★.𝕂𝔽𝕄 — CS2 Stats

CH76561198124184579[U:1:163918851]Steam profile ↗✓ No bans

1,420Tracked matches62%Win rate2020Tracked since

4,577Hours in CS9Hrs last 2 wks

CSDB Rating6.8 SolidPositional Player

Premier CS Rating14,999Blue band · top ~28.4% of ranked players (population est.)

CSDB Leaderboard#148361 of 259149 tracked

WingmanGold Nova II

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 28 Oct 2026 (4 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.

Rating over time

Premier CS Rating: 14,999 -3,461 7 Sept – 28 Oct · 18 days played

19,007Peak Premier in tracked matches

45Days played since 2025-09-07

Premier CS Rating

3,498 below peak (18,497)
Next: Purple band at 15,000 — 1 to go
Reached: Purple band · Blue band · Light Blue band

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

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	54.2%	42.0%	44.4%	above
Shot accuracy	14.8%	9.6%	11.9%	above
Kill/death ratio	1.55	0.98	1.03	above
Match win rate	41.8%	43.8%	45.2%	3.4% short

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

Widest gap: Match win 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.

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Performance scores

Aim89

Positioning60

Utility53

0–100 skill scores via Leetify.

Recent form

HOT45–52–3Last 10045%Win rateWWWWWWWWWL

Last 10 vs previous 10: +40pp win rate · +0.06 avg rating · −3.6pp headshot accuracy · −23ms reaction

Win rate up 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

5–0 · 100% win rate
Avg rating 0.05
Avg headshot accuracy 17%
Avg reaction 422ms

Last 10

9–1 · 90% win rate
Avg rating 0.04
Avg headshot accuracy 19%
Avg reaction 441ms

Last 20

14–6 · 70% win rate
Avg rating 0.01
Avg headshot accuracy 21%
Avg reaction 453ms

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 (+1.1 against its own average).

Aim8.9

Utility5.3

Positioning6.0

Opening Duels6.0

Clutch2.2

Sharp aimer

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 90% playstyle similarity

Most alike: aim profile, positioning profile.

Where you differ: lower utility contribution.

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 89 — the mechanical foundation is a clear strength.

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

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

Aim8.9

Positioning6.0

Utility5.3

Mechanics6.3

Opening Duels6.6

Win Impact9.0

Composite 6.8/10 (Solid), 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+0.01

first ⅓ avg -0.00 → last ⅓ avg 0.00

Reaction time518ms−66ms

first ⅓ avg 584ms → last ⅓ avg 518ms

Headshot accuracy24.3%+4.8%

first ⅓ avg 19.5% → last ⅓ avg 24.3%

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

0.17Best match rating · 13–8 · dust2, 16 Apr →

50%Best headshot accuracy · 3–3 · mirage, 1 Aug →

328msFastest reaction time · 13–10 · ancient, 28 Oct →

13–0Biggest win · cache, 25 Oct →

Across the last 100 tracked matches.

Highlights

9Longest win streak

W9Current streak

10–6In matches decided by ≤2 rounds

6Overtime games

Map breakdown

overpassBest map · 60% over 5dust2Weakest map · 25% over 20

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	21	9–12	43%	-0.01
dust2	D	20	5–15	25%	-0.01
inferno	B	15	7–8	47%	0.01
cache	A	14	8–6	57%	-0.00
nuke	B	12	6–6	50%	0.01
ancient	D	9	3–6	33%	0.01
overpass	A	5	3–2	60%	-0.03
anubis	—	3	3–0	100%	-0.01
train	—	1	1–0	100%	0.06

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (25% over 20). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

174,431Lifetime kills

1.55K/D · Top 5% of Blue band

6,063Matches

41.8%Match win rate

54.2%Headshot % · Top 10% of Blue band

14.8%Shot accuracy · Top 25% of Blue band

15,349MVPs

2,269Hours (in match)

3,850Bombs planted

1,242Bombs defused

Most-used weapons

AK-4761,747

AWP32,007

Desert Eagle24,273

M4A4 / M4A1-S14,215

P2000 / USP-S8,987

Glock-185,084

SSG 084,373

P2502,958

Knife2,155

FAMAS2,120

Lifetime map wins

12,143dust2

5,059inferno

2,138cbble

1,701vertigo

1,638nuke

812train

302lake

183office

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

Faceit stats

Combat

331Matches

53%Win rate

1.28Avg K/D

83.5ADR

38%Headshot %

Clutches & streaks

31%1v1 clutch win

32%1v2 clutch win

7Longest win streak

Recent Faceit resultsLLWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	57	61%	1.24	16.1
Inferno	33	52%	1.62	15.8
Dust2	23	57%	1.08	15.1
Anubis	21	71%	1.40	15.8
Ancient	14	43%	1.32	18.4
Nuke	5	60%	1.25	16.6
Overpass	5	60%	1.28	15.0
Vertigo	5	60%	1.84	20.6

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.

23.9%Headshot accuracy

36.2%Accuracy (enemy spotted)

40.0%Spray accuracy

78.5%Counter-strafing

7.5°Preaim

507msReaction time

53.1%T opening success

59.6%CT opening success

0.54Enemies flashed / flash

3.9%Flash assists

6.02HE damage / grenade

15.36Flashes / match

Recommended for you

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.

25% win rate across 20 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
ancient	13–10	0.08	18%	28 Oct →
inferno	13–3	0.14	15%	28 Oct →
cache	13–10	-0.04	16%	25 Oct →
inferno	13–5	-0.02	18%	25 Oct →
cache	13–0	0.10	19%	25 Oct →
mirage	13–10	0.09	12%	24 Oct →
cache	13–4	-0.00	32%	24 Oct →
nuke	13–11	0.09	20%	24 Oct →
nuke	13–10	0.01	19%	23 Oct →
inferno	11–13	-0.05	26%	23 Oct →
ancient	13–10	0.04	21%	23 Oct →
dust2	3–13	-0.06	21%	17 Oct →
inferno	13–11	-0.01	30%	17 Oct →
mirage	10–13	-0.01	24%	3 Oct →
cache	13–8	-0.04	6%	3 Oct →
dust2	6–13	0.02	30%	2 Oct →
mirage	8–4	-0.04	25%	2 Oct →
cache	11–13	-0.03	21%	12 Aug →
dust2	13–9	0.02	32%	12 Aug →
mirage	7–13	-0.08	20%	12 Aug →
cache	7–13	-0.02	30%	11 Aug →
mirage	13–8	-0.04	40%	11 Aug →
dust2	9–13	-0.04	44%	10 Aug →
mirage	10–13	0.03	36%	10 Aug →
cache	10–13	-0.00	14%	3 Aug →
nuke	13–11	-0.04	25%	1 Aug →
anubis	13–3	-0.03	25%	1 Aug →
mirage	3–3	0.08	50%	1 Aug →
inferno	12–12	-0.00	20%	1 Aug →
dust2	4–13	-0.05	36%	1 Aug →
ancient	9–13	-0.03	11%	1 Aug →
inferno	13–4	-0.01	24%	30 Jul →
anubis	16–14	0.01	24%	29 Jul →
mirage	5–13	-0.04	19%	28 Jul →
nuke	13–11	0.04	19%	28 Jul →
inferno	11–13	0.01	20%	28 Jul →
ancient	13–16	-0.01	23%	26 Jul →
cache	13–5	0.04	21%	26 Jul →
dust2	5–13	0.00	31%	25 Jul →
mirage	8–13	-0.07	20%	25 Jul →
dust2	4–13	-0.04	27%	25 Jul →
cache	3–13	-0.07	27%	25 Jul →
inferno	5–13	-0.01	22%	25 May →
dust2	0–13	-0.08	29%	24 May →
nuke	8–13	-0.05	20%	24 May →
anubis	13–5	-0.02	21%	24 May →
cache	13–7	-0.00	14%	30 Apr →
cache	9–13	-0.04	41%	30 Apr →
cache	11–13	-0.02	17%	30 Apr →
cache	13–5	0.01	18%	29 Apr →
cache	13–3	0.07	19%	29 Apr →
dust2	13–9	0.08	26%	21 Apr →
mirage	9–13	-0.06	32%	21 Apr →
mirage	6–13	-0.02	32%	20 Apr →
ancient	4–13	0.01	29%	20 Apr →
nuke	12–12	-0.01	25%	18 Apr →
mirage	13–9	-0.04	17%	17 Apr →
mirage	13–9	0.04	11%	17 Apr →
dust2	13–8	0.17	24%	16 Apr →
mirage	13–10	0.01	26%	16 Apr →
inferno	13–11	0.01	24%	15 Apr →
ancient	7–13	-0.04	11%	14 Apr →
overpass	13–11	-0.03	20%	14 Apr →
dust2	11–13	-0.05	20%	13 Apr →
overpass	13–8	0.00	23%	13 Apr →
overpass	13–10	0.07	22%	13 Apr →
inferno	6–13	0.02	23%	13 Apr →
inferno	12–16	0.01	13%	10 Apr →
dust2	13–9	-0.03	17%	10 Apr →
mirage	13–11	-0.02	19%	10 Apr →
mirage	13–6	0.07	11%	9 Apr →
nuke	0–9	-0.02	32%	9 Apr →
ancient	8–13	-0.04	21%	6 Apr →
dust2	13–10	0.03	29%	6 Apr →
mirage	15–15	0.01	36%	6 Apr →
dust2	9–13	0.03	39%	5 Apr →
dust2	9–13	0.00	25%	22 Mar →
nuke	13–11	0.09	17%	22 Mar →
inferno	10–13	-0.02	24%	11 Dec →
mirage	8–13	-0.01	18%	6 Dec →
dust2	2–13	-0.05	10%	26 Oct →
overpass	10–13	-0.05	10%	26 Oct →
mirage	7–13	0.01	8%	17 Oct →
nuke	5–13	-0.06	9%	12 Oct →
dust2	7–13	-0.00	21%	10 Oct →
mirage	5–13	-0.02	20%	10 Oct →
dust2	9–13	-0.03	9%	13 Sept →
overpass	6–13	-0.15	5%	13 Sept →
nuke	6–13	0.02	17%	13 Sept →
nuke	16–12	-0.01	19%	12 Sept →
nuke	10–13	0.02	19%	12 Sept →
dust2	10–13	0.02	12%	12 Sept →
inferno	13–10	0.06	15%	12 Sept →
inferno	13–7	-0.02	22%	11 Sept →
mirage	3–13	-0.03	21%	10 Sept →
ancient	9–13	0.03	22%	10 Sept →
inferno	11–13	-0.01	39%	7 Sept →
dust2	1–13	-0.09	8%	7 Sept →
train	6–1	0.06	44%	7 Sept →
ancient	16–13	0.05	18%	7 Sept →