 | 44% | 14 Oct → | |
| mirage | 13–9 | -0.04 | 33% | 14 Oct → |
Match data via Leetify.
