𝕭𝖚𝕭𝕭𝖆 — CS2 Stats

DE76561199114365237[U:1:1154099509]Steam profile ↗✓ No bans

2,361Tracked matches45%Win rate2021Tracked since

2,057Hours in CS

CSDB Rating5.2 DevelopingPositional Player

FaceitLevel 8Top 31.2% of ranked FACEIT players

WingmanSupreme Master First Class

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 22 Sep 2026 (yesterday). Ranks are recorded once per day this page is viewed.

No change since then — still 2,361 tracked matches. Play, then come back: the next observation lands here.

Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 21 days played since 17 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

Premier CS Rating: 23,519 +6,993 24 Jul – 1 Sept · 13 days played

23,519Peak Premier in tracked matches

21Days played since 2026-07-17

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 Level 8 among CSDB-tracked players (n=14,086), 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	Level 8 median	Level 9 median	vs Level 9
Headshot rate	51.1%	46.8%	48.3%	above
Shot accuracy	9.1%	13.0%	13.2%	4.1% short
Kill/death ratio	1.24	1.06	1.07	above
Match win rate	48.1%	46.3%	46.9%	above

This profile matches the typical Level 9 player on 3 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 9 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim66

Positioning55

Utility47

0–100 skill scores via Leetify.

Recent form

COLD46–47–7Last 10046%Win rateTLLLLWWWLL

Last 10 vs previous 10: −20pp win rate · −0.03 avg rating · +0.1pp headshot accuracy · −11ms reaction

Win rate down 20pp 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

0–4–1 · 0% win rate
Avg rating -0.00
Avg headshot accuracy 21%
Avg reaction 641ms

Last 10

3–6–1 · 30% win rate
Avg rating 0.00
Avg headshot accuracy 19%
Avg reaction 645ms

Last 20

8–10–2 · 40% win rate
Avg rating 0.02
Avg headshot accuracy 19%
Avg reaction 651ms

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 against its own average).

Aim6.6

Utility4.7

Positioning5.5

Opening Duels2.8

Clutch5.2

Strong 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 NiKo 91% 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

T-side openings. Opening success drops from 49% on CT to 29% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 592ms 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

Aim6.6

Positioning5.5

Utility4.7

Mechanics5.8

Opening Duels2.4

Win Impact3.3

Composite 5.2/10 (Developing), 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

Match rating0.02−0.01

first ⅓ avg 0.02 → last ⅓ avg 0.02

Reaction time616ms+48ms

first ⅓ avg 567ms → last ⅓ avg 616ms

Headshot accuracy19.0%−0.1%

first ⅓ avg 19.1% → last ⅓ avg 19.0%

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

0.15Best match rating · 13–1 · mirage, 26 Jul →

64%Best headshot accuracy · 1–4 · dust2, 17 Jul →

344msFastest reaction time · 1–9 · inferno, 25 Jul →

13–1Biggest win · dust2, 7 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak

11–6In matches decided by ≤2 rounds

8Overtime games

Map breakdown

ancientBest map · 71% over 14nukeWeakest map · 0% over 5

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	39	20–19	51%	0.02
inferno	A	16	9–7	56%	0.02
ancient	S	14	10–4	71%	0.04
anubis	D	9	3–6	33%	0.01
cache	D	9	2–7	22%	-0.00
nuke	D	5	0–5	0%	-0.00
overpass	—	2	0–2	0%	0.03
mirage	—	2	1–1	50%	0.09
boulder	—	1	0–1	0%	-0.00
vertigo	—	1	0–1	0%	0.11
office	—	1	0–1	0%	0.00
italy	—	1	1–0	100%	0.09

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (0% over 5). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

113,478Lifetime kills

1.24K/D · Top 25% of Level 8 players

4,831Matches

48.1%Match win rate · Top 50% of Level 8 players

51.1%Headshot % · Top 50% of Level 8 players

9.1%Shot accuracy

13,475MVPs

2,057Hours (in match)

4,127Bombs planted

1,257Bombs defused

Most-used weapons

AK-4738,997

M4A4 / M4A1-S17,429

Desert Eagle12,204

P2000 / USP-S7,857

AWP6,292

Glock-184,877

Galil AR2,293

MP92,151

SSG 082,063

P901,937

Lifetime map wins

16,132dust2

4,531inferno

3,041vertigo

2,114nuke

1,300lake

741train

625office

274italy

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

Faceit stats

Combat

146Matches

59%Win rate

1.34Avg K/D

94.0ADR

49%Headshot %

Clutches & streaks

46%1v1 clutch win

31%1v2 clutch win

6Longest win streak

Recent Faceit resultsWWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	20	75%	1.65	19.3
Anubis	16	69%	1.30	18.8
Dust2	14	64%	1.47	19.3
Mirage	13	46%	1.07	16.0
Inferno	11	64%	1.48	20.4
Vertigo	9	11%	1.28	19.0
Overpass	2	0%	0.40	5.5
Nuke	2	50%	1.18	14.0

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.

20.1%Headshot accuracy

31.0%Accuracy (enemy spotted)

34.4%Spray accuracy

76.0%Counter-strafing

8.5°Preaim

592msReaction time

29.3%T opening success

49.3%CT opening success

0.50Enemies flashed / flash

4.6%Flash assists

6.84HE damage / grenade

6.94Flashes / 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.

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 29.2643% — below the 40% mark we flag

Spend your practice time on Nuke

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

0% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	15–15	0.02	17%	6 Sept →
anubis	9–13	0.01	30%	14 Aug →
dust2	3–13	-0.01	21%	8 Aug →
dust2	6–13	-0.05	20%	8 Aug →
overpass	2–4	0.02	17%	8 Aug →
cache	13–8	0.09	22%	7 Aug →
ancient	13–5	0.11	26%	7 Aug →
dust2	13–1	0.10	20%	7 Aug →
cache	11–13	-0.08	22%	7 Aug →
cache	0–5	-0.19	0%	7 Aug →
dust2	10–13	0.03	28%	7 Aug →
dust2	9–13	-0.06	11%	6 Aug →
ancient	9–13	0.03	18%	6 Aug →
dust2	13–5	0.04	18%	6 Aug →
inferno	13–6	0.08	30%	6 Aug →
dust2	13–3	0.04	20%	6 Aug →
inferno	13–10	0.03	17%	6 Aug →
ancient	8–13	0.09	21%	6 Aug →
nuke	8–8	0.05	18%	6 Aug →
dust2	13–9	-0.00	14%	6 Aug →
nuke	5–13	-0.03	33%	6 Aug →
dust2	0–13	-0.04	26%	5 Aug →
cache	13–11	0.08	16%	5 Aug →
dust2	11–13	0.07	20%	5 Aug →
inferno	8–13	-0.04	18%	4 Aug →
dust2	7–13	0.02	23%	4 Aug →
anubis	13–8	0.06	20%	4 Aug →
ancient	13–11	0.05	7%	4 Aug →
boulder	5–13	-0.00	15%	3 Aug →
ancient	16–14	-0.01	24%	3 Aug →
dust2	8–1	-0.00	13%	3 Aug →
ancient	13–4	0.09	11%	3 Aug →
cache	9–13	-0.02	13%	3 Aug →
ancient	14–16	0.03	16%	3 Aug →
inferno	13–11	0.02	16%	3 Aug →
dust2	7–13	0.03	18%	3 Aug →
dust2	13–5	0.12	10%	3 Aug →
nuke	3–13	-0.06	17%	3 Aug →
inferno	13–11	0.08	12%	3 Aug →
dust2	14–16	0.01	20%	2 Aug →
dust2	10–13	-0.01	21%	2 Aug →
mirage	7–13	0.03	21%	2 Aug →
dust2	12–12	0.03	10%	2 Aug →
inferno	6–13	0.01	23%	2 Aug →
vertigo	12–12	0.11	12%	2 Aug →
anubis	4–13	-0.05	18%	31 Jul →
office	12–12	0.00	7%	31 Jul →
dust2	13–11	0.03	21%	31 Jul →
dust2	13–11	0.02	14%	31 Jul →
dust2	13–10	0.02	15%	29 Jul →
ancient	13–10	0.03	16%	29 Jul →
dust2	15–15	-0.01	25%	29 Jul →
dust2	13–8	-0.01	24%	29 Jul →
dust2	13–11	-0.00	26%	28 Jul →
nuke	10–13	-0.02	30%	27 Jul →
anubis	13–8	0.07	19%	27 Jul →
inferno	13–11	0.09	21%	27 Jul →
inferno	5–13	-0.02	22%	27 Jul →
ancient	13–4	0.06	46%	27 Jul →
inferno	13–8	0.05	14%	27 Jul →
mirage	13–1	0.15	24%	26 Jul →
dust2	11–13	0.01	20%	26 Jul →
dust2	13–10	-0.02	27%	26 Jul →
inferno	4–9	0.01	22%	25 Jul →
inferno	1–9	-0.25	5%	25 Jul →
ancient	13–11	0.06	24%	25 Jul →
dust2	13–7	0.06	23%	25 Jul →
anubis	13–10	0.00	7%	25 Jul →
dust2	13–5	-0.06	9%	25 Jul →
ancient	13–8	0.01	16%	25 Jul →
anubis	13–16	0.05	13%	24 Jul →
dust2	3–13	-0.02	16%	24 Jul →
dust2	9–1	-0.02	11%	24 Jul →
inferno	10–13	-0.04	18%	24 Jul →
dust2	13–10	-0.02	12%	24 Jul →
dust2	5–13	-0.01	23%	24 Jul →
anubis	7–13	-0.00	12%	23 Jul →
dust2	13–6	0.08	22%	23 Jul →
dust2	13–10	0.01	22%	23 Jul →
anubis	4–13	-0.09	6%	23 Jul →
ancient	13–4	0.02	15%	23 Jul →
dust2	13–11	0.05	29%	20 Jul →
dust2	3–13	-0.04	0%	20 Jul →
ancient	9–13	-0.02	15%	19 Jul →
dust2	13–3	0.12	23%	19 Jul →
inferno	9–5	0.13	36%	19 Jul →
inferno	13–4	0.04	16%	19 Jul →
nuke	10–13	0.05	16%	19 Jul →
cache	7–13	0.08	12%	19 Jul →
cache	13–16	0.06	21%	19 Jul →
ancient	7–3	0.00	25%	19 Jul →
cache	12–12	-0.06	28%	19 Jul →
cache	13–16	0.01	16%	19 Jul →
inferno	13–9	0.14	24%	19 Jul →
dust2	2–13	-0.04	24%	19 Jul →
anubis	8–13	0.04	23%	18 Jul →
italy	9–3	0.09	7%	18 Jul →
overpass	4–13	0.05	37%	18 Jul →
inferno	9–13	0.07	16%	18 Jul →
dust2	1–4	0.14	64%	17 Jul →