MuchSkills — CS2 Stats

US76561198200645211[U:1:240379483]Steam profile ↗✓ No bans

815Tracked matches33%Win rate2020Tracked since

691Hours in CS

CSDB Rating3.6 LearningClutch Specialist

WingmanMaster Guardian II

Ladder ranks via Leetify

Performance scores

Aim50

Positioning41

Utility27

0–100 skill scores via Leetify.

Recent form

STEADY45–50–5Last 10045%Win rateLWLWWTLWLW

Last 10 vs previous 10: +20pp win rate · +0.02 avg rating

Player DNA

Primary style: Clutch Specialist — Late-round 1vX conversion well above par.

Aim5.0

Aggression4.4

Utility2.7

Positioning4.1

Opening Duels0.7

Clutch10.0

Reliable in 1v1s

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 NiKo 77% playstyle similarity

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

Where you differ: lower utility contribution; 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. 670ms 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

Aim5.0

Positioning4.1

Utility2.7

Mechanics5.7

Opening Duels0.7

Win Impact0.0

Composite 3.6/10 (Learning), 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 rating-0.02−0.04

first ⅓ avg 0.02 → last ⅓ avg -0.02

Reaction time686ms−11ms

first ⅓ avg 697ms → last ⅓ avg 686ms

Headshot accuracy16.0%−3.5%

first ⅓ avg 19.4% → last ⅓ avg 16.0%

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

0.26Best rating — office 13–4

13–1Biggest win — ancient

4Longest win streak

4–5In matches decided by ≤2 rounds

1Overtime games

Map breakdown

vertigoBest map · 60% over 10anubisWeakest map · 18% over 11

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	30	16–14	53%	0.00
cache	D	12	4–8	33%	-0.03
mirage	B	11	5–6	45%	-0.03
anubis	D	11	2–9	18%	-0.02
vertigo	A	10	6–4	60%	0.01
ancient	A	7	4–3	57%	-0.02
train	A	5	3–2	60%	0.01
overpass	A	5	3–2	60%	-0.01
office	C	5	2–3	40%	0.04
inferno	—	3	0–3	0%	-0.03
nuke	—	1	0–1	0%	-0.04

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (18% over 11). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

43,252Lifetime kills

1.18K/D · Top 25% of tracked players

2,087Matches

35.2%Match win rate

48.0%Headshot % · Top 50% of tracked players

7.9%Shot accuracy

3,019MVPs

691Hours (in match)

1,156Bombs planted

294Bombs defused

Most-used weapons

AK-4720,805

M4A4 / M4A1-S10,088

AWP2,483

P2000 / USP-S1,440

Desert Eagle1,173

Glock-181,046

P90953

MP9639

MP7628

Galil AR624

Lifetime map wins

5,463dust2

1,333inferno

1,189nuke

1,059vertigo

445train

184office

44cbble

15ar_shoots

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

Faceit stats

Combat

11Matches

73%Win rate

1.00Avg K/D

81.2ADR

43%Headshot %

Clutches & streaks

100%1v1 clutch win

0%1v2 clutch win

7Longest win streak

Recent Faceit resultsWWWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	4	50%	0.70	11.0
Mirage	3	100%	1.26	16.7
Nuke	1	100%	0.90	18.0
Overpass	1	100%	0.72	13.0
Anubis	1	0%	0.72	13.0
Ancient	1	100%	2.12	17.0

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.

16.1%Headshot accuracy

33.7%Accuracy (enemy spotted)

32.6%Spray accuracy

75.6%Counter-strafing

10.3°Preaim

670msReaction time

30.4%T opening success

35.0%CT opening success

0.40Enemies flashed / flash

3.9%Flash assists

1.73HE damage / grenade

9.16Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.3956 — below the 0.5 mark we flag
Grenade Lineups →
Advanced Mechanics
You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.
T opening duels 30.3936% — below the 40% mark we flag

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.

18% win rate across 11 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
ancient	7–13	-0.02	10%	27 Aug →
cache	13–4	0.05	16%	27 Aug →
vertigo	7–13	0.00	15%	27 Aug →
dust2	8–3	0.02	14%	27 Aug →
train	13–8	0.05	12%	21 Aug →
cache	12–12	0.00	9%	21 Aug →
inferno	3–13	-0.06	10%	21 Aug →
vertigo	13–4	-0.01	17%	21 Aug →
nuke	7–13	-0.04	20%	14 Aug →
mirage	13–4	-0.04	25%	14 Aug →
cache	7–13	-0.03	10%	13 Aug →
ancient	8–13	-0.02	23%	7 Aug →
ancient	13–1	0.05	30%	6 Aug →
mirage	12–12	-0.02	20%	6 Aug →
vertigo	13–8	0.01	19%	31 Jul →
cache	10–13	-0.00	26%	30 Jul →
dust2	13–11	-0.07	0%	29 Jul →
anubis	10–13	-0.03	15%	23 Jul →
anubis	7–13	-0.03	17%	23 Jul →
cache	8–13	-0.08	10%	22 Jul →
dust2	12–12	0.01	29%	22 Jul →
dust2	6–13	-0.00	9%	20 May →
cache	10–13	-0.00	17%	11 May →
overpass	9–13	-0.02	12%	3 May →
dust2	3–7	-0.01	0%	1 May →
cache	1–13	-0.08	26%	1 May →
cache	3–13	-0.09	17%	1 May →
cache	2–13	-0.06	4%	1 May →
cache	13–4	-0.06	16%	30 Apr →
mirage	4–13	-0.09	25%	30 Apr →
dust2	13–9	-0.03	24%	30 Apr →
cache	13–8	0.02	12%	29 Apr →
dust2	7–13	-0.05	16%	29 Apr →
cache	13–5	0.00	23%	29 Apr →
train	6–0	-0.10	5%	24 Apr →
ancient	13–8	-0.08	18%	22 Apr →
train	12–12	0.01	0%	22 Apr →
inferno	10–13	-0.01	25%	22 Apr →
mirage	9–13	-0.06	8%	21 Apr →
dust2	13–11	0.09	22%	21 Apr →
dust2	4–10	-0.14	0%	15 Apr →
vertigo	6–13	-0.02	13%	15 Apr →
office	9–13	-0.03	18%	25 Mar →
office	13–9	-0.03	9%	22 Mar →
mirage	13–10	0.01	21%	22 Mar →
dust2	10–13	-0.03	16%	21 Feb →
anubis	8–13	-0.02	24%	12 Feb →
vertigo	6–3	0.02	31%	12 Feb →
vertigo	13–4	0.02	15%	12 Feb →
vertigo	4–13	0.02	19%	11 Feb →
dust2	13–5	0.04	13%	10 Feb →
anubis	4–13	0.02	17%	10 Feb →
anubis	6–13	-0.02	15%	10 Feb →
anubis	11–13	-0.04	15%	8 Feb →
anubis	5–13	-0.10	0%	8 Feb →
ancient	13–6	-0.02	9%	29 Jan →
dust2	13–10	-0.02	7%	29 Jan →
overpass	10–13	-0.07	15%	29 Jan →
dust2	1–8	-0.02	11%	28 Jan →
dust2	8–13	-0.07	6%	28 Jan →
ancient	11–13	-0.03	15%	24 Jan →
mirage	11–13	-0.02	18%	23 Jan →
mirage	13–2	-0.06	2%	22 Jan →
dust2	6–13	0.03	13%	18 Jan →
overpass	13–10	0.03	23%	17 Jan →
overpass	13–11	-0.03	13%	17 Jan →
anubis	6–13	-0.02	27%	13 Jan →
dust2	13–5	0.06	25%	13 Jan →
dust2	13–7	0.03	23%	11 Jan →
dust2	9–13	-0.02	24%	3 Jan →
ancient	4–0	-0.04	0%	3 Jan →
mirage	13–4	0.01	13%	3 Jan →
train	12–12	0.03	32%	3 Jan →
mirage	13–7	0.03	16%	27 Dec →
dust2	13–5	0.01	13%	27 Dec →
dust2	4–13	-0.00	24%	26 Dec →
dust2	13–10	0.04	24%	26 Dec →
vertigo	13–6	0.00	24%	23 Dec →
vertigo	13–10	0.01	22%	23 Dec →
vertigo	8–13	0.04	19%	21 Dec →
anubis	13–2	0.02	8%	11 Dec →
dust2	3–5	0.03	40%	10 Dec →
anubis	1–13	-0.01	16%	10 Dec →
anubis	13–6	0.00	10%	10 Dec →
dust2	9–12	-0.02	20%	10 Dec →
mirage	1–13	-0.06	26%	10 Dec →
dust2	13–4	0.05	25%	9 Dec →
dust2	13–2	0.08	27%	8 Dec →
dust2	0–13	-0.05	7%	7 Dec →
dust2	8–5	0.12	19%	6 Dec →
dust2	8–13	-0.03	18%	30 Nov →
office	13–4	0.26	21%	30 Nov →
office	11–13	0.00	24%	27 Nov →
office	6–13	-0.02	16%	27 Nov →
mirage	9–13	-0.05	12%	20 Nov →
dust2	13–5	-0.05	28%	12 Nov →
train	13–5	0.04	16%	12 Nov →
dust2	16–14	0.05	19%	8 Nov →
overpass	13–10	0.04	12%	8 Nov →
inferno	4–13	-0.01	18%	8 Nov →