rulleskøjte — CS2 Stats

DK76561198060770157[U:1:100504429]Steam profile ↗VAC banned

975Tracked matches63%Win rate2020Tracked since

2,051Hours in CS1Hrs last 2 wks

CSDB Rating6.9 SolidHybrid Rifler

WingmanThe Global Elite

Ladder ranks via Leetify

Performance scores

Aim67

Positioning76

Utility72

0–100 skill scores via Leetify.

Recent form

STEADY57–39–4Last 10057%Win rateLLLWLWWWWW

Last 10 vs previous 10: +0pp win rate · -0.01 avg rating

Player DNA

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

Aim6.7

Aggression10.0

Utility7.2

Positioning7.6

Opening Duels5.4

Clutch3.6

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.

Your pro match

Plays most like s1mple 89% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: lower opening-duel success; 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

Strengths

Flashes. 0.78 enemies blinded per flash — utility that consistently lands.

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

Aim6.7

Positioning7.6

Utility7.2

Mechanics5.2

Opening Duels5.4

Win Impact9.4

Composite 6.9/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.04+0.01

first ⅓ avg 0.03 → last ⅓ avg 0.04

Reaction time521ms−34ms

first ⅓ avg 555ms → last ⅓ avg 521ms

Headshot accuracy16.4%−0.5%

first ⅓ avg 16.9% → last ⅓ avg 16.4%

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

0.25Best rating — inferno 9–2

13–2Biggest win — inferno

6Longest win streak

L3Current streak

10–14In matches decided by ≤2 rounds

7Overtime games

Map breakdown

trainBest map · 75% over 8anubisWeakest map · 44% over 9

Map	Grade	Played	Record	Win rate	Avg rating
inferno	A	36	21–15	58%	0.07
dust2	B	20	10–10	50%	0.02
nuke	B	12	6–6	50%	0.01
anubis	C	9	4–5	44%	0.01
train	S	8	6–2	75%	0.02
mirage	B	6	3–3	50%	0.03
overpass	—	4	3–1	75%	0.01
cache	—	3	3–0	100%	0.04
ancient	—	2	1–1	50%	-0.00

Across the last 100 tracked matches.

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

Lifetime stats

65,937Lifetime kills

1.20K/D · Top 25% of tracked players

2,538Matches

52.0%Match win rate · Top 25% of tracked players

44.1%Headshot %

13.6%Shot accuracy · Top 50% of tracked players

8,007MVPs

1,184Hours (in match)

3,055Bombs planted

833Bombs defused

Most-used weapons

AK-4721,667

AWP10,425

M4A4 / M4A1-S9,979

Desert Eagle4,586

P2000 / USP-S3,572

P2502,446

Glock-181,825

Five-SeveN1,296

Tec-91,216

P901,080

Lifetime map wins

9,566inferno

5,259dust2

2,368nuke

613train

379vertigo

306cbble

33lake

33safehouse

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

Faceit stats

Combat

496Matches

55%Win rate

1.43Avg K/D

80.2ADR

42%Headshot %

Clutches & streaks

38%1v1 clutch win

26%1v2 clutch win

9Longest win streak

Recent Faceit resultsLWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	97	55%	1.43	17.6
Dust2	65	52%	1.35	17.7
Mirage	64	52%	1.42	17.7
Anubis	64	61%	1.38	16.7
Nuke	45	51%	1.33	16.1
Ancient	34	53%	1.44	17.8
Train	28	46%	1.24	17.8
Vertigo	17	65%	1.51	15.3

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.

15.9%Headshot accuracy

34.2%Accuracy (enemy spotted)

36.6%Spray accuracy

73.3%Counter-strafing

9.6°Preaim

525msReaction time

44.6%T opening success

58.9%CT opening success

0.78Enemies flashed / flash

11.4%Flash assists

9.11HE damage / grenade

11.20Flashes / 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.

44% win rate across 9 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
dust2	9–13	-0.01	7%	16 Aug →
anubis	7–13	-0.10	16%	16 Aug →
inferno	2–13	-0.04	19%	15 Aug →
nuke	13–11	-0.04	14%	15 Aug →
dust2	11–13	0.02	15%	15 Aug →
cache	13–6	0.01	17%	7 Aug →
inferno	13–11	0.03	13%	1 Aug →
inferno	13–3	0.12	14%	17 Jul →
cache	13–7	0.03	4%	17 Jul →
inferno	13–8	0.09	15%	26 Jun →
dust2	13–10	0.06	14%	26 Jun →
nuke	14–16	0.05	19%	26 Jun →
mirage	13–11	0.03	18%	26 Jun →
anubis	13–6	0.01	9%	26 Jun →
anubis	13–11	-0.01	21%	21 Jun →
dust2	6–13	0.02	14%	21 Jun →
dust2	13–5	0.05	18%	21 Jun →
dust2	11–13	0.00	22%	13 Jun →
inferno	13–4	0.10	16%	13 Jun →
anubis	6–13	-0.05	11%	13 Jun →
inferno	11–13	0.09	21%	12 Jun →
nuke	13–10	0.03	20%	8 Jun →
inferno	16–12	0.00	16%	8 May →
cache	13–4	0.09	25%	8 May →
inferno	13–4	0.08	17%	8 May →
nuke	7–13	-0.01	15%	26 Apr →
inferno	13–3	0.12	14%	26 Apr →
nuke	13–5	0.06	21%	26 Apr →
anubis	10–13	0.01	13%	26 Apr →
inferno	13–7	0.02	17%	26 Apr →
nuke	13–10	0.03	26%	25 Apr →
inferno	8–8	0.17	26%	15 Apr →
inferno	9–2	0.25	14%	15 Apr →
inferno	9–4	0.16	15%	15 Apr →
inferno	3–9	0.03	18%	15 Apr →
inferno	8–8	0.13	14%	15 Apr →
anubis	13–3	0.06	28%	13 Apr →
inferno	13–2	0.23	18%	11 Apr →
inferno	13–2	0.08	21%	11 Apr →
dust2	13–10	0.03	17%	11 Apr →
dust2	13–5	0.05	21%	11 Apr →
nuke	11–13	0.04	17%	28 Mar →
anubis	4–13	0.03	31%	15 Mar →
inferno	13–10	0.01	24%	15 Mar →
anubis	13–3	0.06	19%	24 Jan →
anubis	11–13	0.07	8%	24 Jan →
inferno	8–8	0.03	61%	30 Dec →
inferno	9–1	0.11	27%	30 Dec →
inferno	9–7	0.15	39%	29 Dec →
inferno	11–13	0.00	13%	29 Dec →
mirage	5–13	0.01	18%	25 Dec →
dust2	16–12	-0.01	12%	25 Dec →
ancient	13–6	0.02	26%	24 Dec →
dust2	10–13	-0.00	13%	24 Dec →
dust2	5–13	-0.06	29%	24 Dec →
train	13–10	-0.03	13%	23 Dec →
overpass	13–10	0.04	15%	22 Dec →
nuke	11–13	0.04	20%	22 Dec →
overpass	13–6	-0.02	17%	22 Dec →
dust2	13–9	0.04	15%	22 Dec →
dust2	13–11	0.01	17%	21 Dec →
train	13–3	0.02	40%	21 Dec →
dust2	9–13	0.00	11%	21 Dec →
ancient	11–13	-0.02	14%	20 Dec →
dust2	10–13	-0.02	19%	20 Dec →
overpass	16–14	0.01	22%	20 Dec →
nuke	9–13	-0.03	16%	20 Dec →
inferno	10–13	-0.01	14%	19 Dec →
dust2	13–4	0.14	23%	19 Dec →
train	9–13	-0.03	15%	19 Dec →
nuke	13–11	-0.08	10%	19 Dec →
mirage	4–13	-0.02	24%	19 Dec →
inferno	5–13	-0.01	18%	19 Dec →
inferno	17–19	-0.03	13%	19 Dec →
mirage	13–9	0.11	14%	19 Dec →
mirage	11–13	-0.00	11%	16 Dec →
inferno	13–9	-0.00	22%	16 Dec →
nuke	13–9	-0.01	5%	16 Dec →
train	6–13	-0.02	17%	16 Dec →
dust2	13–11	0.01	15%	15 Dec →
train	13–9	0.01	11%	15 Dec →
inferno	13–16	0.01	21%	15 Dec →
dust2	13–6	0.06	19%	15 Dec →
train	13–11	0.04	22%	15 Dec →
inferno	9–6	0.13	12%	14 Dec →
inferno	8–8	0.05	26%	14 Dec →
inferno	9–2	0.12	27%	14 Dec →
inferno	9–3	0.25	11%	14 Dec →
overpass	11–13	0.03	16%	12 Dec →
nuke	8–13	0.07	21%	12 Dec →
dust2	7–13	0.05	17%	12 Dec →
dust2	2–13	-0.06	14%	11 Dec →
inferno	10–13	0.00	12%	11 Dec →
inferno	13–6	0.06	19%	11 Dec →
inferno	11–13	-0.06	13%	11 Dec →
train	16–13	0.07	24%	11 Dec →
inferno	11–13	0.05	20%	10 Dec →
train	13–4	0.08	13%	10 Dec →
inferno	13–7	0.05	17%	10 Dec →
mirage	13–8	0.03	23%	10 Dec →