Á𝓵𝓪𝓵𝓪𝓵𝓪 ♤ — CS2 Stats

US76561198146096195[U:1:185830467]Steam profile ↗✓ No bans

1,853Tracked matches77%Win rate2020Tracked since

5,029Hours in CS22Hrs last 2 wks

CSDB Rating6.7 SolidSupport

Premier CS Rating25,547Top 10% of 183,637 CSDB-tracked playersRed band · top ~2.7% of ranked players (population est.)

CSDB Leaderboard#15201 of 228403 tracked

FaceitLevel 3Top 90.6% of ranked FACEIT players

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 14 Sep 2026 (5 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.

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. 39 days played since 8 Jun 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: 25,547 +3,054 8 Jun – 14 Sept · 14 days played

25,547Peak Premier in tracked matches

39Days played since 2026-06-08

Premier CS Rating

At peak — 25,547
+3,436 over 90 days
Next: Gold band at 30,000 — 4,453 to go
Reached: Red band · Pink band · Purple band · Blue band
Red band first seen 2026-09-09
Pink band first seen 2026-09-09

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 3 among CSDB-tracked players (n=9,018), 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 3 median	Level 4 median	vs Level 4
Headshot rate	34.2%	41.9%	42.7%	8.5% short
Shot accuracy	16.3%	12.2%	11.2%	above
Kill/death ratio	1.26	0.98	1.00	above
Match win rate	57.2%	43.3%	43.9%	above

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

Widest gap: Headshot rate. That is the metric furthest from the Level 4 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim77

Positioning55

Utility64

0–100 skill scores via Leetify.

Recent form

HOT50–41–9Last 10050%Win rateLWWWWWLWWW

Last 10 vs previous 10: +10pp win rate · −0.00 avg rating · −4.0pp headshot accuracy · −108ms 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 0.00
Avg headshot accuracy 16%
Avg reaction 437ms

Last 10

8–2 · 80% win rate
Avg rating 0.01
Avg headshot accuracy 16%
Avg reaction 447ms

Last 20

15–5 · 75% win rate
Avg rating 0.02
Avg headshot accuracy 18%
Avg reaction 501ms

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 (+2.9 against its own average).

Aim7.7

Utility6.4

Positioning5.5

Opening Duels2.3

Clutch0.0

Effective flashes

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 Twistzz 87% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower aim profile.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

CSDB Rating breakdown

Aim7.7

Positioning5.5

Utility6.4

Mechanics5.2

Opening Duels2.6

Win Impact10.0

Composite 6.7/10 (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

Match rating0.01+0.01

first ⅓ avg 0.00 → last ⅓ avg 0.01

Reaction time507ms−9ms

first ⅓ avg 515ms → last ⅓ avg 507ms

Headshot accuracy16.8%+0.7%

first ⅓ avg 16.1% → last ⅓ avg 16.8%

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

0.12Best match rating · 13–6 · cache, 30 Jul →

39%Best headshot accuracy · 8–13 · anubis, 20 Jun →

344msFastest reaction time · 13–9 · dust2, 31 Aug →

13–1Biggest win · dust2, 13 Sept →

Across the last 100 tracked matches.

Highlights

9Longest win streak

2–8In matches decided by ≤2 rounds

4Overtime games

Map breakdown

anubisBest map · 60% over 5infernoWeakest map · 44% over 9

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	69	34–35	49%	0.01
inferno	C	9	4–5	44%	0.02
mirage	A	7	4–3	57%	0.00
anubis	A	5	3–2	60%	0.00
overpass	—	3	3–0	100%	-0.01
nuke	—	3	0–3	0%	-0.02
ancient	—	2	1–1	50%	-0.01
cache	—	2	1–1	50%	0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (44% over 9). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

153,337Lifetime kills

1.26K/D · Top 10% of Level 3 players

10,919Matches

57.2%Match win rate · Top 5% of Level 3 players

34.2%Headshot %

16.3%Shot accuracy · Top 25% of Level 3 players

15,920MVPs

3,128Hours (in match)

9,074Bombs planted

1,294Bombs defused

Most-used weapons

AWP43,622

AK-4724,115

M4A4 / M4A1-S18,940

P9010,342

SSG 087,156

Desert Eagle6,650

P2000 / USP-S5,585

Glock-184,951

MP74,284

SG 5533,938

Lifetime map wins

65,865dust2

4,032inferno

1,350nuke

640vertigo

253train

131office

129cbble

64lake

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

Faceit stats

Combat

43Matches

56%Win rate

1.11Avg K/D

71.6ADR

37%Headshot %

Clutches & streaks

0%1v1 clutch win

0%1v2 clutch win

4Longest win streak

Recent Faceit resultsLWWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	3	100%	0.83	11.7
Dust2	1	0%	0.93	13.0
Nuke	1	100%	0.50	9.0
Ancient	1	0%	0.75	12.0

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.

16.8%Headshot accuracy

37.6%Accuracy (enemy spotted)

36.4%Spray accuracy

73.6%Counter-strafing

8.6°Preaim

510msReaction time

35.4%T opening success

45.1%CT opening success

0.71Enemies flashed / flash

8.6%Flash assists

10.54HE damage / grenade

8.09Flashes / 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 35.3812% — below the 40% mark we flag

Spend your practice time on Inferno

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

44% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	7–13	-0.01	20%	17 Sept →
dust2	13–10	-0.03	13%	17 Sept →
overpass	13–10	-0.02	15%	17 Sept →
ancient	13–2	-0.00	21%	17 Sept →
inferno	13–6	0.07	14%	14 Sept →
dust2	13–10	0.08	19%	14 Sept →
dust2	4–13	0.06	23%	13 Sept →
dust2	13–1	-0.04	13%	13 Sept →
dust2	13–10	0.01	10%	12 Sept →
dust2	13–8	0.01	10%	12 Sept →
dust2	8–1	0.05	25%	12 Sept →
dust2	13–11	-0.00	26%	12 Sept →
dust2	13–6	0.02	22%	10 Sept →
mirage	13–10	0.03	14%	9 Sept →
dust2	13–4	0.02	25%	9 Sept →
mirage	13–4	0.00	17%	9 Sept →
dust2	10–13	0.02	13%	9 Sept →
inferno	4–13	-0.00	15%	8 Sept →
dust2	13–4	0.02	10%	7 Sept →
dust2	2–13	-0.02	28%	7 Sept →
dust2	13–9	0.02	14%	7 Sept →
dust2	13–5	0.03	31%	6 Sept →
ancient	7–13	-0.02	15%	6 Sept →
anubis	13–8	-0.04	16%	6 Sept →
inferno	13–10	0.02	19%	6 Sept →
dust2	13–6	0.00	10%	5 Sept →
cache	11–13	-0.02	11%	5 Sept →
anubis	13–8	0.01	11%	5 Sept →
anubis	13–4	0.04	13%	5 Sept →
dust2	13–9	-0.03	22%	5 Sept →
dust2	6–13	-0.04	23%	31 Aug →
dust2	13–9	0.04	4%	31 Aug →
dust2	13–9	-0.04	13%	30 Aug →
dust2	13–7	-0.04	24%	30 Aug →
inferno	13–6	0.03	20%	30 Aug →
dust2	13–6	-0.07	11%	30 Aug →
mirage	1–13	-0.02	20%	29 Aug →
dust2	10–13	-0.06	16%	29 Aug →
dust2	4–13	-0.08	23%	25 Aug →
mirage	12–12	0.00	10%	25 Aug →
dust2	13–8	0.00	23%	23 Aug →
mirage	13–7	-0.05	11%	17 Aug →
dust2	10–13	-0.04	14%	17 Aug →
nuke	10–13	0.05	19%	15 Aug →
dust2	13–3	0.10	19%	15 Aug →
dust2	13–2	0.11	20%	15 Aug →
dust2	13–5	0.04	14%	14 Aug →
mirage	13–10	0.02	17%	14 Aug →
dust2	7–13	-0.05	19%	13 Aug →
dust2	12–12	0.01	20%	13 Aug →
dust2	7–13	-0.03	21%	13 Aug →
dust2	12–12	0.03	16%	11 Aug →
dust2	9–0	0.02	28%	11 Aug →
dust2	5–13	-0.08	7%	11 Aug →
dust2	11–13	0.04	13%	10 Aug →
dust2	13–9	0.03	25%	10 Aug →
dust2	2–13	-0.04	9%	10 Aug →
dust2	13–5	0.11	32%	4 Aug →
dust2	6–13	0.02	29%	3 Aug →
dust2	11–13	0.01	13%	3 Aug →
inferno	13–5	0.10	20%	1 Aug →
dust2	13–16	-0.00	13%	30 Jul →
dust2	13–1	0.10	18%	30 Jul →
nuke	4–13	-0.08	3%	30 Jul →
cache	13–6	0.12	9%	30 Jul →
dust2	6–13	-0.04	19%	23 Jun →
mirage	7–13	0.02	13%	22 Jun →
overpass	13–10	-0.00	19%	22 Jun →
nuke	8–13	-0.04	15%	21 Jun →
dust2	7–13	0.01	24%	21 Jun →
dust2	12–12	0.06	17%	20 Jun →
inferno	11–13	0.03	10%	20 Jun →
anubis	14–16	-0.02	14%	20 Jun →
inferno	8–13	-0.03	18%	20 Jun →
anubis	8–13	0.02	39%	20 Jun →
dust2	7–13	-0.04	13%	20 Jun →
dust2	9–13	-0.02	8%	19 Jun →
dust2	12–12	-0.00	19%	19 Jun →
dust2	13–9	0.06	15%	19 Jun →
dust2	13–10	0.02	19%	18 Jun →
dust2	13–2	0.02	5%	18 Jun →
dust2	11–13	-0.03	21%	18 Jun →
dust2	13–7	0.05	10%	18 Jun →
dust2	8–13	-0.01	17%	18 Jun →
dust2	3–13	0.00	11%	18 Jun →
dust2	12–12	0.05	25%	17 Jun →
dust2	8–13	0.06	18%	16 Jun →
inferno	13–16	-0.02	18%	16 Jun →
dust2	0–13	-0.03	13%	14 Jun →
inferno	11–13	0.01	9%	13 Jun →
dust2	11–13	-0.04	20%	13 Jun →
dust2	12–12	-0.02	17%	13 Jun →
dust2	13–1	-0.01	19%	12 Jun →
dust2	12–12	-0.02	8%	12 Jun →
overpass	13–10	-0.00	11%	10 Jun →
dust2	13–11	0.00	16%	9 Jun →
dust2	13–3	0.05	19%	9 Jun →
dust2	15–15	-0.03	12%	8 Jun →
dust2	1–13	0.03	18%	8 Jun →
dust2	13–1	-0.02	17%	8 Jun →