`#.BarBye ♿✈ — CS2 Stats

RU76561198009648732[U:1:49383004]Steam profile ↗VAC banned

768Tracked matches54%Win rate2020Tracked since

2,603Hours in CS6Hrs last 2 wks

CSDB Rating4.5 DevelopingAll-Rounder

CSDB Leaderboard#231076 of 239296 tracked

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 12 Sep 2026 (11 days ago). Ranks are recorded once per day this page is viewed.

0Faceit ELO · 1,242 → 1,242

+7Tracked matches · now 768

+5.7ppWin rate · 48.1% → 53.8%

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. 47 days played since 16 Mar 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: 21,839 +2,780 13 Jun – 6 Jul · 7 days played

Faceit ELO: 1,242 +0 3 Sept – 12 Sept · 2 observations

23,346Peak Premier in tracked matches

1,242Highest Faceit ELO seen on CSDB

47Days played since 2026-03-16

Faceit ELO

At peak — 1,242
Next: Level 7 at 1,351 — 109 to go
Reached: Level 6 · Level 5 · Level 4 · Level 3
Level 6 first seen 2026-09-03
Level 5 first seen 2026-09-03

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

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Performance scores

Aim55

Positioning53

Utility43

0–100 skill scores via Leetify.

Recent form

STEADY46–46–8Last 10046%Win rateTLTWWLWLTW

Last 10 vs previous 10: 0pp win rate · +0.04 avg rating · −4.7pp headshot accuracy · −51ms reaction

Win rate 0pp 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

2–1–2 · 40% win rate
Avg rating 0.01
Avg headshot accuracy 13%
Avg reaction 556ms

Last 10

4–3–3 · 40% win rate
Avg rating 0.02
Avg headshot accuracy 16%
Avg reaction 566ms

Last 20

8–9–3 · 40% win rate
Avg rating -0.00
Avg headshot accuracy 18%
Avg reaction 592ms

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: All-Rounder — No style dimension stands clear of the others in this profile.

Aim5.5

Utility4.3

Positioning5.3

Opening Duels3.4

Clutch5.2

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 jL 83% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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. 585ms 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

Aim5.5

Positioning5.3

Utility4.3

Mechanics4.3

Opening Duels3.9

Win Impact6.3

Composite 4.5/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.01

first ⅓ avg -0.00 → last ⅓ avg -0.01

Reaction time595ms−37ms

first ⅓ avg 632ms → last ⅓ avg 595ms

Headshot accuracy18.6%+1.8%

first ⅓ avg 16.8% → last ⅓ avg 18.6%

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

0.20Best match rating · 13–2 · dust2, 18 Jun →

50%Best headshot accuracy · 13–4 · cache, 22 Aug →

352msFastest reaction time · 13–5 · inferno, 20 Jun →

13–1Biggest win · dust2, 21 Sept →

Across the last 100 tracked matches.

Highlights

10Longest win streak

5–8In matches decided by ≤2 rounds

10Overtime games

Map breakdown

mirageBest map · 63% over 8infernoWeakest map · 38% over 21

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	29	12–17	41%	0.02
inferno	C	21	8–13	38%	-0.01
anubis	A	12	7–5	58%	0.01
cache	A	10	6–4	60%	-0.02
ancient	C	8	3–5	38%	-0.02
mirage	A	8	5–3	63%	0.03
italy	C	5	2–3	40%	-0.01
nuke	—	4	1–3	25%	-0.02
train	—	1	1–0	100%	0.03
overpass	—	1	1–0	100%	0.01
office	—	1	0–1	0%	-0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 21). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

98,425Lifetime kills

1.42K/D · Top 5% of tracked players

3,933Matches

44.4%Match win rate

38.4%Headshot %

18.1%Shot accuracy · Top 10% of tracked players

10,019MVPs

1,470Hours (in match)

2,946Bombs planted

1,302Bombs defused

Most-used weapons

AWP26,190

M4A4 / M4A1-S16,266

AK-4715,476

P2506,796

P2000 / USP-S5,043

Glock-183,429

Desert Eagle2,587

Galil AR2,224

SSG 082,217

MAC-102,187

Lifetime map wins

8,429dust2

6,333inferno

1,654nuke

1,474train

1,162cbble

712vertigo

448office

284aztec

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

Faceit stats

Combat

237Matches

53%Win rate

1.27Avg K/D

69.3ADR

33%Headshot %

Clutches & streaks

46%1v1 clutch win

18%1v2 clutch win

7Longest win streak

Recent Faceit resultsWLLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	21	38%	0.91	12.5
Dust2	21	38%	0.92	14.1
Anubis	12	58%	0.94	14.4
Mirage	8	50%	1.24	18.3
Ancient	8	75%	0.96	13.9
Overpass	4	0%	0.75	13.0
Train	3	0%	1.09	16.3
Cache	2	100%	1.15	16.0

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.

19.2%Headshot accuracy

31.1%Accuracy (enemy spotted)

30.4%Spray accuracy

69.3%Counter-strafing

9.3°Preaim

585msReaction time

46.5%T opening success

44.9%CT opening success

0.49Enemies flashed / flash

2.3%Flash assists

8.04HE damage / grenade

6.89Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4895 — below the 0.5 mark we flag
Grenade Lineups →

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.

38% win rate across 21 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
italy	12–12	-0.05	11%	22 Sept →
cache	7–13	0.01	9%	21 Sept →
dust2	12–12	0.07	15%	21 Sept →
dust2	13–1	0.02	9%	21 Sept →
inferno	13–11	0.02	19%	19 Sept →
dust2	9–13	0.04	26%	16 Sept →
inferno	13–10	0.08	26%	16 Sept →
anubis	9–13	-0.03	15%	31 Aug →
inferno	12–12	-0.03	12%	28 Aug →
dust2	13–5	0.03	19%	28 Aug →
cache	10–13	-0.08	11%	28 Aug →
inferno	5–13	0.00	11%	25 Aug →
dust2	11–13	0.00	23%	25 Aug →
cache	13–4	-0.01	50%	22 Aug →
inferno	9–13	-0.04	18%	22 Aug →
dust2	11–13	-0.07	14%	22 Aug →
ancient	13–11	0.02	15%	21 Aug →
dust2	9–13	-0.07	19%	20 Aug →
anubis	13–9	0.01	20%	20 Aug →
cache	16–13	0.02	27%	19 Aug →
inferno	9–13	-0.02	15%	18 Aug →
ancient	11–13	-0.08	15%	18 Aug →
ancient	15–15	-0.05	31%	17 Aug →
dust2	4–13	-0.01	15%	17 Aug →
cache	13–3	-0.07	5%	27 Jul →
anubis	13–10	-0.07	22%	27 Jul →
anubis	16–13	0.11	30%	26 Jul →
cache	16–13	-0.04	16%	26 Jul →
ancient	13–3	0.06	21%	26 Jul →
inferno	13–10	0.01	30%	17 Jul →
dust2	11–13	-0.03	4%	17 Jul →
dust2	5–13	-0.02	38%	17 Jul →
cache	3–11	0.00	7%	9 Jul →
dust2	12–12	0.02	33%	9 Jul →
mirage	13–10	0.05	14%	7 Jul →
inferno	12–8	-0.05	14%	6 Jul →
dust2	5–13	-0.03	21%	6 Jul →
mirage	6–13	-0.03	13%	6 Jul →
dust2	13–3	-0.04	22%	6 Jul →
anubis	5–13	-0.05	14%	5 Jul →
inferno	2–13	-0.07	10%	5 Jul →
inferno	6–13	-0.07	23%	5 Jul →
inferno	9–13	-0.08	13%	4 Jul →
train	13–6	0.03	11%	3 Jul →
anubis	5–13	-0.09	17%	25 Jun →
mirage	13–3	0.09	14%	25 Jun →
anubis	8–13	-0.05	13%	23 Jun →
mirage	13–10	0.05	13%	22 Jun →
anubis	13–1	0.06	13%	22 Jun →
dust2	13–3	0.09	19%	20 Jun →
mirage	13–10	0.04	17%	20 Jun →
dust2	13–3	0.04	17%	20 Jun →
dust2	13–8	0.01	14%	20 Jun →
inferno	13–5	0.10	22%	20 Jun →
inferno	13–7	0.01	25%	18 Jun →
anubis	13–3	0.01	14%	18 Jun →
dust2	13–2	0.06	22%	18 Jun →
inferno	11–13	-0.02	11%	18 Jun →
inferno	4–13	0.02	14%	18 Jun →
dust2	13–2	0.20	21%	18 Jun →
cache	13–4	-0.04	7%	17 Jun →
dust2	11–13	-0.01	24%	17 Jun →
ancient	13–16	-0.05	20%	13 Jun →
overpass	13–9	0.01	23%	13 Jun →
anubis	13–9	0.15	21%	13 Jun →
dust2	13–16	0.09	26%	13 Jun →
cache	12–12	0.03	14%	13 Jun →
inferno	13–7	0.03	13%	13 Jun →
dust2	11–13	0.11	22%	13 Jun →
mirage	16–14	0.06	5%	13 Jun →
dust2	13–8	0.03	15%	12 Jun →
mirage	4–13	0.02	9%	9 Jun →
dust2	12–12	-0.00	17%	9 Jun →
anubis	15–15	0.02	17%	26 May →
ancient	2–13	-0.00	22%	16 May →
anubis	13–11	0.03	10%	16 May →
dust2	13–6	0.05	22%	16 May →
nuke	12–16	0.07	18%	16 May →
cache	13–6	-0.02	21%	6 May →
italy	13–11	-0.07	18%	23 Apr →
inferno	5–13	-0.01	19%	15 Apr →
dust2	13–8	0.01	29%	15 Apr →
inferno	0–13	-0.13	9%	15 Apr →
ancient	6–13	-0.04	12%	14 Apr →
inferno	2–13	-0.03	18%	9 Apr →
office	9–13	-0.03	26%	8 Apr →
italy	11–13	-0.01	20%	7 Apr →
nuke	16–12	-0.03	16%	3 Apr →
inferno	10–13	0.01	18%	31 Mar →
dust2	8–13	-0.03	30%	31 Mar →
italy	13–6	0.09	14%	24 Mar →
italy	9–13	-0.02	29%	19 Mar →
dust2	10–13	-0.02	12%	18 Mar →
nuke	6–13	0.01	15%	18 Mar →
nuke	4–9	-0.12	14%	17 Mar →
mirage	3–13	-0.01	10%	17 Mar →
dust2	13–2	0.10	13%	17 Mar →
inferno	13–7	-0.02	10%	16 Mar →
ancient	13–9	-0.01	14%	16 Mar →
dust2	5–13	-0.07	17%	16 Mar →