Kyuxor — CS2 Stats

76561199593852038[U:1:1633586310]Steam profile ↗

766Tracked matches72%Win rate2024Tracked since

CSDB Rating7.1 StrongAggressive Rifler

Premier CS Rating22,745Top 50% of 819 CSDB-tracked playersPink band · top ~5.5% of ranked players (population est.)

CSDB Leaderboard#5134 of 18552 tracked

FaceitLevel 10Top 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim86

Positioning65

Utility40

0–100 skill scores via Leetify.

Recent form

STEADY69–26–5Last 10069%Win rateWTWWLLWWWL

Last 10 vs previous 10: -20pp win rate · +0.02 avg rating

Player DNA

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

Aim8.6

Aggression10.0

Utility4.0

Positioning6.5

Opening Duels4.8

Clutch6.0

Sharp aimerLimited utility dependence

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 sh1ro 92% playstyle similarity

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

Where you differ: lower utility contribution.

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 86 — the mechanical foundation is a clear strength.

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 588ms 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

Aim8.6

Positioning6.5

Utility4.0

Mechanics6.5

Opening Duels4.8

Win Impact10.0

Composite 7.1/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.03+0.01

first ⅓ avg 0.03 → last ⅓ avg 0.03

Reaction time587ms−78ms

first ⅓ avg 665ms → last ⅓ avg 587ms

Headshot accuracy28.1%−3.0%

first ⅓ avg 31.1% → last ⅓ avg 28.1%

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

0.18Best rating — dust2 6–1

13–0Biggest win — inferno

13Longest win streak

7–1In matches decided by ≤2 rounds

3Overtime games

Map breakdown

officeBest map · 100% over 5trainWeakest map · 40% over 5

Map	Grade	Played	Record	Win rate	Avg rating
inferno	S	33	24–9	73%	0.02
anubis	B	13	7–6	54%	0.02
nuke	A	8	5–3	63%	0.03
mirage	S	6	5–1	83%	0.03
cache	B	6	3–3	50%	0.03
office	S	5	5–0	100%	0.02
train	C	5	2–3	40%	0.01
overpass	A	5	3–2	60%	0.01
dust2	—	4	3–1	75%	0.07
ancient	—	4	3–1	75%	0.01
vertigo	—	3	3–0	100%	0.06
boulder	—	2	1–1	50%	0.02
fachwerk	—	2	1–1	50%	0.02
warden	—	2	2–0	100%	0.05
shelter	—	1	1–0	100%	0.12
alpine	—	1	1–0	100%	0.08

Across the last 100 tracked matches.

Faceit stats

Combat

162Matches

57%Win rate

1.54Avg K/D

94.1ADR

59%Headshot %

Clutches & streaks

50%1v1 clutch win

30%1v2 clutch win

15Longest win streak

Recent Faceit resultsWLLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Anubis	42	62%	1.48	18.6
Inferno	27	59%	1.74	21.2
Vertigo	26	62%	1.49	20.6
Nuke	22	55%	1.76	21.1
Ancient	20	55%	1.49	18.4
Mirage	15	47%	1.33	15.5
Dust2	9	44%	1.20	19.0
Overpass	1	100%	2.09	23.0

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.

28.3%Headshot accuracy

36.9%Accuracy (enemy spotted)

41.6%Spray accuracy

79.4%Counter-strafing

9.6°Preaim

588msReaction time

45.1%T opening success

53.4%CT opening success

0.36Enemies flashed / flash

5.1%Flash assists

12.89HE damage / grenade

2.06Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.3604 — below the 0.5 mark we flag
Grenade Lineups →

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.

40% 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
shelter	13–2	0.12	41%	25 Jul →
boulder	12–12	-0.00	26%	25 Jul →
boulder	13–10	0.04	29%	24 Jul →
fachwerk	13–10	0.01	42%	24 Jul →
anubis	5–13	0.03	30%	24 Jul →
fachwerk	2–8	0.02	26%	21 Jul →
inferno	13–3	0.09	30%	22 Jun →
inferno	11–8	0.03	16%	22 Jun →
office	13–5	0.07	31%	21 Jun →
inferno	7–13	0.11	24%	17 Jun →
train	9–13	0.02	28%	17 Jun →
inferno	13–10	0.06	22%	13 Jun →
mirage	13–9	-0.03	18%	4 Jun →
cache	13–9	0.01	36%	4 Jun →
office	13–11	0.03	40%	4 Jun →
inferno	13–4	0.12	39%	3 Jun →
inferno	13–8	0.01	24%	3 Jun →
vertigo	13–11	0.02	19%	3 Jun →
inferno	10–13	0.03	30%	28 May →
dust2	13–7	0.05	33%	28 May →
inferno	13–6	-0.01	21%	27 May →
inferno	11–4	0.08	25%	27 May →
cache	1–11	-0.05	19%	24 May →
inferno	13–0	0.02	30%	24 May →
nuke	7–13	-0.07	24%	24 May →
inferno	13–8	0.02	25%	20 May →
inferno	3–13	-0.01	33%	20 May →
inferno	13–7	0.12	26%	17 May →
inferno	13–9	-0.02	31%	16 May →
inferno	13–11	-0.02	30%	16 May →
cache	6–13	0.08	31%	15 May →
cache	13–10	-0.02	27%	6 May →
cache	12–12	0.11	23%	3 May →
cache	13–7	0.03	28%	29 Apr →
inferno	13–9	0.10	31%	25 Apr →
overpass	9–13	-0.00	30%	25 Apr →
anubis	13–11	0.01	45%	22 Apr →
office	13–9	-0.01	32%	18 Apr →
anubis	13–7	0.05	50%	18 Apr →
inferno	13–2	0.09	25%	18 Apr →
train	13–6	0.03	24%	18 Apr →
inferno	13–2	0.02	28%	15 Apr →
dust2	6–1	0.18	38%	15 Apr →
nuke	4–3	-0.12	0%	15 Apr →
mirage	13–6	0.00	19%	15 Apr →
vertigo	13–2	0.10	33%	14 Apr →
mirage	13–7	0.06	31%	13 Apr →
vertigo	13–6	0.06	34%	13 Apr →
ancient	13–5	-0.02	38%	27 Mar →
nuke	1–13	-0.04	21%	27 Mar →
ancient	13–7	0.04	42%	27 Mar →
anubis	16–12	0.08	19%	26 Mar →
inferno	13–6	-0.07	37%	18 Mar →
anubis	13–7	0.12	38%	3 Mar →
mirage	13–2	0.12	40%	3 Mar →
inferno	2–3	0.01	40%	26 Feb →
overpass	4–10	-0.04	17%	21 Feb →
dust2	13–5	-0.03	21%	21 Feb →
inferno	16–12	0.08	25%	18 Feb →
anubis	10–13	-0.06	27%	18 Feb →
nuke	13–11	0.07	29%	14 Feb →
anubis	5–13	-0.00	36%	14 Feb →
inferno	9–13	-0.03	38%	6 Feb →
overpass	13–2	0.03	25%	6 Feb →
inferno	13–1	-0.03	38%	6 Feb →
anubis	4–13	-0.09	26%	3 Feb →
inferno	0–13	-0.10	75%	3 Feb →
office	13–3	0.00	30%	1 Feb →
ancient	8–13	-0.01	34%	1 Feb →
anubis	10–13	0.01	26%	24 Jan →
anubis	15–15	-0.04	23%	24 Jan →
inferno	13–9	0.01	30%	24 Jan →
anubis	13–9	0.05	40%	24 Jan →
warden	13–6	-0.01	31%	23 Jan →
alpine	13–4	0.08	32%	23 Jan →
anubis	13–7	0.04	22%	23 Jan →
inferno	9–13	-0.01	23%	23 Jan →
anubis	13–3	0.09	38%	23 Jan →
warden	13–0	0.11	67%	23 Jan →
nuke	13–1	0.14	56%	23 Jan →
inferno	13–8	0.03	28%	18 Jan →
inferno	13–1	0.06	40%	18 Jan →
mirage	0–4	-0.01	0%	12 Dec →
office	13–9	0.00	41%	12 Dec →
nuke	12–12	0.06	24%	12 Dec →
overpass	13–7	0.07	38%	27 Sept →
nuke	13–1	0.17	24%	27 Sept →
train	13–6	0.00	36%	27 Sept →
ancient	13–10	0.03	32%	27 Sept →
mirage	13–11	0.02	35%	7 Sept →
dust2	7–13	0.06	31%	28 Aug →
inferno	13–8	0.12	25%	5 Aug →
inferno	4–13	-0.11	50%	3 Aug →
inferno	2–13	-0.04	26%	3 Aug →
inferno	4–0	-0.08	0%	3 Aug →
overpass	13–7	-0.01	26%	3 Aug →
train	10–13	0.01	29%	3 Aug →
train	12–12	-0.00	31%	26 Jul →
inferno	13–10	0.03	29%	25 Jul →
nuke	13–8	0.01	29%	25 Jul →