carbonated asparagus — CS2 Stats

76561198017225879[U:1:56960151]Steam profile ↗✓ No bans

756Tracked matches37%Win rate2022Tracked since

1,683Hours in CS4Hrs last 2 wks

CSDB Rating5.9 SolidHybrid Rifler

Ladder ranks via Leetify

Performance scores

Aim69

Positioning62

Utility61

0–100 skill scores via Leetify.

Recent form

STEADY47–45–8Last 10047%Win rateLWWWLLTWLW

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

Player DNA

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

Aim6.9

Aggression10.0

Utility6.1

Positioning6.2

Opening Duels4.3

Clutch0.0

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 92% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: 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. 614ms 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

Aim6.9

Positioning6.2

Utility6.1

Mechanics7.6

Opening Duels4.3

Win Impact0.7

Composite 5.9/10 (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 rating0.01−0.03

first ⅓ avg 0.04 → last ⅓ avg 0.01

Reaction time609ms−26ms

first ⅓ avg 635ms → last ⅓ avg 609ms

Headshot accuracy14.8%−0.3%

first ⅓ avg 15.1% → last ⅓ avg 14.8%

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 — ancient 13–5

13–0Biggest win — ancient

6Longest win streak

7–4In matches decided by ≤2 rounds

1Overtime games

Map breakdown

ancientBest map · 78% over 9nukeWeakest map · 31% over 13

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	18	8–10	44%	0.01
cache	C	15	6–9	40%	0.04
mirage	C	14	6–8	43%	0.01
nuke	D	13	4–9	31%	-0.00
inferno	B	13	7–6	54%	0.01
ancient	S	9	7–2	78%	0.04
train	S	7	5–2	71%	0.03
anubis	C	5	2–3	40%	0.02
overpass	—	4	2–2	50%	0.02
office	—	2	0–2	0%	-0.04

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (31% over 13). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

62,032Lifetime kills

1.16K/D · Top 50% of tracked players

2,669Matches

46.6%Match win rate · Top 50% of tracked players

41.7%Headshot %

14.9%Shot accuracy · Top 50% of tracked players

7,417MVPs

1,592Hours (in match)

1,522Bombs planted

811Bombs defused

Most-used weapons

AK-4720,224

M4A4 / M4A1-S10,821

AWP8,518

P2000 / USP-S3,608

Desert Eagle2,348

Glock-182,200

P2501,681

SSG 081,125

Tec-91,059

P90978

Lifetime map wins

5,043dust2

2,512nuke

2,194inferno

684office

611train

219vertigo

212italy

203assault

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

Faceit stats

Combat

3Matches

67%Win rate

1.21Avg K/D

88.3ADR

46%Headshot %

Clutches & streaks

0%1v1 clutch win

100%1v2 clutch win

1Longest win streak

Recent Faceit resultsLLWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	1	100%	1.17	14.0
Train	1	100%	0.87	13.0
Anubis	1	0%	1.60	24.0

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.

14.6%Headshot accuracy

37.0%Accuracy (enemy spotted)

39.2%Spray accuracy

84.1%Counter-strafing

10.5°Preaim

614msReaction time

42.6%T opening success

51.7%CT opening success

0.62Enemies flashed / flash

6.4%Flash assists

10.07HE damage / grenade

11.75Flashes / 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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 14.6065% — below the 15% mark we flag
Aim Training →

Spend your practice time on Nuke

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

31% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
nuke	7–13	0.00	6%	28 Aug →
dust2	13–8	0.02	11%	26 Aug →
mirage	13–10	0.00	21%	25 Aug →
ancient	13–3	0.06	20%	25 Aug →
dust2	10–13	-0.01	20%	25 Aug →
mirage	9–13	0.02	22%	15 Aug →
ancient	12–12	-0.05	10%	15 Aug →
train	10–0	0.05	17%	15 Aug →
cache	10–13	0.11	14%	25 Jul →
dust2	13–10	0.09	20%	25 Jul →
nuke	12–12	0.01	14%	11 Jul →
office	9–13	0.01	18%	10 Jul →
train	9–13	-0.02	15%	10 Jul →
inferno	13–11	0.02	21%	24 Jun →
train	13–8	-0.03	6%	24 Jun →
nuke	12–12	0.02	11%	10 Jun →
inferno	13–6	0.03	14%	10 Jun →
mirage	13–4	0.09	19%	10 Jun →
office	1–13	-0.08	13%	10 Jun →
anubis	8–13	-0.00	17%	9 Jun →
dust2	9–13	-0.05	11%	9 Jun →
nuke	9–13	-0.02	15%	8 Jun →
inferno	8–13	-0.03	18%	8 Jun →
nuke	14–16	-0.03	7%	7 Jun →
cache	9–13	0.06	15%	7 Jun →
mirage	10–13	-0.07	13%	7 Jun →
dust2	7–13	-0.04	9%	7 Jun →
dust2	10–13	-0.01	16%	7 Jun →
mirage	9–13	0.07	16%	7 Jun →
inferno	13–8	0.01	12%	31 May →
anubis	2–13	-0.09	11%	31 May →
anubis	13–7	0.11	13%	31 May →
ancient	13–11	0.01	24%	25 May →
cache	8–5	-0.01	15%	25 May →
nuke	11–13	-0.01	17%	24 May →
mirage	13–5	-0.01	21%	24 May →
ancient	13–7	-0.01	9%	24 May →
nuke	13–6	0.02	11%	24 May →
ancient	13–0	0.04	12%	24 May →
dust2	13–5	0.14	17%	24 May →
nuke	9–1	0.04	9%	23 May →
train	10–13	-0.02	24%	23 May →
mirage	7–13	-0.07	17%	23 May →
inferno	13–10	0.03	18%	22 May →
cache	13–6	0.03	13%	22 May →
overpass	11–13	0.01	14%	22 May →
mirage	8–5	0.09	16%	21 May →
inferno	13–6	-0.04	6%	20 May →
dust2	13–11	-0.02	14%	20 May →
overpass	13–6	-0.05	10%	20 May →
inferno	10–13	-0.01	11%	19 May →
dust2	13–11	-0.03	10%	19 May →
mirage	10–13	-0.07	6%	12 May →
cache	4–13	-0.03	14%	12 May →
inferno	13–11	0.01	17%	11 May →
dust2	4–13	0.07	16%	11 May →
cache	13–8	0.03	19%	10 May →
cache	5–13	0.04	14%	10 May →
cache	12–12	0.00	16%	9 May →
dust2	5–13	-0.01	10%	9 May →
dust2	13–4	0.03	11%	8 May →
inferno	4–13	-0.05	13%	8 May →
mirage	8–0	0.04	20%	8 May →
cache	6–13	0.11	11%	8 May →
overpass	13–11	0.06	15%	8 May →
inferno	7–13	-0.05	40%	8 May →
dust2	5–13	-0.03	31%	7 May →
cache	10–13	0.13	10%	7 May →
dust2	13–6	0.01	12%	7 May →
ancient	13–5	0.22	22%	7 May →
nuke	11–13	-0.03	11%	5 May →
cache	8–13	-0.04	16%	5 May →
nuke	13–6	0.00	14%	3 May →
ancient	13–5	0.02	6%	3 May →
inferno	13–10	0.08	20%	3 May →
dust2	13–10	0.08	13%	3 May →
cache	10–13	-0.03	4%	2 May →
ancient	13–10	0.13	17%	1 May →
nuke	13–11	0.00	15%	1 May →
dust2	6–13	-0.00	32%	1 May →
overpass	8–13	0.07	14%	30 Apr →
mirage	7–13	-0.04	13%	30 Apr →
cache	13–8	-0.00	8%	30 Apr →
cache	13–8	0.03	12%	30 Apr →
train	13–8	0.03	12%	30 Apr →
cache	13–10	0.09	16%	29 Apr →
train	13–9	0.07	18%	26 Apr →
mirage	9–13	-0.06	12%	26 Apr →
anubis	12–12	0.03	13%	26 Apr →
dust2	12–12	-0.02	12%	25 Apr →
inferno	12–12	0.06	16%	25 Apr →
nuke	8–13	-0.01	13%	25 Apr →
mirage	13–6	0.10	21%	25 Apr →
inferno	10–13	0.07	14%	24 Apr →
mirage	10–13	0.10	24%	24 Apr →
ancient	5–13	-0.01	22%	24 Apr →
train	13–4	0.11	15%	24 Apr →
dust2	7–13	-0.00	17%	24 Apr →
nuke	12–12	0.00	22%	20 Apr →
anubis	13–10	0.02	14%	19 Apr →