Mustard4u — CS2 Stats

RO76561199114703546[U:1:1154437818]Steam profile ↗✓ No bans

1,221Tracked matches56%Win rate2021Tracked since

1,120Hours in CS6Hrs last 2 wks

CSDB Rating5.6 SolidAggressive Rifler

WingmanSupreme Master First Class

Ladder ranks via Leetify

Performance scores

Aim72

Positioning59

Utility45

0–100 skill scores via Leetify.

Recent form

HOT60–35–5Last 10060%Win rateWWWWLWWLWL

Last 10 vs previous 10: +40pp win rate · -0.03 avg rating

Player DNA

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

Aim7.2

Aggression7.9

Utility4.5

Positioning5.9

Opening Duels3.4

Clutch6.0

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 ropz 89% playstyle similarity

Most alike: positioning profile, utility contribution.

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. 584ms 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

Aim7.2

Positioning5.9

Utility4.5

Mechanics7.8

Opening Duels3.4

Win Impact6.9

Composite 5.6/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01−0.02

first ⅓ avg 0.02 → last ⅓ avg 0.01

Reaction time585ms−38ms

first ⅓ avg 623ms → last ⅓ avg 585ms

Headshot accuracy15.9%−0.0%

first ⅓ avg 15.9% → last ⅓ avg 15.9%

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

0.14Best rating — train 6–13

13–1Biggest win — train

9Longest win streak

W4Current streak

9–7In matches decided by ≤2 rounds

3Overtime games

Map breakdown

cacheBest map · 71% over 7infernoWeakest map · 40% over 5

Map	Grade	Played	Record	Win rate	Avg rating
nuke	A	18	10–8	56%	0.01
mirage	S	16	11–5	69%	0.01
train	S	15	10–5	67%	0.03
vertigo	S	13	9–4	69%	0.05
dust2	A	9	5–4	56%	0.03
overpass	A	8	5–3	63%	0.03
cache	S	7	5–2	71%	-0.01
ancient	C	7	3–4	43%	-0.00
inferno	C	5	2–3	40%	-0.03
shelter	—	1	0–1	0%	0.09
anubis	—	1	0–1	0%	-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (40% over 5). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

36,165Lifetime kills

1.29K/D · Top 25% of tracked players

2,007Matches

48.4%Match win rate · Top 50% of tracked players

45.8%Headshot % · Top 50% of tracked players

6.1%Shot accuracy

5,328MVPs

619Hours (in match)

1,731Bombs planted

334Bombs defused

Most-used weapons

AK-4710,829

M4A4 / M4A1-S6,420

AWP2,183

P2000 / USP-S1,846

Glock-181,641

Desert Eagle1,609

FAMAS1,406

Galil AR1,201

MP91,070

MAC-10920

Lifetime map wins

2,500dust2

1,914nuke

1,801inferno

1,392vertigo

926train

565lake

152office

94cbble

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

Faceit stats

Combat

47Matches

55%Win rate

1.04Avg K/D

83.7ADR

52%Headshot %

Clutches & streaks

50%1v1 clutch win

17%1v2 clutch win

4Longest win streak

Recent Faceit resultsWLLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	19	47%	1.05	17.7
Dust2	9	44%	1.02	17.9
Nuke	9	56%	0.96	16.2
Inferno	3	33%	0.77	13.3
Ancient	2	100%	1.42	18.5
Anubis	1	100%	2.00	10.0
Vertigo	1	100%	1.18	20.0
Train	1	100%	1.13	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.

15.2%Headshot accuracy

36.9%Accuracy (enemy spotted)

38.1%Spray accuracy

85.0%Counter-strafing

10.6°Preaim

584msReaction time

42.5%T opening success

44.7%CT opening success

0.69Enemies flashed / flash

5.1%Flash assists

8.05HE damage / grenade

5.32Flashes / 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.

40% win rate across 5 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
mirage	13–11	-0.03	16%	30 Aug →
vertigo	13–9	0.07	17%	29 Aug →
vertigo	9–3	0.04	21%	29 Aug →
vertigo	13–2	0.06	19%	18 Aug →
cache	8–13	-0.04	21%	18 Aug →
dust2	13–9	0.03	14%	16 Aug →
inferno	13–10	-0.04	9%	16 Aug →
nuke	7–13	-0.09	10%	15 Aug →
cache	13–7	-0.05	21%	3 Aug →
inferno	5–13	-0.04	23%	3 Aug →
ancient	6–13	-0.07	21%	3 Aug →
nuke	1–13	-0.01	18%	2 Aug →
vertigo	5–13	0.02	15%	2 Aug →
train	11–13	0.03	19%	2 Aug →
train	13–1	0.02	19%	2 Aug →
nuke	16–19	0.02	13%	1 Aug →
dust2	10–13	0.01	6%	1 Aug →
mirage	13–10	0.03	20%	1 Aug →
dust2	13–8	0.07	18%	30 Jul →
vertigo	11–13	0.09	15%	29 Jul →
vertigo	13–9	0.02	15%	29 Jul →
vertigo	13–2	0.01	16%	29 Jul →
mirage	13–11	0.05	13%	27 Jul →
nuke	9–13	0.07	11%	26 Jul →
inferno	12–12	-0.08	6%	25 Jul →
nuke	13–8	0.02	13%	25 Jul →
nuke	13–11	0.01	19%	25 Jul →
nuke	12–12	0.01	10%	24 Jul →
mirage	3–13	0.00	31%	24 Jul →
mirage	12–12	-0.01	9%	21 Jul →
nuke	13–8	-0.01	13%	21 Jul →
nuke	13–10	0.07	15%	21 Jul →
mirage	7–13	0.01	19%	20 Jul →
overpass	11–13	0.04	17%	20 Jul →
mirage	13–10	-0.00	17%	19 Jul →
vertigo	2–9	0.01	35%	19 Jul →
vertigo	9–5	0.09	36%	19 Jul →
train	6–13	0.14	13%	19 Jul →
dust2	13–11	0.06	20%	19 Jul →
train	13–8	0.02	23%	18 Jul →
train	13–9	0.01	22%	18 Jul →
ancient	11–13	0.04	18%	17 Jul →
train	13–3	0.04	22%	17 Jul →
overpass	3–9	-0.11	21%	17 Jul →
overpass	9–7	0.11	15%	17 Jul →
nuke	13–11	0.00	20%	17 Jul →
nuke	10–0	0.02	23%	17 Jul →
nuke	13–2	0.00	20%	17 Jul →
vertigo	13–4	0.05	25%	15 Jul →
train	13–7	-0.03	16%	14 Jul →
overpass	2–13	-0.07	10%	14 Jul →
train	12–12	0.03	17%	14 Jul →
train	10–13	-0.02	20%	14 Jul →
train	13–2	0.02	12%	14 Jul →
train	13–1	0.10	27%	14 Jul →
train	13–6	0.02	23%	13 Jul →
cache	13–10	0.04	16%	13 Jul →
mirage	13–5	0.05	10%	13 Jul →
vertigo	13–11	0.01	18%	13 Jul →
mirage	13–9	0.08	11%	12 Jul →
dust2	2–13	0.05	4%	12 Jul →
vertigo	13–4	0.13	17%	12 Jul →
ancient	13–16	0.03	13%	12 Jul →
dust2	13–6	0.06	25%	12 Jul →
cache	13–4	0.01	17%	12 Jul →
mirage	13–5	0.01	13%	12 Jul →
cache	2–13	-0.09	6%	11 Jul →
nuke	14–16	0.01	10%	11 Jul →
shelter	8–13	0.09	20%	11 Jul →
train	8–13	0.02	12%	11 Jul →
train	13–9	0.08	11%	11 Jul →
inferno	13–8	0.05	16%	11 Jul →
dust2	13–8	0.03	26%	11 Jul →
dust2	11–13	0.01	10%	10 Jul →
mirage	13–11	-0.00	29%	10 Jul →
dust2	6–13	0.01	15%	9 Jul →
anubis	8–13	-0.04	17%	9 Jul →
vertigo	12–12	0.03	16%	9 Jul →
inferno	8–13	-0.04	13%	9 Jul →
nuke	13–10	0.05	20%	9 Jul →
overpass	13–8	0.11	15%	9 Jul →
ancient	13–3	0.02	12%	9 Jul →
train	13–2	0.03	11%	9 Jul →
cache	13–3	0.05	16%	9 Jul →
nuke	11–13	0.02	15%	8 Jul →
ancient	13–9	-0.00	15%	6 Jul →
overpass	13–11	0.10	17%	6 Jul →
overpass	13–5	0.01	21%	6 Jul →
nuke	13–3	0.05	18%	6 Jul →
nuke	13–3	0.06	14%	6 Jul →
cache	13–10	-0.00	11%	6 Jul →
mirage	13–5	0.08	18%	2 Jul →
overpass	13–3	0.06	7%	2 Jul →
mirage	13–9	-0.02	19%	2 Jul →
mirage	10–13	0.01	15%	1 Jul →
nuke	7–13	-0.03	19%	1 Jul →
ancient	13–5	0.06	20%	30 Jun →
mirage	1–11	-0.01	14%	29 Jun →
ancient	0–13	-0.07	27%	29 Jun →
mirage	13–1	-0.05	7%	29 Jun →