Martus — CS2 Stats

FI76561198219830089[U:1:259564361]Steam profile ↗✓ No bans

2,536Tracked matches50%Win rate2020Tracked since

CSDB Rating6.3 SolidSupport

CSDB Leaderboard#230312 of 261691 tracked

FaceitLevel 10 · 2,126 ELOTop 12.4% of ranked FACEIT players

WingmanLegendary Eagle Master

Ladder ranks via Leetify

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Performance scores

Aim82

Positioning54

Utility59

0–100 skill scores via Leetify.

Recent form

STEADY43–45–12Last 10043%Win rateWLLTWLWWWW

Last 10 vs previous 10: +10pp win rate · +0.01 avg rating · −1.6pp headshot accuracy · −27ms reaction

Win rate +10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

2–2–1 · 40% win rate
Avg rating -0.00
Avg headshot accuracy 14%
Avg reaction 531ms

Last 10

6–3–1 · 60% win rate
Avg rating 0.02
Avg headshot accuracy 16%
Avg reaction 529ms

Last 20

11–7–2 · 55% win rate
Avg rating 0.01
Avg headshot accuracy 17%
Avg reaction 542ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Support — Utility contribution stands above the rest of this profile (+2 against its own average).

Aim8.2

Utility5.9

Positioning5.4

Opening Duels1.5

Clutch3.0

Strong 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.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

Plays most like NiKo 91% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower opening-duel success.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

CSDB Rating breakdown

Aim8.2

Positioning5.4

Utility5.9

Mechanics7.3

Opening Duels2.3

Win Impact5.0

Composite 6.3/10 (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 rating0.00−0.04

first ⅓ avg 0.04 → last ⅓ avg 0.00

Reaction time555ms−109ms

first ⅓ avg 664ms → last ⅓ avg 555ms

Headshot accuracy17.8%−8.1%

first ⅓ avg 25.9% → last ⅓ avg 17.8%

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.

Personal bests

0.20Best match rating · 12–12 · dust2, 12 May →

59%Best headshot accuracy · 13–5 · stronghold, 4 Jun →

422msFastest reaction time · 13–11 · ancient, 13 Nov →

13–2Biggest win · italy, 21 Aug →

Across the last 100 tracked matches.

Highlights

6Longest win streak

6–5In matches decided by ≤2 rounds

8Overtime games

Map breakdown

mirageBest map · 50% over 14dust2Weakest map · 29% over 7

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	14	7–7	50%	0.03
ancient	B	12	6–6	50%	0.01
cache	B	12	6–6	50%	0.03
nuke	C	10	4–6	40%	-0.01
anubis	C	9	4–5	44%	0.01
dust2	D	7	2–5	29%	0.04
inferno	C	5	2–3	40%	0.06
vertigo	C	5	2–3	40%	0.00
train	—	4	1–3	25%	0.01
stronghold	—	4	4–0	100%	0.05
office	—	4	1–3	25%	0.00
overpass	—	3	0–3	0%	-0.02
italy	—	3	3–0	100%	0.07
warden	—	3	1–2	33%	-0.00
shelter	—	1	0–1	0%	-0.05
fachwerk	—	1	0–1	0%	-0.06
eldorado	—	1	0–1	0%	-0.05
debris	—	1	0–1	0%	0.02
alpine	—	1	0–1	0%	0.07

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

2,697Matches

51%Win rate

1.08Avg K/D

75.4ADR

49%Headshot %

Clutches & streaks

35%1v1 clutch win

19%1v2 clutch win

10Longest win streak

Recent Faceit resultsWWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	447	58%	1.04	15.1
Anubis	313	50%	1.01	14.8
Vertigo	152	53%	1.03	14.4
Nuke	148	40%	1.01	14.8
Overpass	131	59%	1.16	15.4
Mirage	126	48%	1.02	15.1
Train	117	59%	1.10	15.3
Inferno	21	33%	0.99	14.2

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.

17.8%Headshot accuracy

37.0%Accuracy (enemy spotted)

43.5%Spray accuracy

82.7%Counter-strafing

9.3°Preaim

549msReaction time

33.6%T opening success

45.2%CT opening success

0.63Enemies flashed / flash

7.9%Flash assists

9.52HE damage / grenade

11.77Flashes / 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 33.6344% — below the 40% mark we flag

Spend your practice time on Dust 2

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.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
ancient	13–11	-0.03	7%	13 Nov →
nuke	11–13	0.03	19%	13 Nov →
cache	9–13	-0.02	22%	12 Nov →
inferno	8–8	0.02	8%	10 Nov →
vertigo	13–5	-0.01	14%	8 Nov →
cache	5–13	0.09	17%	5 Nov →
nuke	13–5	0.01	24%	5 Nov →
train	13–10	0.03	22%	5 Nov →
anubis	13–7	0.01	12%	3 Nov →
mirage	13–6	0.03	15%	30 Oct →
ancient	9–13	-0.02	15%	29 Oct →
overpass	8–8	0.06	10%	29 Oct →
anubis	16–12	0.01	18%	17 Oct →
inferno	7–13	0.01	29%	17 Oct →
dust2	13–5	-0.03	15%	14 Oct →
anubis	11–13	-0.05	7%	13 Oct →
mirage	6–13	-0.05	10%	8 Oct →
mirage	13–7	0.05	31%	4 Sept →
cache	13–9	0.07	18%	1 Sept →
anubis	13–8	0.05	25%	1 Sept →
cache	19–16	0.10	16%	31 Aug →
ancient	9–13	-0.07	11%	31 Aug →
cache	12–12	-0.05	23%	29 Aug →
train	3–13	-0.02	21%	29 Aug →
shelter	9–13	-0.05	10%	29 Aug →
fachwerk	7–13	-0.06	19%	29 Aug →
ancient	3–13	0.02	25%	29 Aug →
ancient	10–13	0.02	17%	29 Aug →
cache	15–15	0.00	24%	29 Aug →
ancient	19–16	-0.02	13%	28 Aug →
ancient	13–8	-0.00	24%	27 Aug →
anubis	7–13	0.02	17%	27 Aug →
ancient	16–14	0.00	27%	26 Aug →
vertigo	13–6	0.00	24%	23 Aug →
eldorado	6–9	-0.05	27%	21 Aug →
debris	8–8	0.02	44%	21 Aug →
italy	13–2	0.01	45%	21 Aug →
dust2	6–10	0.07	24%	21 Aug →
mirage	13–4	0.01	14%	21 Aug →
cache	13–11	-0.03	21%	10 Aug →
nuke	13–6	0.02	13%	7 Aug →
mirage	16–14	0.05	19%	3 Aug →
vertigo	12–12	0.08	17%	3 Aug →
mirage	6–13	0.02	35%	3 Aug →
mirage	4–13	-0.06	41%	3 Aug →
anubis	8–13	-0.01	32%	1 Aug →
nuke	12–16	-0.03	22%	31 Jul →
mirage	13–9	0.12	23%	27 Jul →
ancient	12–16	-0.04	20%	23 Jul →
anubis	7–13	-0.05	13%	21 Jul →
mirage	13–7	0.03	11%	4 Jun →
stronghold	13–5	0.05	59%	4 Jun →
vertigo	6–13	-0.02	9%	3 Jun →
office	13–10	0.03	21%	3 Jun →
nuke	5–13	-0.04	31%	3 Jun →
office	3–13	-0.08	14%	3 Jun →
nuke	9–13	0.04	15%	3 Jun →
warden	6–13	-0.02	25%	3 Jun →
stronghold	7–5	-0.05	44%	3 Jun →
warden	13–9	-0.01	50%	3 Jun →
cache	13–10	0.01	19%	1 Jun →
train	11–13	0.09	22%	1 Jun →
cache	8–13	0.09	23%	1 Jun →
dust2	8–13	-0.05	50%	1 Jun →
cache	13–11	0.04	33%	14 May →
italy	13–4	0.04	16%	14 May →
anubis	13–8	0.08	28%	14 May →
ancient	13–5	0.18	38%	14 May →
nuke	13–4	-0.03	28%	14 May →
dust2	13–5	0.01	29%	14 May →
mirage	11–13	0.10	23%	14 May →
mirage	13–9	0.07	25%	14 May →
office	3–13	0.01	39%	14 May →
train	0–13	-0.06	56%	14 May →
dust2	7–13	0.02	29%	14 May →
cache	12–12	0.06	23%	14 May →
overpass	5–13	-0.03	15%	13 May →
mirage	10–13	0.07	24%	13 May →
inferno	13–10	0.12	8%	13 May →
dust2	8–13	0.08	31%	13 May →
stronghold	13–8	0.10	24%	13 May →
ancient	13–6	0.08	27%	13 May →
warden	12–12	0.02	21%	12 May →
stronghold	10–1	0.10	20%	12 May →
inferno	12–12	0.01	11%	12 May →
office	10–13	0.06	22%	12 May →
dust2	12–12	0.20	29%	12 May →
nuke	13–7	0.13	28%	12 May →
italy	13–6	0.16	29%	12 May →
mirage	8–13	0.07	30%	12 May →
alpine	11–13	0.07	41%	12 May →
vertigo	5–13	-0.03	40%	12 May →
anubis	12–12	0.06	24%	12 May →
cache	13–6	0.01	26%	12 May →
ancient	10–13	-0.07	17%	2 Apr →
mirage	5–13	-0.04	11%	30 Mar →
nuke	3–9	-0.15	6%	30 Mar →
nuke	8–8	-0.06	29%	30 Mar →
inferno	9–2	0.14	27%	30 Mar →
overpass	5–9	-0.10	25%	30 Mar →