#₵ⱤØ₦Ø$ — CS2 Stats

RO76561198881728916[U:1:921463188]Steam profile ↗✓ No bans

2,308Tracked matches68%Win rate2020Tracked since

7,994Hours in CS18Hrs last 2 wks

CSDB Rating6.5 SolidAggressive Rifler

WingmanLegendary Eagle

Ladder ranks via Leetify

Performance scores

Aim83

Positioning55

Utility46

0–100 skill scores via Leetify.

Recent form

STEADY50–43–7Last 10050%Win rateWLWWWWTTLL

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

Player DNA

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

Aim8.3

Aggression9.8

Utility4.6

Positioning5.5

Opening Duels4.4

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 device 91% playstyle similarity

Most alike: opening-fight frequency, opening-duel success.

Where you differ: lower 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

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 605ms 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

Aim8.3

Positioning5.5

Utility4.6

Mechanics7.8

Opening Duels4.4

Win Impact10.0

Composite 6.5/10 (Solid), 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 rating0.03+0.01

first ⅓ avg 0.02 → last ⅓ avg 0.03

Reaction time615ms−20ms

first ⅓ avg 635ms → last ⅓ avg 615ms

Headshot accuracy23.4%−0.8%

first ⅓ avg 24.2% → last ⅓ avg 23.4%

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

0.18Best rating — dust2 13–8

13–1Biggest win — nuke

13Longest win streak

7–5In matches decided by ≤2 rounds

9Overtime games

Map breakdown

anubisBest map · 57% over 14infernoWeakest map · 43% over 7

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	36	17–19	47%	0.03
mirage	A	20	11–9	55%	0.01
anubis	A	14	8–6	57%	0.02
ancient	B	11	5–6	45%	-0.01
nuke	A	7	4–3	57%	0.02
inferno	C	7	3–4	43%	-0.01
train	—	2	1–1	50%	0.09
overpass	—	1	0–1	0%	0.01
dogtown	—	1	0–1	0%	-0.01
grail	—	1	1–0	100%	0.06

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (43% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

300,458Lifetime kills

1.25K/D · Top 25% of tracked players

9,204Matches

47.7%Match win rate · Top 50% of tracked players

43.2%Headshot %

18.3%Shot accuracy · Top 10% of tracked players

37,055MVPs

6,867Hours (in match)

6,993Bombs planted

1,887Bombs defused

Most-used weapons

AWP114,485

AK-4774,181

M4A4 / M4A1-S29,917

Desert Eagle19,240

P2000 / USP-S12,518

SSG 087,320

Galil AR6,839

Glock-186,169

FAMAS5,550

Knife3,698

Lifetime map wins

24,740dust2

8,863inferno

3,219vertigo

3,126nuke

2,864train

254cbble

40dust

29office

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

Faceit stats

Combat

3,271Matches

51%Win rate

1.03Avg K/D

80.1ADR

49%Headshot %

Clutches & streaks

44%1v1 clutch win

20%1v2 clutch win

15Longest win streak

Recent Faceit resultsLLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	118	47%	0.95	15.3
Dust2	63	63%	1.21	17.5
Anubis	50	48%	0.96	14.4
Inferno	31	55%	0.91	14.1
Ancient	31	39%	0.90	14.8
Vertigo	22	64%	1.02	18.1
Nuke	17	24%	0.88	15.7
Cache	4	25%	1.16	20.3

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.

23.1%Headshot accuracy

37.6%Accuracy (enemy spotted)

34.3%Spray accuracy

85.2%Counter-strafing

8.1°Preaim

605msReaction time

48.0%T opening success

47.3%CT opening success

0.61Enemies flashed / flash

7.4%Flash assists

5.69HE damage / grenade

8.69Flashes / 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.

43% win rate across 7 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
nuke	13–9	0.03	20%	24 Aug →
mirage	3–13	0.07	22%	25 Jul →
anubis	16–14	-0.03	31%	23 Jul →
ancient	13–2	0.04	23%	20 Jul →
ancient	13–11	-0.00	21%	20 Jul →
inferno	13–3	0.13	16%	20 Jul →
dust2	12–12	0.05	32%	15 Jul →
mirage	12–12	-0.03	22%	15 Jul →
mirage	3–13	-0.02	5%	29 Jun →
dust2	2–13	-0.02	27%	29 Jun →
dust2	2–13	0.03	20%	26 Jun →
mirage	13–10	0.03	16%	26 Jun →
ancient	7–13	-0.02	24%	6 Jun →
mirage	13–7	0.05	27%	6 Jun →
overpass	2–6	0.01	24%	1 Jun →
dust2	13–16	0.02	15%	22 May →
mirage	3–13	-0.08	17%	13 May →
ancient	13–9	0.06	22%	7 May →
anubis	4–13	-0.06	18%	6 May →
mirage	13–11	-0.01	21%	21 Apr →
anubis	13–9	0.13	33%	3 Apr →
nuke	13–1	0.05	12%	3 Apr →
anubis	13–7	0.03	10%	2 Apr →
dust2	13–9	-0.03	28%	31 Mar →
mirage	13–7	0.03	38%	31 Mar →
nuke	16–13	-0.01	22%	28 Mar →
dust2	16–13	0.00	22%	25 Mar →
dust2	13–8	0.18	38%	25 Mar →
mirage	13–7	0.07	28%	22 Mar →
dust2	13–2	0.07	31%	22 Mar →
dust2	13–7	0.04	34%	22 Mar →
dust2	13–11	0.06	21%	17 Mar →
dust2	12–12	0.13	33%	27 Feb →
dust2	13–7	0.11	29%	27 Jan →
mirage	8–13	-0.09	21%	1 Jan →
train	13–6	0.10	41%	18 Dec →
mirage	13–5	0.07	15%	19 Nov →
nuke	8–13	0.01	26%	4 Nov →
mirage	10–13	-0.07	26%	1 Nov →
ancient	3–13	-0.05	20%	1 Nov →
inferno	13–7	0.02	29%	1 Nov →
ancient	13–9	0.01	26%	1 Nov →
dust2	9–13	-0.01	20%	31 Oct →
anubis	13–2	0.03	17%	31 Oct →
anubis	13–9	0.08	25%	30 Oct →
dust2	8–13	0.03	32%	13 Oct →
dust2	7–13	0.05	27%	6 Oct →
mirage	12–12	0.06	28%	6 Oct →
dust2	11–13	0.08	38%	6 Oct →
dust2	7–13	-0.07	28%	4 Sept →
ancient	14–16	-0.02	23%	4 Sept →
dogtown	8–8	-0.01	19%	2 Sept →
dust2	6–13	0.01	20%	13 Aug →
mirage	19–16	0.02	24%	28 Jul →
dust2	3–13	-0.05	50%	27 Jul →
inferno	10–13	-0.05	19%	26 Jul →
dust2	13–8	-0.05	14%	26 Jul →
mirage	13–9	0.01	31%	22 Jul →
dust2	13–7	0.04	27%	22 Jul →
dust2	13–6	-0.10	18%	22 Jul →
grail	13–8	0.06	25%	2 Jul →
anubis	6–13	-0.04	24%	25 Jun →
inferno	4–10	-0.22	0%	30 Apr →
anubis	4–13	-0.05	23%	27 Apr →
anubis	13–11	-0.01	28%	19 Apr →
dust2	4–13	0.04	24%	17 Apr →
dust2	13–8	0.05	15%	17 Apr →
dust2	13–10	0.06	19%	12 Apr →
nuke	8–13	-0.03	16%	27 Mar →
anubis	10–13	0.05	16%	27 Mar →
inferno	13–11	0.02	18%	24 Mar →
mirage	13–6	0.11	24%	24 Mar →
ancient	3–13	0.07	18%	24 Mar →
dust2	13–8	0.06	17%	24 Mar →
anubis	16–13	0.04	22%	21 Mar →
ancient	0–8	-0.24	0%	5 Mar →
dust2	10–13	-0.02	27%	5 Mar →
inferno	8–13	0.07	28%	4 Mar →
dust2	13–9	0.03	35%	2 Mar →
ancient	13–7	0.03	41%	2 Mar →
nuke	13–10	0.05	16%	27 Feb →
dust2	13–10	0.05	41%	27 Feb →
anubis	10–13	0.03	23%	27 Feb →
dust2	11–13	-0.03	25%	23 Feb →
dust2	6–13	-0.08	21%	20 Feb →
dust2	13–3	0.09	28%	19 Feb →
mirage	9–13	-0.02	20%	19 Feb →
train	15–15	0.07	16%	19 Feb →
inferno	1–13	-0.06	29%	19 Feb →
nuke	11–13	0.03	26%	19 Feb →
mirage	13–5	0.05	30%	19 Feb →
mirage	13–5	0.10	28%	16 Feb →
anubis	13–6	0.04	17%	15 Feb →
dust2	8–13	0.09	31%	5 Feb →
dust2	15–15	0.10	24%	2 Feb →
dust2	13–11	-0.00	16%	30 Jan →
ancient	2–13	-0.03	45%	30 Jan →
dust2	3–13	-0.04	27%	30 Jan →
mirage	4–13	-0.07	33%	29 Jan →
anubis	11–13	-0.02	21%	29 Jan →