marlo — CS2 Stats

MN76561199442989788[U:1:1482724060]Steam profile ↗✓ No bans

981Tracked matches52%Win rate2023Tracked since

982Hours in CS

CSDB Rating5.6 SolidHybrid Rifler

Ladder ranks via Leetify

Performance scores

Aim67

Positioning58

Utility39

0–100 skill scores via Leetify.

Recent form

STEADY48–47–5Last 10048%Win rateLWWLWWWLLW

Last 10 vs previous 10: +20pp win rate · -0.00 avg rating

Player DNA

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

Aim6.7

Aggression5.8

Utility3.9

Positioning5.8

Opening Duels2.7

Clutch3.8

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 88% playstyle similarity

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

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. 644ms 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

Aim6.7

Positioning5.8

Utility3.9

Mechanics6.8

Opening Duels2.7

Win Impact5.6

Composite 5.6/10 (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 rating0.00+0.00

first ⅓ avg 0.00 → last ⅓ avg 0.00

Reaction time642ms−16ms

first ⅓ avg 658ms → last ⅓ avg 642ms

Headshot accuracy21.1%−0.6%

first ⅓ avg 21.7% → last ⅓ avg 21.1%

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 — dust2 13–7

13–0Biggest win — vertigo

5Longest win streak

4–4In matches decided by ≤2 rounds

7Overtime games

Map breakdown

anubisBest map · 56% over 9ancientWeakest map · 30% over 10

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	38	20–18	53%	-0.00
ancient	D	10	3–7	30%	-0.02
anubis	A	9	5–4	56%	0.00
mirage	C	9	4–5	44%	-0.02
nuke	B	8	4–4	50%	0.01
overpass	C	7	3–4	43%	0.00
inferno	D	6	2–4	33%	-0.00
cache	—	4	0–4	0%	0.01
vertigo	—	2	1–1	50%	-0.00
warden	—	2	2–0	100%	-0.01
alpine	—	1	1–0	100%	-0.01
agency	—	1	0–1	0%	-0.03
jura	—	1	1–0	100%	0.04
grail	—	1	1–0	100%	0.06
train	—	1	1–0	100%	-0.08

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

42,799Lifetime kills

0.93K/D

1,528Matches

47.0%Match win rate · Top 50% of tracked players

60.2%Headshot % · Top 10% of tracked players

3.7%Shot accuracy

3,249MVPs

982Hours (in match)

1,873Bombs planted

412Bombs defused

Most-used weapons

AK-4724,187

M4A4 / M4A1-S6,376

P2000 / USP-S2,470

Desert Eagle2,428

Glock-181,367

AWP1,365

MP9964

MAC-10819

Galil AR587

FAMAS460

Lifetime map wins

5,202dust2

1,169inferno

1,082nuke

918vertigo

191train

30cbble

9italy

6office

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

Faceit stats

Combat

544Matches

49%Win rate

1.17Avg K/D

78.8ADR

47%Headshot %

Clutches & streaks

39%1v1 clutch win

22%1v2 clutch win

6Longest win streak

Recent Faceit resultsLWLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Anubis	118	59%	1.29	17.3
Dust2	106	47%	1.16	16.5
Mirage	88	42%	1.11	15.8
Ancient	57	46%	1.14	17.2
Inferno	46	41%	1.06	14.7
Nuke	36	53%	1.02	14.5
Vertigo	20	55%	1.23	16.1
Train	7	57%	1.25	16.0

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.

21.2%Headshot accuracy

33.0%Accuracy (enemy spotted)

35.2%Spray accuracy

80.7%Counter-strafing

9.2°Preaim

644msReaction time

36.8%T opening success

45.1%CT opening success

0.58Enemies flashed / flash

8.6%Flash assists

7.53HE damage / grenade

6.86Flashes / 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.

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 36.7755% — below the 40% mark we flag

Spend your practice time on Ancient

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

30% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	1–9	-0.06	28%	26 Aug →
dust2	13–8	0.04	19%	12 Jul →
nuke	13–10	0.01	18%	28 Jun →
vertigo	10–13	0.01	10%	23 Jun →
dust2	13–7	0.14	28%	22 Jun →
warden	13–8	0.03	10%	22 Jun →
alpine	12–0	-0.01	25%	22 Jun →
ancient	3–13	0.06	13%	22 Jun →
ancient	5–13	-0.03	10%	20 Jun →
warden	13–8	-0.06	15%	20 Jun →
dust2	12–12	-0.03	31%	19 Jun →
vertigo	13–0	-0.01	14%	10 Jun →
dust2	13–2	0.07	21%	10 Jun →
cache	1–13	0.03	22%	8 Jun →
nuke	9–13	0.08	19%	3 Jun →
anubis	13–6	0.03	20%	2 Jun →
nuke	16–12	0.03	30%	1 Jun →
nuke	8–13	0.01	18%	1 Jun →
ancient	8–13	-0.06	21%	31 May →
anubis	11–13	-0.00	43%	31 May →
dust2	1–13	-0.01	29%	29 May →
nuke	3–13	-0.03	17%	27 May →
inferno	11–13	-0.02	30%	26 May →
dust2	9–13	-0.03	29%	26 May →
dust2	13–10	-0.00	23%	25 May →
mirage	13–9	0.04	23%	25 May →
ancient	9–13	-0.02	11%	25 May →
overpass	13–5	0.01	31%	25 May →
dust2	13–1	-0.00	4%	25 May →
nuke	13–9	-0.01	15%	25 May →
dust2	13–6	-0.04	19%	25 May →
inferno	13–11	-0.01	29%	25 May →
inferno	11–13	-0.04	21%	24 May →
dust2	2–13	-0.10	16%	24 May →
overpass	13–3	0.12	21%	24 May →
anubis	13–6	0.01	14%	24 May →
ancient	2–13	-0.05	19%	24 May →
anubis	13–10	-0.01	25%	24 May →
dust2	9–13	-0.03	25%	24 May →
dust2	2–13	0.02	33%	24 May →
cache	9–13	0.06	32%	4 May →
overpass	4–13	-0.04	23%	4 May →
cache	8–13	-0.02	20%	29 Apr →
cache	3–13	-0.03	19%	28 Apr →
mirage	3–13	-0.05	27%	28 Apr →
mirage	13–11	-0.02	9%	16 Jan →
ancient	13–6	0.01	16%	16 Jan →
ancient	13–1	-0.02	35%	15 Jan →
dust2	13–6	-0.02	20%	23 Dec →
overpass	8–13	-0.02	25%	22 Dec →
mirage	7–13	-0.02	22%	22 Dec →
dust2	3–13	-0.06	23%	19 Dec →
dust2	2–9	-0.13	0%	9 Dec →
dust2	13–7	-0.04	25%	8 Dec →
dust2	13–10	0.02	27%	6 Dec →
overpass	5–13	-0.05	10%	22 Nov →
mirage	13–8	-0.04	36%	22 Nov →
inferno	10–13	0.03	16%	3 Nov →
nuke	13–6	0.02	24%	3 Nov →
dust2	13–7	0.02	23%	3 Nov →
dust2	8–13	-0.06	32%	24 Oct →
overpass	16–14	-0.03	24%	27 Sept →
dust2	6–13	-0.03	26%	11 Sept →
dust2	16–13	0.03	30%	13 Aug →
dust2	10–6	-0.07	10%	15 Jul →
dust2	10–13	-0.00	25%	9 Jul →
dust2	12–12	-0.05	14%	28 Jun →
mirage	5–13	-0.02	46%	28 Jun →
mirage	7–13	-0.05	36%	11 Jun →
anubis	13–16	-0.02	12%	14 May →
dust2	13–5	0.04	23%	13 May →
inferno	13–9	0.00	21%	11 May →
agency	6–13	-0.03	27%	8 May →
dust2	13–0	0.03	19%	8 May →
jura	8–1	0.04	36%	8 May →
grail	13–10	0.06	27%	8 May →
inferno	9–13	0.00	19%	28 Apr →
anubis	6–13	-0.02	16%	24 Apr →
mirage	13–6	0.00	16%	23 Apr →
dust2	13–8	-0.04	15%	23 Apr →
anubis	13–3	0.06	19%	22 Apr →
dust2	13–4	0.08	17%	16 Apr →
dust2	13–8	0.02	9%	16 Apr →
nuke	6–13	-0.01	17%	13 Apr →
mirage	8–13	-0.06	18%	12 Apr →
dust2	12–12	-0.05	15%	11 Apr →
anubis	10–13	-0.06	16%	11 Apr →
ancient	15–15	-0.05	15%	10 Apr →
dust2	13–2	-0.05	36%	9 Apr →
ancient	5–13	-0.01	19%	8 Apr →
dust2	11–13	0.10	27%	8 Apr →
anubis	22–18	0.01	12%	6 Apr →
train	13–11	-0.08	13%	6 Apr →
overpass	12–12	0.01	17%	6 Apr →
dust2	6–13	0.02	30%	6 Apr →
dust2	13–3	0.07	34%	6 Apr →
dust2	9–13	0.03	22%	5 Apr →
dust2	13–3	0.04	36%	5 Apr →
ancient	16–12	-0.03	12%	5 Apr →
dust2	7–13	0.04	21%	4 Apr →