Marlon4Tilt™ — CS2 Stats

76561198150954571[U:1:190688843]Steam profile ↗

1,555Tracked matches47%Win rate2021Tracked since

CSDB Rating5.9 SolidHybrid Rifler

FaceitLevel 6Top 54.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim86

Positioning48

Utility48

0–100 skill scores via Leetify.

Recent form

COLD57–39–4Last 10057%Win rateLLLLWLWLLL

Last 10 vs previous 10: -50pp win rate · -0.01 avg rating

Player DNA

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

Aim8.6

Aggression5.9

Utility4.8

Positioning4.8

Opening Duels1.6

Clutch4.4

Sharp aimerStrong CT-side opener

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 89% playstyle similarity

Most alike: opening-fight frequency, aim profile.

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

Strengths

Aim. Aim score of 86 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 39 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.

T-side openings. Opening success drops from 45% on CT to 28% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 609ms 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

Aim8.6

Positioning4.8

Utility4.8

Mechanics7.3

Opening Duels1.9

Win Impact3.9

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 rating-0.02−0.01

first ⅓ avg -0.01 → last ⅓ avg -0.02

Reaction time604ms+6ms

first ⅓ avg 598ms → last ⅓ avg 604ms

Headshot accuracy23.2%+2.4%

first ⅓ avg 20.8% → last ⅓ avg 23.2%

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

0.09Best rating — ancient 13–4

13–2Biggest win — cache

9Longest win streak

L4Current streak

12–7In matches decided by ≤2 rounds

6Overtime games

Map breakdown

ancientBest map · 75% over 8cacheWeakest map · 45% over 29

Map	Grade	Played	Record	Win rate	Avg rating
cache	B	29	13–16	45%	-0.00
dust2	S	18	12–6	67%	-0.02
mirage	A	11	7–4	64%	-0.03
anubis	A	10	6–4	60%	-0.00
ancient	S	8	6–2	75%	0.00
inferno	B	6	3–3	50%	-0.03
overpass	—	4	2–2	50%	-0.02
vertigo	—	4	1–3	25%	-0.01
train	—	4	3–1	75%	-0.03
nuke	—	3	2–1	67%	-0.00
office	—	2	2–0	100%	-0.05
fachwerk	—	1	0–1	0%	-0.09

Across the last 100 tracked matches.

Faceit stats

Combat

188Matches

45%Win rate

0.84Avg K/D

84.0ADR

37%Headshot %

Clutches & streaks

42%1v1 clutch win

32%1v2 clutch win

6Longest win streak

Recent Faceit resultsWWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	11	73%	1.14	17.4
Dust2	8	62%	1.32	15.1
Anubis	6	67%	1.10	16.3
Nuke	6	50%	0.92	13.8
Cache	3	100%	1.80	24.0
Inferno	2	0%	0.38	6.5
Ancient	2	50%	0.60	12.0
Vertigo	2	50%	1.36	17.5

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.

22.7%Headshot accuracy

36.7%Accuracy (enemy spotted)

44.9%Spray accuracy

82.7%Counter-strafing

7.8°Preaim

609msReaction time

27.9%T opening success

45.3%CT opening success

0.47Enemies flashed / flash

4.2%Flash assists

5.47HE damage / grenade

11.00Flashes / 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 0.4682 — 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 27.9143% — 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.

45% win rate across 29 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
anubis	7–13	-0.05	27%	23 Jul →
cache	9–13	-0.06	18%	19 Jul →
fachwerk	0–13	-0.09	28%	19 Jul →
inferno	6–13	-0.06	31%	17 Jul →
inferno	13–6	-0.04	17%	17 Jul →
anubis	13–16	0.03	15%	4 Jul →
cache	13–8	-0.01	23%	3 Jul →
cache	11–13	0.05	29%	3 Jul →
mirage	6–13	-0.02	36%	1 Jul →
anubis	10–13	-0.07	17%	30 Jun →
mirage	13–11	-0.01	24%	30 Jun →
dust2	13–11	-0.04	19%	30 Jun →
dust2	13–6	0.01	16%	15 Jun →
overpass	8–13	0.00	20%	15 Jun →
ancient	13–5	-0.05	22%	15 Jun →
cache	13–4	-0.06	13%	11 Jun →
ancient	8–13	0.05	25%	11 Jun →
anubis	13–5	-0.01	32%	11 Jun →
inferno	7–13	-0.03	21%	11 Jun →
mirage	13–5	-0.05	21%	11 Jun →
dust2	16–13	-0.04	29%	11 Jun →
cache	13–9	-0.03	38%	11 Jun →
cache	9–13	-0.05	23%	11 Jun →
dust2	0–13	-0.07	25%	10 Jun →
vertigo	10–13	0.01	19%	6 Jun →
vertigo	0–5	-0.04	44%	6 Jun →
cache	13–8	-0.01	19%	4 Jun →
vertigo	6–13	-0.00	24%	4 Jun →
vertigo	13–6	0.00	9%	4 Jun →
nuke	19–16	0.02	20%	1 Jun →
anubis	13–11	-0.02	24%	27 May →
cache	11–13	0.02	24%	22 May →
cache	9–13	-0.03	18%	21 May →
dust2	13–11	-0.06	21%	21 May →
dust2	11–13	-0.01	34%	21 May →
dust2	13–5	-0.00	40%	21 May →
cache	4–13	-0.07	24%	21 May →
ancient	13–11	0.07	12%	20 May →
cache	13–11	0.06	11%	20 May →
cache	13–6	0.00	26%	18 May →
cache	12–12	-0.02	10%	18 May →
cache	10–13	-0.01	12%	18 May →
overpass	13–11	0.01	35%	16 May →
dust2	13–7	-0.02	14%	16 May →
ancient	16–13	0.00	23%	16 May →
ancient	13–6	-0.03	9%	16 May →
dust2	13–4	0.03	25%	16 May →
mirage	13–11	0.02	16%	16 May →
cache	12–12	0.03	18%	16 May →
overpass	6–13	-0.04	20%	14 May →
cache	13–2	0.06	11%	14 May →
mirage	10–13	-0.09	13%	14 May →
mirage	13–6	-0.01	10%	14 May →
office	13–7	-0.07	11%	13 May →
office	13–10	-0.04	17%	13 May →
mirage	13–7	-0.06	11%	10 May →
cache	13–8	-0.05	31%	8 May →
cache	13–5	0.03	24%	6 May →
cache	13–11	0.03	37%	4 May →
cache	13–3	0.04	18%	3 May →
cache	9–13	-0.00	24%	2 May →
cache	7–13	0.03	30%	1 May →
dust2	4–13	-0.04	20%	1 May →
dust2	13–4	0.01	23%	1 May →
dust2	10–13	-0.03	30%	30 Apr →
inferno	13–9	-0.02	16%	30 Apr →
cache	13–9	0.01	29%	30 Apr →
cache	13–6	0.02	15%	30 Apr →
cache	12–12	-0.02	28%	30 Apr →
cache	8–13	-0.04	14%	30 Apr →
cache	12–12	0.01	18%	30 Apr →
cache	11–13	-0.03	25%	30 Apr →
cache	9–13	-0.00	21%	30 Apr →
mirage	9–13	-0.07	30%	26 Apr →
anubis	13–7	0.07	22%	26 Apr →
anubis	14–16	-0.03	16%	26 Apr →
dust2	13–9	-0.01	24%	26 Apr →
train	7–13	-0.07	31%	26 Apr →
dust2	8–13	0.01	13%	26 Apr →
inferno	11–13	-0.04	17%	26 Apr →
ancient	11–13	-0.11	8%	24 Apr →
nuke	13–11	0.02	8%	24 Apr →
dust2	13–10	-0.01	25%	24 Apr →
overpass	13–3	-0.05	12%	24 Apr →
mirage	6–13	0.01	15%	24 Apr →
train	13–8	0.07	23%	23 Apr →
train	13–5	-0.01	18%	23 Apr →
dust2	13–9	0.02	30%	23 Apr →
train	13–9	-0.09	17%	23 Apr →
nuke	6–13	-0.04	33%	19 Apr →
dust2	6–13	-0.06	17%	19 Apr →
anubis	16–14	-0.05	22%	18 Apr →
anubis	13–6	0.07	22%	18 Apr →
ancient	13–5	-0.01	19%	18 Apr →
anubis	13–9	0.02	20%	18 Apr →
mirage	13–2	-0.01	44%	18 Apr →
dust2	13–5	-0.06	11%	17 Apr →
inferno	13–11	0.00	7%	17 Apr →
ancient	13–4	0.09	31%	17 Apr →
mirage	13–9	0.00	30%	17 Apr →