⛧⃝𓄃𝑩𝒖𝒄𝒌𝒚 — CS2 Stats

76561199019944561[U:1:1059678833]Steam profile ↗✓ No bans

4,025Tracked matches37%Win rate2020Tracked since

3,737Hours in CS

CSDB Rating4.8 DevelopingHybrid Rifler

Premier CS Rating12,756Blue band · top ~40.3% of ranked players (population est.)

CSDB Leaderboard#38323 of 57629 tracked

FaceitLevel 5Top 67.6% of ranked FACEIT players

WingmanGold Nova III

Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 5 among CSDB-tracked players (n=2,587), 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 5 median	Level 6 median	vs Level 6
Headshot rate	41.5%	43.7%	44.7%	3.1% short
Shot accuracy	5.6%	11.8%	12.1%	6.5% short
Kill/death ratio	0.80	1.02	1.04	0.23 short
Match win rate	41.3%	45.0%	45.2%	3.9% short

This profile sits below the typical Level 6 player on every metric we can compare.

Widest gap: Shot accuracy. That is the metric furthest from the Level 6 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim64

Positioning58

Utility36

0–100 skill scores via Leetify.

Recent form

COLD52–45–3Last 10052%Win rateLLLWWLWLLL

Last 10 vs previous 10: +0pp win rate · +0.02 avg rating

Player DNA

Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.

Aim6.4

Aggression9.0

Utility3.6

Positioning5.8

Opening Duels4.6

Clutch3.4

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 85% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: higher opening-fight frequency; 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. 611ms 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

Aim6.4

Positioning5.8

Utility3.6

Mechanics6.2

Opening Duels4.6

Win Impact0.6

Composite 4.8/10 (Developing), 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 0.02 → last ⅓ avg 0.00

Reaction time609ms+14ms

first ⅓ avg 595ms → last ⅓ avg 609ms

Headshot accuracy16.9%+2.5%

first ⅓ avg 14.4% → last ⅓ avg 16.9%

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 — mirage 13–9

13–2Biggest win — nuke

7Longest win streak

L3Current streak

12–11In matches decided by ≤2 rounds

17Overtime games

Map breakdown

ancientBest map · 62% over 13infernoWeakest map · 33% over 6

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	31	16–15	52%	0.01
mirage	A	25	14–11	56%	0.01
ancient	A	13	8–5	62%	0.03
nuke	C	11	4–7	36%	0.00
anubis	B	10	5–5	50%	0.01
inferno	D	6	2–4	33%	-0.01
cache	—	3	2–1	67%	-0.01
train	—	1	1–0	100%	-0.07

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

129,745Lifetime kills

0.80K/D

7,324Matches

41.3%Match win rate

41.5%Headshot %

5.6%Shot accuracy

11,930MVPs

3,737Hours (in match)

6,806Bombs planted

997Bombs defused

Most-used weapons

AK-4751,898

M4A4 / M4A1-S27,263

AWP9,781

Desert Eagle9,443

P2000 / USP-S5,726

Glock-184,221

MP93,226

Galil AR3,212

Zeus x272,655

Knife1,318

Lifetime map wins

21,864dust2

3,060inferno

2,917vertigo

1,688nuke

264train

236cbble

39ar_shoots

37lake

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

Faceit stats

Combat

298Matches

52%Win rate

1.07Avg K/D

78.3ADR

40%Headshot %

Clutches & streaks

37%1v1 clutch win

22%1v2 clutch win

11Longest win streak

Recent Faceit resultsLLLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	94	44%	1.18	15.4
Dust2	67	51%	0.99	15.0
Inferno	40	55%	1.01	14.3
Ancient	36	56%	0.96	14.4
Anubis	28	64%	1.14	15.9
Nuke	14	57%	1.04	17.4
Vertigo	11	73%	1.16	14.8
Train	3	100%	1.19	19.3

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

35.3%Accuracy (enemy spotted)

33.4%Spray accuracy

77.9%Counter-strafing

9.4°Preaim

611msReaction time

48.0%T opening success

48.7%CT opening success

0.53Enemies flashed / flash

3.5%Flash assists

5.60HE damage / grenade

6.88Flashes / match

Recommended for you

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.

33% win rate across 6 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
mirage	7–13	0.08	19%	30 Aug →
dust2	11–13	-0.02	19%	30 Aug →
ancient	3–13	-0.03	20%	30 Aug →
mirage	13–9	0.18	18%	30 Aug →
dust2	13–8	-0.03	23%	30 Aug →
mirage	6–13	-0.06	15%	30 Aug →
ancient	16–14	0.08	20%	30 Aug →
dust2	11–13	0.00	23%	30 Aug →
mirage	9–13	-0.00	13%	30 Aug →
dust2	7–13	-0.06	26%	30 Aug →
anubis	13–4	0.04	31%	30 Aug →
ancient	13–9	0.06	22%	29 Aug →
nuke	7–13	-0.00	15%	29 Aug →
dust2	14–16	0.02	14%	29 Aug →
mirage	13–16	0.03	16%	29 Aug →
nuke	11–13	-0.01	11%	29 Aug →
dust2	9–13	-0.03	13%	28 Aug →
mirage	7–13	-0.07	15%	28 Aug →
ancient	16–14	0.00	10%	28 Aug →
nuke	7–13	-0.07	13%	28 Aug →
cache	13–8	-0.02	25%	28 Aug →
mirage	11–13	-0.02	9%	27 Aug →
cache	13–11	0.03	21%	26 Aug →
dust2	13–8	-0.01	19%	26 Aug →
mirage	13–11	0.04	14%	26 Aug →
dust2	13–11	-0.01	15%	26 Aug →
nuke	7–13	-0.03	14%	26 Aug →
mirage	13–16	-0.01	11%	26 Aug →
dust2	4–13	0.03	19%	26 Aug →
inferno	9–13	-0.03	13%	26 Aug →
inferno	5–13	-0.02	12%	24 Aug →
mirage	10–13	-0.06	15%	24 Aug →
dust2	15–15	0.01	17%	24 Aug →
mirage	16–14	-0.05	6%	24 Aug →
nuke	13–7	0.04	9%	24 Aug →
ancient	16–12	0.01	19%	24 Aug →
mirage	14–16	0.03	13%	24 Aug →
ancient	8–13	0.04	13%	24 Aug →
anubis	9–13	0.03	9%	23 Aug →
ancient	13–5	0.06	16%	23 Aug →
mirage	13–3	0.05	6%	23 Aug →
anubis	8–13	0.04	8%	23 Aug →
dust2	13–7	0.17	29%	23 Aug →
anubis	13–11	-0.04	12%	23 Aug →
ancient	14–16	-0.04	13%	23 Aug →
mirage	11–13	0.03	10%	23 Aug →
anubis	6–13	-0.04	12%	23 Aug →
inferno	10–13	-0.02	8%	23 Aug →
dust2	13–7	0.02	21%	23 Aug →
nuke	13–2	0.09	18%	22 Aug →
mirage	13–2	-0.05	20%	22 Aug →
dust2	13–8	0.03	18%	22 Aug →
dust2	13–10	0.06	15%	22 Aug →
anubis	10–13	0.02	10%	22 Aug →
mirage	13–5	0.00	16%	22 Aug →
dust2	15–15	-0.01	22%	22 Aug →
nuke	13–16	0.01	8%	22 Aug →
mirage	13–8	-0.06	7%	22 Aug →
anubis	13–3	-0.03	13%	19 Aug →
mirage	13–9	-0.09	12%	19 Aug →
dust2	9–13	-0.09	5%	18 Aug →
inferno	12–12	0.00	10%	18 Aug →
mirage	13–6	-0.03	16%	17 Aug →
dust2	2–13	0.07	24%	17 Aug →
dust2	11–13	-0.02	20%	17 Aug →
mirage	10–13	0.05	12%	17 Aug →
mirage	13–10	0.06	17%	17 Aug →
dust2	16–14	-0.03	19%	16 Aug →
mirage	13–6	0.08	5%	15 Aug →
ancient	13–11	0.04	11%	15 Aug →
dust2	16–13	0.01	15%	15 Aug →
dust2	13–6	0.05	15%	15 Aug →
dust2	11–13	0.00	15%	15 Aug →
dust2	13–8	0.04	21%	15 Aug →
mirage	13–9	0.07	10%	15 Aug →
nuke	10–13	0.02	6%	15 Aug →
dust2	16–14	-0.03	4%	14 Aug →
mirage	13–11	0.01	13%	14 Aug →
nuke	13–2	-0.07	18%	14 Aug →
dust2	7–13	-0.01	16%	14 Aug →
nuke	13–5	0.00	17%	14 Aug →
ancient	13–8	0.03	20%	14 Aug →
anubis	13–9	0.04	8%	14 Aug →
mirage	13–10	0.12	11%	14 Aug →
dust2	13–10	0.00	12%	14 Aug →
inferno	13–11	0.00	15%	14 Aug →
dust2	16–13	0.03	9%	13 Aug →
nuke	6–13	0.03	18%	12 Aug →
dust2	13–6	0.04	37%	12 Aug →
ancient	8–13	-0.02	15%	12 Aug →
train	13–3	-0.07	18%	12 Aug →
dust2	13–9	0.01	12%	12 Aug →
dust2	14–16	-0.00	14%	12 Aug →
ancient	7–13	0.12	20%	11 Aug →
anubis	13–9	0.03	19%	11 Aug →
cache	5–13	-0.04	8%	11 Aug →
dust2	9–13	-0.04	15%	11 Aug →
inferno	13–6	0.01	11%	11 Aug →
anubis	10–13	-0.03	8%	11 Aug →
ancient	13–7	0.05	20%	11 Aug →