Unc 🅱️en — CS2 Stats

US76561198033451721[U:1:73185993]Steam profile ↗✓ No bans

449Tracked matches64%Win rate2020Tracked since

2,575Hours in CS9Hrs last 2 wks

CSDB Rating4.5 DevelopingSupport

Premier CS Rating14,497Blue band · top ~31.1% of ranked players (population est.)

CSDB Leaderboard#149229 of 252262 tracked

WingmanMaster Guardian Elite

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 15 Oct 2026 (yesterday). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 14,497 +1,471 16 Jul – 15 Oct · 28 days played

14,999Peak Premier in tracked matches

36Days played since 2026-07-16

Premier CS Rating

400 below peak (14,897)
+299 over 30 days · steady
+1,471 over 90 days
Next: Purple band at 15,000 — 503 to go
Reached: Blue band · Light Blue band
Blue band first seen 2026-08-29
Light Blue band first seen 2026-08-29

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Compare periods

Last 30 days vs previous 30

Metric	Last 30	Previous 30	Change
Matches	46	—	—
Win rate	59%	—	—
K/D	1.13	—	—
Headshot %	37%	—	—

Measured 20 Sep 2026 → 16 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=21,222), 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	Blue band median	Purple band median	vs Purple band
Headshot rate	30.2%	42.0%	44.3%	14.2% short
Shot accuracy	17.1%	9.6%	11.9%	above
Kill/death ratio	1.01	0.98	1.03	meets
Match win rate	64.4%	43.8%	45.2%	above

This profile matches the typical Purple band player on 3 of 4 comparable metrics.

Widest gap: Headshot rate. That is the metric furthest from the Purple band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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

Aim52

Positioning39

Utility41

0–100 skill scores via Leetify.

Recent form

STEADY51–45–4Last 10051%Win rateLLWTLWWWWL

Last 10 vs previous 10: −30pp win rate · −0.00 avg rating · −2.9pp headshot accuracy · +10ms reaction

Win rate down 30pp 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

1–3–1 · 20% win rate
Avg rating 0.01
Avg headshot accuracy 12%
Avg reaction 647ms

Last 10

5–4–1 · 50% win rate
Avg rating 0.02
Avg headshot accuracy 12%
Avg reaction 598ms

Last 20

13–6–1 · 65% win rate
Avg rating 0.02
Avg headshot accuracy 13%
Avg reaction 593ms

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).

Aim5.2

Utility4.1

Positioning3.9

Opening Duels1.0

Limited utility dependence

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 ZywOo 90% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower opening-duel success; 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

Reaction time. 584ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim5.2

Positioning3.9

Utility4.1

Mechanics4.2

Opening Duels1.3

Win Impact9.8

Composite 4.5/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00−0.00

first ⅓ avg 0.01 → last ⅓ avg 0.00

Reaction time578ms−6ms

first ⅓ avg 584ms → last ⅓ avg 578ms

Headshot accuracy11.9%−0.4%

first ⅓ avg 12.3% → last ⅓ avg 11.9%

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

0.14Best match rating · 13–7 · ancient, 25 Jul →

28%Best headshot accuracy · 4–13 · cache, 27 Aug →

336msFastest reaction time · 7–13 · ancient, 28 Aug →

13–2Biggest win · inferno, 29 Aug →

Across the last 100 tracked matches.

Highlights

6Longest win streak

L2Current streak

10–7In matches decided by ≤2 rounds

13Overtime games

Map breakdown

infernoBest map · 65% over 17dust2Weakest map · 33% over 9

Map	Grade	Played	Record	Win rate	Avg rating
inferno	S	17	11–6	65%	0.00
cache	B	15	8–7	53%	0.01
nuke	C	14	5–9	36%	-0.00
ancient	A	13	8–5	62%	0.01
anubis	C	12	5–7	42%	-0.02
dust2	D	9	3–6	33%	-0.00
mirage	C	8	3–5	38%	-0.01
train	C	5	2–3	40%	0.02
vertigo	—	4	3–1	75%	0.05
office	—	2	2–0	100%	-0.03
fachwerk	—	1	1–0	100%	0.02

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

93,352Lifetime kills

1.01K/D · Top 50% of Blue band

9,525Matches

64.4%Match win rate · Top 5% of Blue band

30.2%Headshot %

17.1%Shot accuracy · Top 10% of Blue band

5,996MVPs

1,568Hours (in match)

6,066Bombs planted

741Bombs defused

Most-used weapons

AK-4720,588

M4A4 / M4A1-S19,530

AWP10,216

P904,309

P2000 / USP-S3,708

P2503,528

MP72,782

Desert Eagle2,739

Galil AR2,685

Five-SeveN2,381

Lifetime map wins

4,622nuke

4,270dust2

2,380inferno

846cbble

804train

640office

402vertigo

305lake

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

121Matches

50%Win rate

0.98Avg K/D

—ADR

29%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

8Longest win streak

Recent Faceit resultsLLLWL

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.

12.2%Headshot accuracy

35.4%Accuracy (enemy spotted)

37.4%Spray accuracy

68.9%Counter-strafing

11.0°Preaim

584msReaction time

36.6%T opening success

34.1%CT opening success

0.58Enemies flashed / flash

5.1%Flash assists

9.78HE damage / grenade

2.49Flashes / match

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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 12.193% — below the 15% mark we flag
Aim Training →
Grenades & Utility
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 2.4929 — below the 4 mark we flag
Grenade Lineups →
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 36.5617% — below the 40% mark we flag

Spend your practice time on Dust 2

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.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
anubis	5–13	0.02	12%	15 Oct →
train	8–13	-0.01	9%	9 Oct →
train	13–9	0.05	8%	9 Oct →
nuke	15–15	0.01	12%	4 Oct →
mirage	14–16	0.01	17%	4 Oct →
dust2	13–11	0.01	23%	4 Oct →
dust2	13–5	0.04	6%	4 Oct →
inferno	13–11	0.09	13%	28 Sept →
nuke	13–6	0.03	13%	27 Sept →
inferno	4–13	-0.05	3%	27 Sept →
vertigo	13–3	0.12	15%	23 Sept →
vertigo	13–8	0.07	11%	23 Sept →
anubis	13–11	0.00	10%	20 Sept →
anubis	13–7	-0.01	14%	20 Sept →
nuke	13–6	0.05	17%	12 Sept →
ancient	13–11	0.02	12%	10 Sept →
ancient	6–13	0.02	11%	9 Sept →
cache	7–13	-0.08	23%	6 Sept →
ancient	13–7	-0.00	10%	6 Sept →
inferno	13–6	0.02	22%	6 Sept →
ancient	6–11	-0.11	3%	6 Sept →
dust2	13–5	-0.02	10%	6 Sept →
dust2	11–13	0.04	7%	6 Sept →
anubis	1–7	-0.07	0%	6 Sept →
office	13–10	-0.00	13%	3 Sept →
office	13–11	-0.06	18%	3 Sept →
inferno	13–8	0.01	11%	1 Sept →
nuke	15–15	-0.06	10%	1 Sept →
mirage	13–9	0.01	9%	30 Aug →
nuke	10–13	-0.03	11%	30 Aug →
dust2	2–13	-0.03	18%	30 Aug →
ancient	16–12	0.00	10%	30 Aug →
mirage	9–13	-0.07	11%	29 Aug →
cache	13–7	0.00	20%	29 Aug →
inferno	12–16	0.03	14%	29 Aug →
ancient	9–13	-0.02	15%	29 Aug →
inferno	13–2	0.01	10%	29 Aug →
anubis	13–7	0.02	12%	29 Aug →
mirage	13–7	-0.01	22%	29 Aug →
cache	13–8	-0.03	15%	28 Aug →
nuke	11–13	-0.04	15%	28 Aug →
nuke	13–10	0.10	8%	28 Aug →
inferno	7–13	-0.03	14%	28 Aug →
inferno	13–10	-0.02	10%	28 Aug →
ancient	7–13	-0.02	5%	28 Aug →
cache	13–5	0.04	9%	27 Aug →
cache	8–13	0.02	15%	27 Aug →
anubis	10–13	-0.05	5%	27 Aug →
cache	4–13	-0.01	28%	27 Aug →
mirage	7–13	-0.07	14%	19 Aug →
inferno	8–13	0.04	15%	19 Aug →
train	11–13	0.03	12%	13 Aug →
train	4–13	-0.04	11%	13 Aug →
train	13–7	0.07	18%	13 Aug →
dust2	2–13	-0.02	14%	11 Aug →
ancient	16–12	0.09	12%	9 Aug →
cache	8–13	-0.01	10%	9 Aug →
inferno	13–9	0.02	13%	9 Aug →
nuke	8–13	-0.04	14%	9 Aug →
dust2	10–13	-0.03	8%	6 Aug →
inferno	5–13	-0.01	16%	5 Aug →
cache	13–10	0.04	12%	5 Aug →
inferno	13–8	-0.03	17%	5 Aug →
cache	13–2	0.06	9%	5 Aug →
inferno	7–13	-0.05	2%	5 Aug →
vertigo	11–13	-0.00	14%	3 Aug →
vertigo	13–11	0.02	15%	3 Aug →
nuke	13–11	-0.01	9%	31 Jul →
inferno	13–10	0.04	17%	31 Jul →
anubis	13–6	0.02	14%	30 Jul →
cache	16–12	0.04	13%	30 Jul →
nuke	9–13	0.01	20%	29 Jul →
ancient	13–6	-0.02	15%	29 Jul →
mirage	2–13	-0.03	15%	29 Jul →
fachwerk	13–11	0.02	12%	28 Jul →
mirage	16–13	0.04	11%	26 Jul →
cache	15–15	0.03	15%	26 Jul →
anubis	16–13	-0.01	9%	26 Jul →
mirage	6–13	0.02	13%	26 Jul →
nuke	13–4	0.08	8%	26 Jul →
anubis	3–13	-0.04	13%	26 Jul →
ancient	5–13	-0.02	10%	25 Jul →
cache	11–13	0.04	10%	25 Jul →
ancient	13–7	0.14	6%	25 Jul →
inferno	13–3	-0.04	25%	23 Jul →
anubis	10–13	-0.04	10%	22 Jul →
anubis	10–13	0.00	11%	22 Jul →
cache	13–11	0.01	17%	20 Jul →
inferno	13–3	0.11	10%	20 Jul →
nuke	5–13	-0.04	17%	20 Jul →
ancient	13–3	-0.00	7%	20 Jul →
dust2	11–13	-0.05	13%	19 Jul →
inferno	13–11	-0.04	10%	19 Jul →
dust2	8–13	0.03	13%	19 Jul →
nuke	13–16	-0.05	4%	19 Jul →
ancient	13–10	0.05	6%	18 Jul →
cache	12–16	-0.04	17%	16 Jul →
cache	13–6	-0.01	11%	16 Jul →
anubis	9–13	-0.04	13%	16 Jul →
nuke	15–15	-0.00	11%	16 Jul →