niqxz — CS2 Stats

76561198401444275[U:1:441178547]Steam profile ↗

1,463Tracked matches50%Win rate2020Tracked since

CSDB Rating6.0 SolidAggressive Rifler

FaceitLevel 8Top 31.2% of ranked FACEIT players

WingmanDistinguished Master Guardian

Ladder ranks via Leetify

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Performance scores

Aim76

Positioning47

Utility52

0–100 skill scores via Leetify.

Recent form

STEADY51–43–6Last 10051%Win rateLWLLTWLWWL

Last 10 vs previous 10: -10pp win rate · +0.02 avg rating

Player DNA

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

Aim7.6

Aggression6.8

Utility5.2

Positioning4.7

Opening Duels2.9

Clutch1.8

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 ropz 88% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

Where you differ: lower opening-duel success; 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. 625ms 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

Aim7.6

Positioning4.7

Utility5.2

Mechanics8.1

Opening Duels2.9

Win Impact5.0

Composite 6.0/10 (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-0.01+0.00

first ⅓ avg -0.01 → last ⅓ avg -0.01

Reaction time613ms−61ms

first ⅓ avg 673ms → last ⅓ avg 613ms

Headshot accuracy17.6%+0.1%

first ⅓ avg 17.5% → last ⅓ avg 17.6%

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

0.28Best rating — inferno 9–0

13–0Biggest win — inferno

7Longest win streak

6–7In matches decided by ≤2 rounds

8Overtime games

Map breakdown

overpassBest map · 89% over 9infernoWeakest map · 20% over 15

Map	Grade	Played	Record	Win rate	Avg rating
mirage	A	19	12–7	63%	-0.01
cache	A	17	10–7	59%	-0.00
inferno	D	15	3–12	20%	0.02
dust2	B	13	6–7	46%	-0.02
anubis	C	11	4–7	36%	-0.02
overpass	S	9	8–1	89%	0.01
ancient	C	8	3–5	38%	-0.01
nuke	—	3	2–1	67%	-0.02
train	—	3	2–1	67%	-0.03
poseidon	—	1	1–0	100%	0.06
vertigo	—	1	0–1	0%	0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (20% over 15). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

410Matches

55%Win rate

1.16Avg K/D

75.4ADR

38%Headshot %

Clutches & streaks

29%1v1 clutch win

30%1v2 clutch win

9Longest win streak

Recent Faceit resultsLWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	18	44%	1.06	14.3
Mirage	16	50%	0.93	15.0
Dust2	12	33%	0.81	13.2
Anubis	10	50%	0.85	13.3
Overpass	9	89%	1.26	15.9
Cache	9	67%	1.60	18.0
Ancient	7	57%	0.83	14.7
Vertigo	6	50%	0.96	13.8

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

35.0%Accuracy (enemy spotted)

41.3%Spray accuracy

86.6%Counter-strafing

9.0°Preaim

625msReaction time

39.7%T opening success

43.8%CT opening success

0.57Enemies flashed / flash

6.6%Flash assists

10.68HE damage / grenade

8.38Flashes / 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 39.738% — 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.

20% win rate across 15 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
cache	0–3	-0.03	0%	28 Aug →
dust2	13–7	0.02	31%	26 Aug →
inferno	6–13	0.01	26%	25 Aug →
dust2	5–13	-0.04	21%	24 Aug →
inferno	12–12	0.04	13%	20 Aug →
dust2	13–8	0.02	22%	19 Aug →
cache	4–9	-0.13	25%	11 Aug →
poseidon	9–6	0.06	21%	7 Aug →
dust2	13–6	0.01	8%	7 Aug →
mirage	7–13	-0.06	11%	7 Aug →
dust2	8–13	-0.05	17%	23 Jul →
cache	4–13	-0.05	15%	23 Jul →
nuke	13–7	-0.00	27%	23 Jul →
anubis	12–12	-0.02	6%	23 Jul →
anubis	13–5	-0.03	17%	20 Jul →
cache	13–9	-0.03	9%	20 Jul →
mirage	13–7	-0.03	11%	20 Jul →
anubis	9–13	-0.02	15%	20 Jul →
inferno	13–1	-0.00	20%	2 Jul →
dust2	4–13	-0.05	21%	2 Jul →
dust2	13–8	-0.01	10%	2 Jul →
dust2	8–13	-0.06	27%	29 Jun →
anubis	13–10	0.06	19%	29 Jun →
anubis	10–13	0.01	11%	27 Jun →
nuke	1–11	-0.05	11%	27 Jun →
inferno	9–0	0.28	13%	27 Jun →
vertigo	7–9	0.04	14%	27 Jun →
cache	11–13	-0.03	11%	24 Jun →
cache	13–7	0.03	19%	18 Jun →
train	7–3	-0.07	25%	18 Jun →
cache	6–13	0.00	31%	18 Jun →
train	13–4	0.03	37%	18 Jun →
mirage	13–5	-0.04	16%	18 Jun →
inferno	6–13	-0.05	12%	18 Jun →
mirage	10–13	-0.06	11%	15 Jun →
mirage	13–9	-0.02	24%	18 May →
train	5–13	-0.07	13%	18 May →
anubis	13–2	0.02	6%	18 May →
ancient	13–10	0.02	21%	17 May →
cache	12–12	0.02	20%	17 May →
mirage	7–13	-0.05	14%	17 May →
mirage	9–13	-0.06	25%	11 May →
cache	22–19	-0.01	21%	10 May →
cache	9–13	-0.07	18%	10 May →
cache	13–10	-0.08	16%	10 May →
cache	13–10	0.03	16%	29 Apr →
cache	13–7	-0.01	16%	29 Apr →
overpass	13–11	0.03	19%	25 Apr →
cache	13–6	0.03	26%	25 Apr →
mirage	16–13	-0.03	9%	25 Apr →
overpass	13–11	0.02	24%	25 Apr →
dust2	5–13	-0.03	26%	25 Apr →
inferno	11–13	-0.02	26%	24 Apr →
cache	13–1	0.09	14%	24 Apr →
cache	13–11	0.01	24%	24 Apr →
cache	13–1	0.17	8%	24 Apr →
anubis	13–10	-0.02	13%	22 Apr →
overpass	13–4	0.08	24%	22 Apr →
mirage	9–13	-0.00	11%	22 Apr →
mirage	13–9	0.08	22%	21 Apr →
inferno	5–13	-0.02	23%	21 Apr →
mirage	13–3	0.04	27%	21 Apr →
inferno	0–4	-0.09	0%	20 Apr →
mirage	6–13	-0.05	10%	20 Apr →
nuke	13–8	-0.02	17%	20 Apr →
inferno	9–13	0.03	35%	20 Apr →
ancient	4–13	-0.04	11%	20 Apr →
overpass	13–4	0.01	11%	19 Apr →
inferno	15–15	0.06	16%	19 Apr →
mirage	13–7	0.05	17%	19 Apr →
inferno	11–13	-0.06	26%	19 Apr →
ancient	3–13	-0.07	9%	19 Apr →
mirage	13–2	0.07	11%	18 Apr →
ancient	13–10	-0.03	10%	18 Apr →
anubis	14–16	0.01	32%	18 Apr →
overpass	13–10	-0.04	13%	18 Apr →
overpass	13–2	0.02	17%	18 Apr →
dust2	13–7	0.10	27%	18 Apr →
dust2	1–7	-0.06	22%	15 Apr →
overpass	16–14	-0.02	13%	15 Apr →
mirage	13–6	-0.04	14%	15 Apr →
inferno	8–13	-0.03	16%	7 Apr →
anubis	6–10	-0.05	13%	6 Apr →
dust2	7–13	-0.07	29%	6 Apr →
inferno	3–13	0.00	21%	5 Apr →
inferno	13–0	0.16	12%	5 Apr →
mirage	13–5	-0.00	22%	5 Apr →
ancient	7–13	0.03	12%	5 Apr →
inferno	5–13	-0.05	35%	4 Apr →
overpass	13–11	-0.02	20%	4 Apr →
ancient	11–13	-0.05	10%	4 Apr →
mirage	13–4	0.10	24%	4 Apr →
anubis	2–8	-0.09	0%	1 Apr →
overpass	15–15	-0.01	16%	31 Mar →
anubis	5–13	-0.05	14%	30 Mar →
ancient	13–7	0.06	13%	28 Mar →
mirage	15–15	-0.05	21%	28 Mar →
dust2	13–11	-0.01	19%	28 Mar →
mirage	13–9	-0.06	22%	27 Mar →
ancient	14–16	0.02	22%	27 Mar →