mauxム — CS2 Stats

FI76561197999959698[U:1:39693970]Steam profile ↗

1,884Tracked matches39%Win rate2020Tracked since

CSDB Rating5.0 DevelopingHybrid Rifler

Premier CS Rating19,546Purple band · top ~10.3% of ranked players (population est.)

CSDB Leaderboard#13856 of 31706 tracked

FaceitLevel 7Top 42.3% of ranked FACEIT players

WingmanMaster Guardian Elite

Ladder ranks via Leetify

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Performance scores

Aim67

Positioning39

Utility53

0–100 skill scores via Leetify.

Recent form

STEADY52–40–8Last 10052%Win rateWLWWLLLWWL

Last 10 vs previous 10: +40pp win rate · +0.00 avg rating

Player DNA

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

Aim6.7

Aggression5.6

Utility5.3

Positioning3.9

Opening Duels1.7

Clutch2.4

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.

Your pro match

Plays most like NiKo 86% playstyle similarity

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

Where you differ: lower positioning profile; 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

T-side openings. Opening success drops from 45% on CT to 29% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim6.7

Positioning3.9

Utility5.3

Mechanics7.5

Opening Duels1.9

Win Impact1.4

Composite 5.0/10 (Developing), 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-0.02−0.00

first ⅓ avg -0.01 → last ⅓ avg -0.02

Reaction time587ms−31ms

first ⅓ avg 618ms → last ⅓ avg 587ms

Headshot accuracy14.9%−0.9%

first ⅓ avg 15.8% → last ⅓ avg 14.9%

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

0.11Best rating — train 13–2

13–0Biggest win — vertigo

7Longest win streak

6–5In matches decided by ≤2 rounds

6Overtime games

Map breakdown

infernoBest map · 70% over 20trainWeakest map · 20% over 5

Map	Grade	Played	Record	Win rate	Avg rating
inferno	S	20	14–6	70%	-0.01
nuke	B	15	8–7	53%	-0.02
cache	A	14	8–6	57%	-0.02
anubis	A	13	8–5	62%	0.00
ancient	S	12	8–4	67%	-0.00
train	D	5	1–4	20%	0.03
italy	D	5	1–4	20%	-0.02
overpass	—	4	1–3	25%	-0.06
mirage	—	3	0–3	0%	-0.06
shelter	—	3	1–2	33%	0.01
fachwerk	—	2	1–1	50%	0.03
vertigo	—	2	1–1	50%	0.02
boulder	—	1	0–1	0%	-0.05
office	—	1	0–1	0%	0.02

Across the last 100 tracked matches.

Faceit stats

Combat

708Matches

51%Win rate

0.90Avg K/D

71.3ADR

40%Headshot %

Clutches & streaks

32%1v1 clutch win

17%1v2 clutch win

8Longest win streak

Recent Faceit resultsWLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	91	54%	0.82	12.9
Nuke	63	59%	0.85	13.0
Anubis	58	50%	0.84	13.7
Ancient	45	47%	0.83	13.9
Cache	33	55%	0.81	12.9
Overpass	25	52%	0.81	12.5
Train	16	50%	0.79	12.3
Mirage	16	50%	0.84	12.4

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.

14.3%Headshot accuracy

33.5%Accuracy (enemy spotted)

34.7%Spray accuracy

83.8%Counter-strafing

9.2°Preaim

584msReaction time

28.8%T opening success

45.1%CT opening success

0.59Enemies flashed / flash

12.9%Flash assists

9.57HE damage / grenade

6.84Flashes / 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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 14.3298% — below the 15% mark we flag
Aim Training →
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 28.8201% — below the 40% mark we flag

Spend your practice time on Train

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
nuke	13–9	-0.04	9%	28 Aug →
inferno	11–13	0.00	12%	28 Aug →
ancient	13–4	-0.00	11%	27 Aug →
inferno	13–8	0.02	12%	27 Aug →
nuke	2–13	-0.08	9%	27 Aug →
inferno	10–13	-0.01	12%	27 Aug →
ancient	7–13	-0.04	19%	27 Aug →
nuke	13–6	0.03	24%	27 Aug →
ancient	13–11	-0.01	18%	26 Aug →
mirage	5–13	-0.08	16%	26 Aug →
anubis	13–4	-0.01	8%	26 Aug →
overpass	9–13	-0.09	17%	26 Aug →
mirage	5–13	-0.02	13%	26 Aug →
cache	4–13	-0.01	11%	23 Aug →
overpass	6–13	-0.07	6%	22 Aug →
train	7–13	0.04	17%	22 Aug →
fachwerk	12–12	0.02	11%	22 Aug →
italy	5–13	-0.08	9%	22 Aug →
shelter	3–13	0.03	17%	22 Aug →
boulder	6–13	-0.05	22%	22 Aug →
inferno	13–10	-0.03	12%	21 Aug →
nuke	13–10	0.01	20%	20 Aug →
ancient	13–5	0.05	10%	20 Aug →
ancient	8–13	-0.01	29%	20 Aug →
nuke	15–15	-0.04	11%	18 Aug →
inferno	13–6	0.00	17%	18 Aug →
cache	13–16	0.05	15%	18 Aug →
nuke	9–13	-0.02	7%	18 Aug →
mirage	10–13	-0.07	19%	17 Aug →
ancient	13–5	0.03	19%	17 Aug →
cache	13–11	-0.00	27%	17 Aug →
nuke	13–6	-0.02	22%	17 Aug →
anubis	12–16	-0.06	16%	16 Aug →
inferno	8–13	-0.05	12%	16 Aug →
inferno	13–3	0.07	21%	16 Aug →
train	7–13	0.04	20%	15 Aug →
italy	6–13	0.04	5%	15 Aug →
cache	5–13	-0.08	6%	15 Aug →
anubis	13–3	0.03	15%	15 Aug →
anubis	12–16	0.04	19%	14 Aug →
ancient	13–9	0.02	15%	14 Aug →
nuke	13–11	0.04	14%	14 Aug →
anubis	6–13	-0.04	22%	14 Aug →
inferno	13–3	0.04	14%	14 Aug →
italy	7–13	-0.04	12%	13 Aug →
vertigo	13–0	0.02	13%	13 Aug →
inferno	13–10	-0.04	16%	13 Aug →
inferno	13–6	-0.06	18%	13 Aug →
cache	12–12	-0.09	19%	13 Aug →
overpass	13–0	-0.08	11%	13 Aug →
train	12–12	-0.06	16%	13 Aug →
shelter	13–9	-0.02	14%	13 Aug →
vertigo	10–13	0.03	24%	12 Aug →
italy	7–13	-0.06	12%	12 Aug →
train	7–13	0.01	28%	12 Aug →
anubis	13–1	0.02	9%	12 Aug →
nuke	11–13	-0.05	16%	12 Aug →
nuke	13–5	0.01	3%	11 Aug →
cache	13–10	-0.01	15%	11 Aug →
overpass	12–12	-0.02	17%	11 Aug →
shelter	12–12	0.00	20%	11 Aug →
train	13–2	0.11	14%	11 Aug →
cache	13–10	0.03	33%	11 Aug →
office	12–12	0.02	36%	10 Aug →
italy	13–7	0.04	11%	10 Aug →
fachwerk	13–9	0.04	17%	10 Aug →
ancient	13–5	-0.04	12%	9 Aug →
nuke	11–13	-0.00	10%	9 Aug →
inferno	13–2	0.00	12%	9 Aug →
inferno	10–13	-0.01	7%	9 Aug →
inferno	13–11	-0.00	22%	9 Aug →
anubis	13–8	0.00	19%	9 Aug →
nuke	13–4	0.01	14%	9 Aug →
inferno	13–6	-0.02	21%	9 Aug →
cache	13–8	-0.05	15%	9 Aug →
inferno	13–9	-0.02	14%	7 Aug →
cache	13–6	-0.02	14%	7 Aug →
inferno	15–15	-0.05	13%	7 Aug →
ancient	10–13	-0.04	29%	5 Aug →
anubis	11–13	-0.05	7%	5 Aug →
cache	11–13	-0.01	34%	5 Aug →
anubis	10–13	-0.01	17%	5 Aug →
anubis	13–4	0.03	16%	4 Aug →
inferno	13–11	-0.04	16%	4 Aug →
nuke	4–13	-0.07	2%	4 Aug →
cache	16–12	0.02	22%	4 Aug →
ancient	13–8	0.06	11%	4 Aug →
nuke	13–6	-0.03	26%	3 Aug →
anubis	13–7	-0.02	19%	3 Aug →
cache	13–8	0.02	18%	3 Aug →
inferno	13–9	0.01	17%	3 Aug →
anubis	13–7	0.06	18%	3 Aug →
cache	3–13	-0.06	16%	3 Aug →
ancient	13–11	-0.04	27%	3 Aug →
nuke	10–13	-0.07	10%	2 Aug →
inferno	13–9	-0.02	4%	2 Aug →
ancient	9–13	-0.01	11%	2 Aug →
anubis	13–1	0.02	17%	2 Aug →
inferno	10–13	-0.06	5%	2 Aug →
cache	13–5	-0.01	20%	2 Aug →