rozen — CS2 Stats

SE76561198123072778[U:1:162807050]Steam profile ↗

1,722Tracked matches57%Win rate2020Tracked since

9,371Hours in CS22Hrs last 2 wks

CSDB Rating8.1 StrongEntry Fragger

Premier CS Rating26,283Top 25% of 819 CSDB-tracked playersRed band · top ~2.4% of ranked players (population est.)

CSDB Leaderboard#988 of 9771 tracked

FaceitLevel 10 · 3,092 ELOTop 12.4% of ranked FACEIT players

WingmanThe Global Elite

Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 10 among CSDB-tracked players (n=218), 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	63.0%	52.8%
Shot accuracy	17.8%	13.7%
Kill/death ratio	1.10	1.08
Match win rate	54.5%	49.2%

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Performance scores

Aim93

Positioning69

Utility65

0–100 skill scores via Leetify.

Recent form

STEADY56–43–1Last 10056%Win rateLWWLWWLLWW

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

Player DNA

Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.

Aim9.3

Aggression10.0

Utility6.5

Positioning6.9

Opening Duels7.1

Clutch3.0

Sharp aimerStrong 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.

Your pro match

Plays most like s1mple 97% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

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

Strengths

Aim. Aim score of 93 — the mechanical foundation is a clear strength.

CT openings. 66% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 66% on CT to 51% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim9.3

Positioning6.9

Utility6.5

Mechanics7.9

Opening Duels7.1

Win Impact7.2

Composite 8.1/10 (Strong), 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 rating0.05+0.02

first ⅓ avg 0.03 → last ⅓ avg 0.05

Reaction time505ms−41ms

first ⅓ avg 546ms → last ⅓ avg 505ms

Headshot accuracy22.5%−0.4%

first ⅓ avg 22.9% → last ⅓ avg 22.5%

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

0.22Best rating — dust2 13–2

13–0Biggest win — dust2

6Longest win streak

6–7In matches decided by ≤2 rounds

8Overtime games

Map breakdown

cacheBest map · 78% over 18anubisWeakest map · 38% over 8

Map	Grade	Played	Record	Win rate	Avg rating
mirage	A	23	13–10	57%	0.05
cache	S	18	14–4	78%	0.06
dust2	A	16	9–7	56%	0.05
ancient	S	12	8–4	67%	0.03
inferno	C	10	4–6	40%	0.01
anubis	C	8	3–5	38%	0.05
nuke	A	5	3–2	60%	0.02
vertigo	—	3	2–1	67%	0.07
overpass	—	3	0–3	0%	0.04
train	—	2	0–2	0%	0.04

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

590,651Lifetime kills

1.10K/D · Top 50% of Level 10 players

13,936Matches

54.5%Match win rate · Top 25% of Level 10 players

63.0%Headshot % · Top 25% of Level 10 players

17.8%Shot accuracy · Top 25% of Level 10 players

70,457MVPs

14,348Hours (in match)

19,094Bombs planted

11,607Bombs defused

Most-used weapons

AK-47288,173

M4A4 / M4A1-S92,401

P2000 / USP-S49,233

AWP48,817

Desert Eagle44,041

Glock-1817,104

P2506,939

Knife6,866

SG 5534,167

Galil AR3,973

Lifetime map wins

26,026inferno

22,068dust2

13,641train

9,237nuke

6,714cbble

6,246vertigo

175lake

129office

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

Faceit stats

Combat

3,037Matches

59%Win rate

1.30Avg K/D

86.7ADR

54%Headshot %

Clutches & streaks

35%1v1 clutch win

27%1v2 clutch win

14Longest win streak

Recent Faceit resultsLWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	124	60%	1.30	17.6
Anubis	77	51%	1.37	18.4
Nuke	58	47%	1.22	18.2
Inferno	54	61%	1.43	17.4
Overpass	50	60%	1.44	18.3
Ancient	49	39%	1.33	17.8
Dust2	44	64%	1.57	18.6
Vertigo	16	56%	1.42	16.9

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.

23.5%Headshot accuracy

39.1%Accuracy (enemy spotted)

43.5%Spray accuracy

85.7%Counter-strafing

8.5°Preaim

497msReaction time

51.0%T opening success

66.1%CT opening success

0.57Enemies flashed / flash

8.8%Flash assists

11.33HE damage / grenade

10.81Flashes / match

Recommended for you

Spend your practice time on Anubis

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 8 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
mirage	5–13	0.02	16%	20 Aug →
cache	13–6	0.09	28%	20 Aug →
anubis	13–10	0.02	23%	19 Aug →
nuke	11–13	0.01	24%	16 Aug →
mirage	16–14	0.03	16%	16 Aug →
cache	13–6	0.02	24%	16 Aug →
anubis	7–13	0.02	20%	13 Aug →
dust2	8–13	0.10	31%	13 Aug →
nuke	13–8	0.04	21%	11 Aug →
mirage	13–1	0.18	31%	11 Aug →
vertigo	13–7	0.11	14%	8 Aug →
ancient	11–13	0.03	21%	7 Aug →
inferno	7–13	0.00	22%	7 Aug →
dust2	13–0	0.02	29%	4 Aug →
nuke	11–13	0.01	26%	22 Jul →
mirage	8–13	0.04	23%	22 Jul →
ancient	13–10	0.06	17%	22 Jul →
anubis	6–13	0.01	21%	21 Jul →
mirage	13–5	0.05	29%	21 Jul →
vertigo	13–10	-0.02	17%	19 Jul →
cache	13–3	0.07	19%	19 Jul →
dust2	11–13	-0.00	25%	19 Jul →
cache	11–13	0.05	33%	18 Jul →
mirage	13–3	0.14	26%	18 Jul →
inferno	13–11	0.05	21%	18 Jul →
anubis	11–1	0.11	39%	18 Jul →
dust2	14–16	0.06	26%	18 Jul →
mirage	13–10	0.05	24%	18 Jul →
cache	13–4	0.10	20%	18 Jul →
train	12–16	0.05	26%	18 Jul →
dust2	1–13	-0.03	0%	18 Jul →
ancient	13–2	0.13	29%	15 Jul →
dust2	13–1	-0.01	0%	15 Jul →
cache	13–0	-0.01	33%	15 Jul →
dust2	13–7	0.13	31%	15 Jul →
inferno	13–8	0.11	29%	14 Jul →
anubis	2–13	0.04	37%	14 Jul →
inferno	15–15	0.07	30%	14 Jul →
cache	9–13	0.05	38%	14 Jul →
cache	2–13	-0.02	26%	14 Jul →
anubis	13–0	0.12	37%	14 Jul →
dust2	13–0	0.14	32%	14 Jul →
mirage	13–8	0.10	20%	13 Jul →
mirage	6–13	0.05	37%	13 Jul →
ancient	13–6	0.01	16%	13 Jul →
cache	13–8	-0.01	25%	11 Jul →
dust2	13–6	0.08	25%	6 Jul →
dust2	11–13	0.07	22%	6 Jul →
anubis	9–13	0.00	21%	6 Jul →
mirage	13–10	0.07	20%	3 Jul →
ancient	13–5	-0.05	17%	2 Jul →
mirage	2–13	-0.07	18%	1 Jul →
dust2	13–8	0.04	20%	1 Jul →
inferno	8–13	-0.07	17%	15 Jun →
nuke	16–14	0.01	18%	6 Jun →
overpass	7–13	-0.00	22%	6 Jun →
cache	13–11	0.06	31%	5 Jun →
cache	13–2	0.12	39%	2 Jun →
cache	8–13	0.06	21%	26 May →
cache	13–1	0.05	22%	26 May →
cache	13–8	0.10	20%	25 May →
cache	13–1	0.06	18%	23 May →
cache	13–7	0.03	24%	21 May →
cache	13–4	0.04	37%	21 May →
cache	13–5	0.14	31%	21 May →
ancient	0–8	0.02	14%	11 May →
dust2	13–2	0.22	30%	10 May →
ancient	13–1	0.05	17%	10 May →
mirage	8–13	0.09	28%	9 May →
mirage	13–8	-0.06	21%	18 Apr →
mirage	8–13	0.08	16%	13 Apr →
overpass	0–13	-0.01	38%	12 Apr →
mirage	3–13	0.05	34%	12 Apr →
dust2	4–10	0.01	28%	3 Apr →
overpass	10–13	0.12	34%	3 Apr →
mirage	13–4	0.00	29%	3 Apr →
ancient	13–5	0.11	19%	3 Apr →
dust2	2–13	-0.09	31%	3 Apr →
ancient	6–4	-0.08	23%	3 Apr →
mirage	13–16	0.10	23%	2 Apr →
inferno	7–13	-0.04	24%	25 Mar →
nuke	13–3	0.04	10%	24 Mar →
inferno	13–11	0.01	27%	23 Mar →
dust2	13–10	0.01	23%	23 Mar →
inferno	0–13	-0.02	19%	20 Mar →
train	10–13	0.03	24%	20 Mar →
vertigo	13–16	0.12	26%	20 Mar →
anubis	9–13	0.07	20%	20 Mar →
ancient	6–13	0.04	23%	16 Mar →
dust2	13–1	0.11	37%	16 Mar →
inferno	5–13	0.04	17%	16 Mar →
inferno	13–10	-0.01	23%	16 Mar →
mirage	16–13	-0.02	27%	16 Mar →
ancient	0–13	0.01	20%	16 Mar →
mirage	13–4	0.04	20%	13 Mar →
mirage	13–3	0.11	11%	13 Mar →
mirage	13–6	0.01	21%	12 Mar →
mirage	10–13	0.00	13%	8 Mar →
ancient	13–10	0.02	17%	7 Mar →
mirage	4–13	0.08	12%	7 Mar →