maqx — CS2 Stats

76561198197729777[U:1:237464049]Steam profile ↗✓ No bans

3,064Tracked matches53%Win rate2020Tracked since

11,710Hours in CS41Hrs last 2 wks

CSDB Rating7.7 StrongAggressive Rifler

FaceitLevel 10 · 3,039 ELOTop 12.4% of ranked FACEIT players

WingmanLegendary Eagle

Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 10 among CSDB-tracked players (n=7,415), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

Metric	This player	Level 10 median
Headshot rate	47.3%	51.7%
Shot accuracy	18.1%	13.8%
Kill/death ratio	1.39	1.09
Match win rate	53.7%	48.7%

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Performance scores

Aim92

Positioning64

Utility75

0–100 skill scores via Leetify.

Recent form

STEADY59–39–2Last 10059%Win rateWLLLWWWWLL

Last 10 vs previous 10: +0pp win rate · -0.01 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim9.2

Aggression9.9

Utility7.5

Positioning6.4

Opening Duels4.7

Clutch3.8

Sharp aimerStrong CT-side openerEffective flashesHigh utility contribution

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 jL 97% playstyle similarity

Most alike: opening-fight frequency, 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

Strengths

Aim. Aim score of 92 — the mechanical foundation is a clear strength.

CT openings. 64% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Flashes. 0.85 enemies blinded per flash — utility that consistently lands.

Areas to improve

T-side openings. Opening success drops from 64% on CT to 33% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim9.2

Positioning6.4

Utility7.5

Mechanics7.2

Opening Duels4.7

Win Impact6.1

Composite 7.7/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02+0.01

first ⅓ avg 0.02 → last ⅓ avg 0.02

Reaction time510ms−30ms

first ⅓ avg 540ms → last ⅓ avg 510ms

Headshot accuracy24.6%+0.2%

first ⅓ avg 24.4% → last ⅓ avg 24.6%

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

0.15Best rating — inferno 13–9

13–0Biggest win — inferno

8Longest win streak

14–7In matches decided by ≤2 rounds

12Overtime games

Map breakdown

nukeBest map · 88% over 16infernoWeakest map · 42% over 19

Map	Grade	Played	Record	Win rate	Avg rating
inferno	C	19	8–11	42%	0.02
nuke	S	16	14–2	88%	0.03
ancient	S	13	10–3	77%	0.01
dust2	C	12	5–7	42%	0.02
cache	S	8	6–2	75%	0.03
anubis	A	8	5–3	63%	0.03
train	B	8	4–4	50%	0.01
overpass	C	7	3–4	43%	-0.00
vertigo	—	4	3–1	75%	0.07
mirage	—	3	0–3	0%	-0.02
brewery	—	1	1–0	100%	0.08
jura	—	1	0–1	0%	0.11

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (42% over 19). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

301,906Lifetime kills

1.39K/D · Top 10% of Level 10 players

10,358Matches

53.7%Match win rate · Top 25% of Level 10 players

47.3%Headshot %

18.1%Shot accuracy · Top 25% of Level 10 players

38,080MVPs

4,885Hours (in match)

11,277Bombs planted

4,630Bombs defused

Most-used weapons

AK-4796,624

M4A4 / M4A1-S49,526

AWP40,663

Desert Eagle24,033

P2000 / USP-S19,395

Glock-1812,365

Knife7,052

AUG5,466

P2504,763

Galil AR3,943

Lifetime map wins

19,999inferno

16,999nuke

8,801dust2

7,483train

6,250vertigo

2,190cbble

350lake

196office

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

Faceit stats

Combat

5,405Matches

54%Win rate

1.28Avg K/D

84.9ADR

47%Headshot %

Clutches & streaks

39%1v1 clutch win

23%1v2 clutch win

15Longest win streak

Recent Faceit resultsLWLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Nuke	452	64%	1.24	17.1
Ancient	336	55%	1.25	17.4
Inferno	314	52%	1.25	17.7
Dust2	269	51%	1.17	16.8
Anubis	202	49%	1.14	16.2
Train	187	64%	1.34	17.9
Overpass	144	51%	1.17	17.1
Mirage	127	43%	1.17	16.4

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.

24.3%Headshot accuracy

39.6%Accuracy (enemy spotted)

40.6%Spray accuracy

82.3%Counter-strafing

7.8°Preaim

508msReaction time

33.4%T opening success

64.5%CT opening success

0.85Enemies flashed / flash

9.8%Flash assists

11.26HE damage / grenade

14.88Flashes / 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 33.3995% — below the 40% mark we flag

Spend your practice time on Inferno

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

42% win rate across 19 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
ancient	13–6	0.02	17%	29 Aug →
mirage	7–13	-0.06	10%	25 Aug →
dust2	7–13	0.00	20%	23 Aug →
inferno	7–13	0.05	19%	23 Aug →
nuke	13–8	0.06	33%	23 Aug →
vertigo	13–7	0.12	22%	23 Aug →
vertigo	13–6	0.09	25%	23 Aug →
ancient	13–7	0.03	21%	22 Aug →
inferno	3–13	-0.06	24%	19 Aug →
vertigo	23–25	0.07	25%	16 Aug →
dust2	10–13	0.06	21%	16 Aug →
cache	13–6	0.05	30%	15 Aug →
cache	8–13	0.04	16%	9 Aug →
cache	10–13	0.01	18%	9 Aug →
nuke	13–11	0.03	19%	8 Aug →
vertigo	13–10	0.01	23%	6 Aug →
nuke	13–11	0.05	39%	5 Aug →
dust2	4–13	-0.01	20%	1 Aug →
cache	16–12	0.10	39%	26 Jul →
inferno	6–13	0.05	43%	25 Jul →
cache	13–11	0.00	30%	22 Jul →
anubis	7–13	-0.01	19%	22 Jul →
ancient	13–8	0.07	32%	19 Jul →
dust2	8–13	-0.02	13%	8 Jul →
inferno	7–9	-0.02	21%	7 Jul →
inferno	8–8	0.01	37%	5 Jul →
cache	13–10	0.03	29%	3 Jul →
cache	13–3	0.02	37%	3 Jul →
overpass	6–13	-0.08	17%	13 Jun →
nuke	16–12	0.03	24%	31 May →
cache	13–11	0.02	21%	13 May →
anubis	8–13	-0.01	16%	13 May →
dust2	13–7	0.02	33%	21 Apr →
anubis	13–9	0.05	30%	19 Apr →
anubis	13–10	0.02	28%	10 Apr →
anubis	13–5	0.11	23%	7 Apr →
inferno	9–13	0.00	32%	3 Apr →
dust2	13–9	-0.02	29%	2 Apr →
inferno	9–13	-0.02	27%	29 Mar →
nuke	16–14	0.03	33%	28 Mar →
anubis	19–16	0.06	27%	28 Mar →
overpass	13–9	0.04	24%	28 Mar →
anubis	13–4	-0.01	25%	28 Mar →
nuke	13–11	0.05	21%	28 Mar →
inferno	13–0	0.05	31%	28 Mar →
nuke	13–3	0.07	31%	28 Mar →
overpass	13–6	-0.01	22%	28 Mar →
nuke	13–16	-0.06	26%	21 Mar →
dust2	13–2	0.08	44%	21 Mar →
inferno	13–2	0.09	44%	18 Mar →
anubis	15–19	0.02	20%	17 Mar →
inferno	13–11	0.08	30%	28 Feb →
inferno	11–13	0.01	21%	13 Feb →
overpass	14–16	-0.01	26%	13 Feb →
ancient	13–6	0.07	33%	30 Jan →
mirage	2–13	0.00	34%	26 Jan →
dust2	10–13	0.01	28%	26 Jan →
inferno	5–13	-0.03	19%	18 Jan →
dust2	13–7	0.04	24%	12 Jan →
ancient	10–13	0.03	27%	3 Jan →
nuke	13–7	0.07	28%	27 Dec →
ancient	9–13	0.01	21%	27 Dec →
overpass	13–11	0.08	29%	27 Dec →
inferno	5–13	0.01	34%	19 Dec →
dust2	13–8	0.02	21%	14 Dec →
mirage	5–13	-0.01	23%	13 Dec →
inferno	13–11	0.03	25%	13 Dec →
train	13–6	0.01	22%	13 Dec →
nuke	13–11	0.03	24%	13 Dec →
ancient	13–5	0.07	22%	12 Dec →
inferno	13–10	0.01	30%	5 Dec →
nuke	13–10	0.07	32%	3 Oct →
train	7–13	-0.00	28%	27 Sept →
train	10–13	-0.01	18%	19 Sept →
dust2	11–12	0.00	21%	31 Aug →
train	13–10	0.00	41%	19 Aug →
overpass	9–13	-0.04	17%	15 Aug →
brewery	9–6	0.08	14%	2 Aug →
nuke	13–5	0.04	18%	30 Jul →
inferno	13–8	0.00	30%	17 Jul →
overpass	16–19	-0.01	25%	17 Jul →
train	10–13	0.05	33%	1 Jul →
inferno	13–9	0.15	33%	21 Jun →
nuke	13–11	0.00	14%	15 Jun →
ancient	11–13	-0.03	30%	12 Jun →
nuke	10–13	-0.00	29%	9 Jun →
jura	12–12	0.11	21%	6 Jun →
nuke	16–13	0.05	23%	1 Jun →
train	7–13	-0.04	25%	1 Jun →
inferno	13–10	0.01	17%	27 May →
nuke	13–8	0.03	33%	24 May →
train	13–2	0.09	23%	16 May →
ancient	13–3	-0.02	26%	16 May →
ancient	22–19	-0.03	20%	16 May →
ancient	13–11	0.07	24%	4 May →
ancient	13–7	-0.05	27%	24 Apr →
ancient	13–11	-0.05	19%	20 Apr →
dust2	12–16	-0.00	20%	20 Apr →
train	13–11	0.01	20%	3 Apr →
inferno	11–13	0.02	26%	16 Mar →