Malla ❤ — CS2 Stats

NO76561198189175606[U:1:228909878]Steam profile ↗✓ No bans

1,768Tracked matches47%Win rate2020Tracked since

CSDB Rating4.2 DevelopingPassive Rifler

FaceitLevel 9 · 1,346 ELOTop 20.7% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim74

Positioning33

Utility37

0–100 skill scores via Leetify.

Recent form

COLD45–51–4Last 10045%Win rateLLLLLWWLWL

Last 10 vs previous 10: -40pp win rate · -0.01 avg rating

Player DNA

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

Aim7.4

Aggression1.2

Utility3.7

Positioning3.3

Opening Duels0.0

Clutch3.0

Limited utility dependence

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 71% playstyle similarity

Most alike: aim profile, utility contribution.

Where you differ: lower positioning profile; lower opening-fight frequency.

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

Positioning. Positioning trails aim by 41 points — deaths here waste a strong aim profile.

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

Reaction time. 566ms 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

Aim7.4

Positioning3.3

Utility3.7

Mechanics5.9

Opening Duels0.0

Win Impact3.9

Composite 4.2/10 (Developing), 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 rating-0.03+0.00

first ⅓ avg -0.03 → last ⅓ avg -0.03

Reaction time563ms−10ms

first ⅓ avg 573ms → last ⅓ avg 563ms

Headshot accuracy15.0%+0.0%

first ⅓ avg 15.0% → last ⅓ avg 15.0%

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

0.12Best rating — inferno 13–9

13–2Biggest win — inferno

7Longest win streak

L5Current streak

8–11In matches decided by ≤2 rounds

17Overtime games

Map breakdown

infernoBest map · 54% over 13cacheWeakest map · 29% over 7

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	20	8–12	40%	-0.03
dust2	B	16	8–8	50%	-0.03
nuke	D	15	5–10	33%	-0.02
inferno	B	13	7–6	54%	-0.01
ancient	B	13	7–6	54%	-0.03
anubis	B	12	6–6	50%	-0.03
cache	D	7	2–5	29%	-0.05
overpass	—	2	1–1	50%	-0.04
shelter	—	1	0–1	0%	-0.07
fachwerk	—	1	1–0	100%	-0.02

Across the last 100 tracked matches.

Faceit stats

Combat

870Matches

52%Win rate

0.92Avg K/D

73.7ADR

40%Headshot %

Clutches & streaks

35%1v1 clutch win

16%1v2 clutch win

12Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	66	44%	0.96	14.9
Anubis	36	39%	0.89	15.2
Ancient	33	61%	0.85	14.6
Inferno	25	52%	0.96	17.2
Vertigo	24	58%	1.16	17.8
Nuke	20	60%	1.06	16.3
Cache	15	80%	0.69	11.1
Dust2	11	64%	0.98	14.8

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.

15.0%Headshot accuracy

37.8%Accuracy (enemy spotted)

43.6%Spray accuracy

76.7%Counter-strafing

10.2°Preaim

566msReaction time

20.9%T opening success

24.9%CT opening success

0.51Enemies flashed / flash

3.8%Flash assists

8.26HE damage / grenade

3.48Flashes / 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
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 3.4798 — below the 4 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 20.8855% — below the 40% mark we flag

Spend your practice time on Cache

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

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
nuke	10–13	-0.09	15%	26 Aug →
inferno	0–5	-0.09	33%	16 Aug →
anubis	6–13	0.04	18%	16 Aug →
mirage	12–16	0.02	16%	15 Aug →
dust2	5–13	-0.03	12%	7 Aug →
nuke	13–4	-0.02	17%	7 Aug →
dust2	13–5	-0.02	14%	7 Aug →
nuke	10–13	-0.07	10%	7 Aug →
cache	13–11	-0.06	14%	9 Jul →
shelter	10–13	-0.07	17%	9 Jul →
fachwerk	13–5	-0.02	15%	9 Jul →
cache	10–13	-0.08	21%	5 Jul →
inferno	3–13	-0.08	19%	1 Jul →
dust2	14–16	-0.05	13%	1 Jul →
inferno	13–2	0.02	17%	1 Jul →
ancient	16–13	-0.01	18%	1 Jul →
overpass	13–8	-0.04	2%	10 Jun →
dust2	16–13	-0.03	18%	4 Jun →
inferno	13–8	-0.02	18%	4 Jun →
mirage	13–11	-0.02	22%	4 Jun →
dust2	16–12	-0.04	14%	4 Jun →
dust2	8–13	-0.04	10%	4 Jun →
anubis	13–9	-0.00	12%	1 Jun →
nuke	13–10	0.03	11%	1 Jun →
mirage	11–13	-0.03	13%	1 Jun →
mirage	7–13	-0.02	23%	31 May →
dust2	13–11	-0.02	14%	31 May →
anubis	3–13	-0.13	14%	31 May →
nuke	3–13	0.04	14%	31 May →
ancient	11–13	0.05	15%	30 May →
ancient	11–13	0.02	8%	29 May →
dust2	11–13	-0.03	13%	29 May →
mirage	13–10	-0.03	11%	29 May →
mirage	13–7	0.02	19%	28 May →
cache	3–13	-0.08	6%	26 May →
inferno	13–10	-0.05	8%	26 May →
dust2	13–8	-0.03	15%	17 May →
inferno	13–9	0.12	15%	13 May →
ancient	13–7	-0.02	13%	13 May →
nuke	18–22	-0.05	10%	13 May →
cache	12–12	-0.02	12%	12 May →
mirage	13–4	0.05	23%	12 May →
inferno	9–13	0.02	11%	12 May →
dust2	13–7	0.02	14%	12 May →
cache	16–13	-0.02	22%	10 May →
nuke	5–13	-0.08	4%	10 May →
ancient	13–4	-0.05	13%	6 May →
cache	12–12	0.03	21%	30 Apr →
cache	4–13	-0.10	25%	30 Apr →
anubis	13–6	-0.01	13%	26 Apr →
nuke	14–16	-0.02	21%	26 Apr →
anubis	15–15	0.05	16%	26 Apr →
mirage	11–13	-0.08	10%	26 Apr →
mirage	14–16	-0.04	18%	26 Apr →
nuke	13–8	-0.01	20%	26 Apr →
ancient	13–7	-0.07	6%	26 Apr →
mirage	15–15	-0.00	32%	25 Apr →
dust2	13–11	-0.01	18%	25 Apr →
ancient	13–5	-0.00	19%	25 Apr →
dust2	9–13	-0.05	15%	25 Apr →
mirage	12–16	-0.07	15%	25 Apr →
ancient	13–11	-0.03	8%	25 Apr →
ancient	2–13	-0.05	19%	25 Apr →
anubis	13–8	-0.09	12%	25 Apr →
ancient	2–13	-0.06	38%	25 Apr →
anubis	13–7	-0.03	8%	25 Apr →
mirage	4–13	-0.04	31%	24 Apr →
inferno	13–11	0.05	19%	24 Apr →
anubis	16–14	0.00	18%	24 Apr →
dust2	5–13	-0.04	14%	24 Apr →
mirage	6–13	-0.03	11%	24 Apr →
ancient	16–14	-0.05	17%	22 Apr →
mirage	9–13	-0.06	12%	22 Apr →
dust2	7–13	-0.08	5%	22 Apr →
inferno	13–16	-0.04	19%	22 Apr →
nuke	13–9	0.06	17%	22 Apr →
mirage	6–13	-0.04	18%	17 Apr →
ancient	3–13	-0.07	20%	17 Apr →
anubis	8–13	-0.07	7%	17 Apr →
inferno	13–8	-0.07	14%	17 Apr →
mirage	13–8	0.02	11%	17 Apr →
inferno	9–13	0.00	26%	17 Apr →
mirage	6–13	-0.05	21%	15 Apr →
anubis	13–2	0.00	11%	15 Apr →
dust2	13–10	-0.03	22%	12 Apr →
mirage	13–8	-0.02	9%	12 Apr →
nuke	11–13	-0.04	18%	12 Apr →
inferno	14–16	-0.01	23%	12 Apr →
dust2	19–22	-0.07	11%	3 Mar →
inferno	13–8	-0.01	13%	3 Mar →
mirage	13–8	-0.07	24%	25 Feb →
overpass	10–13	-0.05	23%	18 Feb →
nuke	4–13	-0.11	9%	18 Feb →
nuke	5–13	-0.04	20%	16 Feb →
ancient	4–13	-0.03	13%	15 Feb →
mirage	13–10	-0.02	7%	15 Feb →
nuke	13–9	-0.00	12%	15 Feb →
anubis	10–13	-0.11	14%	12 Feb →
nuke	11–13	0.03	12%	9 Feb →
anubis	8–13	-0.02	8%	9 Feb →