Barka — CS2 Stats

HU76561198137626821[U:1:177361093]Steam profile ↗✓ No bans

2,895Tracked matches41%Win rate2020Tracked since

8,281Hours in CS8Hrs last 2 wks

CSDB Rating6.0 SolidAggressive Rifler

Premier CS Rating25,942Top 25% of 29,473 CSDB-tracked playersRed band · top ~2.5% of ranked players (population est.)

CSDB Leaderboard#4497 of 56661 tracked

FaceitLevel 10 · 2,481 ELOTop 12.4% of ranked FACEIT players

WingmanDistinguished Master Guardian

Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 10 among CSDB-tracked players (n=4,917), 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 10 median
Headshot rate	40.5%	51.9%
Shot accuracy	14.4%	13.7%
Kill/death ratio	1.17	1.08
Match win rate	50.8%	48.7%

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Performance scores

Aim79

Positioning56

Utility53

0–100 skill scores via Leetify.

Recent form

HOT50–43–7Last 10050%Win rateLWLWTWWWWW

Last 10 vs previous 10: +30pp win rate · -0.04 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim7.9

Aggression7.9

Utility5.3

Positioning5.6

Opening Duels3.6

Clutch4.8

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

Plays most like ropz 91% playstyle similarity

Most alike: utility contribution, positioning profile.

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 →

Strengths & areas to improve

Areas to improve

Reaction time. 560ms 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

Aim7.9

Positioning5.6

Utility5.3

Mechanics6.1

Opening Duels3.6

Win Impact1.9

Composite 6.0/10 (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 rating0.02+0.00

first ⅓ avg 0.01 → last ⅓ avg 0.02

Reaction time553ms−3ms

first ⅓ avg 556ms → last ⅓ avg 553ms

Headshot accuracy20.8%−2.3%

first ⅓ avg 23.0% → last ⅓ avg 20.8%

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.

Highlights

0.18Best rating — inferno 9–3

13–0Biggest win — dust2

5Longest win streak

3–7In matches decided by ≤2 rounds

3Overtime games

Map breakdown

anubisBest map · 80% over 5ancientWeakest map · 27% over 11

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	27	14–13	52%	0.01
dust2	B	23	11–12	48%	0.01
cache	C	13	5–8	38%	-0.01
ancient	D	11	3–8	27%	0.02
mirage	B	10	5–5	50%	0.00
anubis	S	5	4–1	80%	-0.01
overpass	—	3	2–1	67%	0.02
nuke	—	3	3–0	100%	0.05
office	—	3	1–2	33%	0.01
vertigo	—	1	1–0	100%	-0.02
train	—	1	1–0	100%	0.14

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (27% over 11). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

226,260Lifetime kills

1.17K/D · Top 50% of Level 10 players

9,114Matches

50.8%Match win rate · Top 50% of Level 10 players

40.5%Headshot %

14.4%Shot accuracy · Top 50% of Level 10 players

29,245MVPs

4,343Hours (in match)

7,661Bombs planted

2,429Bombs defused

Most-used weapons

AK-4765,481

M4A4 / M4A1-S34,675

AWP28,990

Desert Eagle16,009

P2000 / USP-S12,519

Glock-189,944

Tec-96,902

P2505,503

Five-SeveN4,323

MAC-104,152

Lifetime map wins

44,903inferno

7,187dust2

2,113nuke

1,718cbble

1,697train

583vertigo

475office

278bank

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

Faceit stats

Combat

782Matches

55%Win rate

1.19Avg K/D

94.0ADR

40%Headshot %

Clutches & streaks

44%1v1 clutch win

22%1v2 clutch win

9Longest win streak

Recent Faceit resultsLWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	73	71%	1.32	18.7
Ancient	59	46%	1.05	17.9
Anubis	50	70%	1.34	19.0
Mirage	46	46%	1.02	16.5
Dust2	39	46%	1.04	17.9
Overpass	11	45%	1.22	19.6
Nuke	11	73%	1.44	19.0
Vertigo	3	67%	1.05	15.7

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.

20.3%Headshot accuracy

33.9%Accuracy (enemy spotted)

38.7%Spray accuracy

77.3%Counter-strafing

7.3°Preaim

560msReaction time

43.5%T opening success

44.9%CT opening success

0.52Enemies flashed / flash

5.8%Flash assists

7.14HE damage / grenade

6.78Flashes / match

Recommended for you

Spend your practice time on Ancient

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

27% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
ancient	5–13	0.07	25%	20 Aug →
inferno	13–7	0.03	16%	20 Aug →
cache	10–13	-0.09	19%	20 Aug →
dust2	13–11	0.04	19%	19 Aug →
cache	12–12	0.07	14%	19 Aug →
inferno	13–4	0.02	20%	19 Aug →
ancient	13–3	0.07	24%	19 Aug →
dust2	8–3	0.04	50%	19 Aug →
inferno	9–3	-0.05	20%	19 Aug →
mirage	13–5	-0.00	14%	19 Aug →
dust2	8–13	-0.04	13%	18 Aug →
dust2	12–12	0.05	27%	18 Aug →
mirage	10–13	0.10	23%	18 Aug →
inferno	9–3	0.18	20%	2 Aug →
dust2	13–2	0.14	11%	1 Aug →
inferno	12–12	0.06	14%	1 Aug →
inferno	5–13	0.08	20%	31 Jul →
dust2	4–13	-0.05	21%	31 Jul →
mirage	10–3	-0.00	22%	31 Jul →
anubis	13–5	0.03	22%	31 Jul →
dust2	6–13	0.07	22%	31 Jul →
mirage	0–13	-0.07	33%	31 Jul →
cache	10–13	0.01	19%	30 Jul →
dust2	11–13	0.03	14%	29 Jul →
inferno	13–4	0.09	18%	29 Jul →
cache	11–13	-0.07	20%	29 Jul →
inferno	13–10	-0.02	28%	29 Jul →
cache	7–13	-0.04	25%	29 Jul →
inferno	4–13	-0.09	7%	23 Jul →
cache	1–6	0.01	22%	23 Jul →
inferno	0–2	-0.02	0%	16 Jul →
mirage	0–13	-0.09	38%	16 Jul →
inferno	5–13	-0.02	27%	16 Jul →
ancient	13–10	0.08	31%	12 Jul →
ancient	8–13	0.02	25%	12 Jul →
ancient	6–13	-0.08	13%	12 Jul →
inferno	13–4	0.02	19%	12 Jul →
inferno	13–9	0.01	20%	12 Jul →
cache	4–13	-0.03	21%	12 Jul →
inferno	13–9	0.00	15%	12 Jul →
mirage	0–13	-0.04	8%	12 Jul →
anubis	13–5	-0.04	21%	12 Jul →
cache	13–6	0.01	22%	12 Jul →
inferno	13–4	0.05	27%	12 Jul →
inferno	6–13	-0.00	11%	12 Jul →
cache	13–9	-0.04	16%	12 Jul →
anubis	13–7	0.03	29%	11 Jul →
dust2	10–13	0.03	31%	11 Jul →
inferno	11–13	-0.02	18%	10 Jul →
inferno	3–9	-0.13	27%	10 Jul →
inferno	6–9	-0.05	33%	10 Jul →
dust2	7–13	-0.04	67%	10 Jul →
inferno	13–4	-0.03	60%	10 Jul →
cache	13–3	-0.06	55%	10 Jul →
dust2	10–3	-0.04	56%	10 Jul →
inferno	13–3	0.16	22%	10 Jul →
dust2	13–0	0.00	50%	10 Jul →
inferno	8–8	-0.02	22%	10 Jul →
inferno	6–9	-0.14	18%	10 Jul →
mirage	16–14	0.03	25%	10 Jul →
overpass	13–9	-0.02	31%	10 Jul →
overpass	4–13	0.02	42%	10 Jul →
vertigo	13–8	-0.02	37%	10 Jul →
train	13–8	0.14	36%	10 Jul →
nuke	13–7	0.10	42%	9 Jul →
ancient	12–12	0.11	21%	9 Jul →
office	13–3	0.05	36%	9 Jul →
cache	13–10	0.03	46%	9 Jul →
cache	6–13	0.02	44%	9 Jul →
anubis	13–6	-0.00	18%	9 Jul →
dust2	12–12	-0.06	19%	9 Jul →
inferno	13–10	0.02	15%	9 Jul →
inferno	8–13	0.08	23%	9 Jul →
mirage	13–9	0.08	32%	8 Jul →
ancient	2–10	-0.01	21%	8 Jul →
office	10–13	0.02	29%	8 Jul →
dust2	13–10	-0.03	29%	8 Jul →
inferno	12–12	0.07	22%	8 Jul →
dust2	13–6	0.05	25%	8 Jul →
overpass	13–4	0.05	17%	8 Jul →
nuke	13–10	0.08	12%	8 Jul →
cache	13–5	0.02	12%	7 Jul →
office	3–13	-0.03	6%	7 Jul →
nuke	13–11	-0.03	5%	6 Jul →
dust2	11–13	-0.04	24%	6 Jul →
anubis	11–13	-0.04	24%	6 Jul →
inferno	13–3	0.04	21%	5 Jul →
ancient	10–13	0.01	23%	5 Jul →
ancient	5–13	-0.02	46%	5 Jul →
dust2	13–1	0.02	45%	5 Jul →
dust2	6–13	-0.00	18%	5 Jul →
dust2	13–4	-0.02	15%	5 Jul →
dust2	11–13	-0.02	15%	5 Jul →
ancient	9–13	-0.02	20%	5 Jul →
mirage	13–16	-0.01	22%	5 Jul →
dust2	2–13	0.01	36%	5 Jul →
mirage	13–1	0.05	25%	5 Jul →
dust2	16–13	0.10	20%	5 Jul →
dust2	13–9	-0.02	17%	5 Jul →
ancient	13–7	0.04	13%	5 Jul →