VeXOR — CS2 Stats

DK76561198794816714[U:1:834550986]Steam profile ↗✓ No bans

786Tracked matches50%Win rate2025Tracked since

CSDB Rating3.9 Learning

FaceitLevel 5 · 881 ELOTop 67.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim44

Positioning50

Utility48

0–100 skill scores via Leetify.

Recent form

STEADY54–46Last 10054%Win rateLWWWWWLLLL

Last 10 vs previous 10: +0pp win rate · +0.04 avg rating

Player DNA

Aim4.4

Aggression4.7

Utility4.8

Positioning5.0

Opening Duels1.5

Clutch3.2

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 84% playstyle similarity

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

Where you differ: lower utility contribution; 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 27% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 669ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 70% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim4.4

Positioning5.0

Utility4.8

Mechanics4.4

Opening Duels1.8

Win Impact5.0

Composite 3.9/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.00+0.03

first ⅓ avg -0.03 → last ⅓ avg -0.00

Reaction time668ms−9ms

first ⅓ avg 677ms → last ⅓ avg 668ms

Headshot accuracy14.2%+2.0%

first ⅓ avg 12.2% → last ⅓ avg 14.2%

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

0.22Best rating — mirage 13–5

13–1Biggest win — ancient

5Longest win streak

8–8In matches decided by ≤2 rounds

16Overtime games

Map breakdown

nukeBest map · 64% over 11infernoWeakest map · 40% over 10

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	20	9–11	45%	0.00
ancient	A	20	11–9	55%	-0.03
mirage	A	16	10–6	63%	0.02
overpass	B	12	6–6	50%	-0.02
nuke	A	11	7–4	64%	-0.01
inferno	C	10	4–6	40%	-0.04
anubis	A	8	5–3	63%	0.01
cache	—	3	2–1	67%	0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (40% over 10). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

780Matches

51%Win rate

0.93Avg K/D

78.3ADR

37%Headshot %

Clutches & streaks

36%1v1 clutch win

20%1v2 clutch win

15Longest win streak

Recent Faceit resultsLLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	185	52%	1.06	15.3
Mirage	161	51%	0.98	14.8
Ancient	143	49%	0.86	14.4
Nuke	90	51%	0.80	13.5
Overpass	78	58%	0.87	14.1
Inferno	52	31%	0.72	12.4
Anubis	45	53%	1.08	16.5
Cache	26	58%	0.86	14.0

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.

14.5%Headshot accuracy

34.1%Accuracy (enemy spotted)

40.3%Spray accuracy

69.6%Counter-strafing

12.0°Preaim

669msReaction time

27.3%T opening success

44.8%CT opening success

0.56Enemies flashed / flash

6.0%Flash assists

8.62HE damage / grenade

6.14Flashes / 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
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 12.0022° — above the 12° mark we flag
Aim Training →
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 14.454% — below the 15% mark we flag
Aim Training →

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.

40% win rate across 10 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
nuke	11–13	-0.06	14%	22 Jun →
mirage	13–8	0.08	46%	15 Jun →
mirage	13–4	0.07	43%	15 Jun →
dust2	13–2	0.11	36%	15 Jun →
mirage	13–4	0.10	39%	15 Jun →
dust2	13–2	0.09	30%	15 Jun →
inferno	5–13	-0.03	9%	13 Jun →
overpass	9–13	-0.05	7%	11 Jun →
dust2	10–13	0.02	23%	9 Jun →
nuke	16–19	-0.06	10%	9 Jun →
mirage	8–13	-0.04	12%	8 Jun →
dust2	8–13	-0.05	12%	7 Jun →
ancient	13–6	0.03	12%	7 Jun →
nuke	16–13	-0.01	15%	6 Jun →
mirage	13–4	0.00	7%	5 Jun →
cache	13–10	0.03	10%	4 Jun →
ancient	4–13	-0.05	3%	3 Jun →
dust2	12–16	-0.06	17%	3 Jun →
nuke	13–10	0.01	11%	3 Jun →
mirage	11–13	-0.02	18%	31 May →
nuke	8–13	0.04	13%	30 May →
cache	13–9	0.04	10%	28 May →
mirage	10–13	-0.03	8%	25 May →
mirage	13–10	-0.03	0%	24 May →
ancient	9–13	0.01	1%	24 May →
overpass	13–3	-0.01	7%	23 May →
dust2	13–2	-0.00	13%	20 May →
ancient	13–10	-0.02	11%	19 May →
overpass	10–13	-0.07	10%	18 May →
overpass	10–13	-0.05	7%	18 May →
ancient	13–11	-0.02	6%	16 May →
cache	5–13	-0.07	5%	16 May →
mirage	14–16	-0.08	5%	15 May →
ancient	13–1	0.01	11%	13 May →
dust2	13–7	-0.02	9%	13 May →
mirage	13–9	0.02	8%	12 May →
dust2	3–13	-0.04	14%	12 May →
dust2	11–13	0.00	15%	12 May →
dust2	2–13	-0.05	6%	7 May →
ancient	13–9	-0.06	7%	6 May →
dust2	13–3	-0.01	11%	5 May →
mirage	13–6	0.03	19%	4 May →
dust2	16–13	-0.03	10%	4 May →
overpass	13–6	-0.05	14%	22 Apr →
ancient	13–16	-0.00	14%	21 Apr →
overpass	13–11	0.02	10%	21 Apr →
anubis	9–13	-0.00	8%	16 Apr →
ancient	8–13	-0.03	13%	16 Apr →
ancient	13–11	0.02	9%	16 Apr →
nuke	19–15	-0.02	10%	16 Apr →
dust2	6–13	-0.05	17%	12 Apr →
anubis	13–9	0.09	28%	12 Apr →
mirage	13–2	0.04	23%	9 Apr →
overpass	7–13	-0.03	2%	9 Apr →
overpass	25–23	0.01	11%	8 Apr →
overpass	16–13	-0.06	5%	8 Apr →
overpass	13–10	0.15	31%	8 Apr →
dust2	13–9	-0.07	10%	7 Apr →
ancient	18–22	-0.06	10%	7 Apr →
anubis	10–13	-0.04	2%	5 Apr →
anubis	13–6	0.09	33%	5 Apr →
mirage	13–5	0.22	42%	5 Apr →
anubis	13–6	0.07	39%	5 Apr →
dust2	13–5	0.14	35%	4 Apr →
dust2	13–3	0.22	44%	4 Apr →
mirage	11–13	-0.03	20%	4 Apr →
nuke	4–13	-0.05	13%	4 Apr →
ancient	8–13	-0.08	5%	3 Apr →
ancient	13–10	-0.05	11%	3 Apr →
dust2	9–13	-0.06	11%	3 Apr →
nuke	19–17	-0.04	9%	2 Apr →
inferno	9–13	-0.06	12%	2 Apr →
ancient	13–4	-0.01	8%	29 Mar →
ancient	16–14	-0.03	14%	29 Mar →
ancient	13–11	-0.06	10%	29 Mar →
inferno	13–8	0.03	15%	26 Mar →
ancient	13–9	-0.02	9%	25 Mar →
dust2	11–13	-0.07	20%	24 Mar →
inferno	2–13	-0.04	21%	23 Mar →
ancient	5–13	-0.01	13%	22 Mar →
mirage	13–6	-0.04	19%	21 Mar →
nuke	25–21	-0.02	12%	19 Mar →
inferno	13–3	0.03	8%	11 Mar →
dust2	12–16	-0.05	20%	11 Mar →
ancient	5–13	-0.03	9%	7 Mar →
inferno	5–13	-0.05	17%	3 Mar →
inferno	16–14	-0.06	12%	2 Mar →
mirage	11–13	-0.02	17%	27 Feb →
anubis	13–9	-0.05	11%	26 Feb →
nuke	16–12	-0.01	13%	24 Feb →
ancient	4–13	-0.08	11%	24 Feb →
inferno	7–13	-0.06	10%	23 Feb →
anubis	13–9	-0.01	11%	19 Feb →
overpass	11–13	-0.05	11%	18 Feb →
inferno	13–8	-0.05	3%	16 Feb →
anubis	9–13	-0.04	11%	15 Feb →
overpass	10–13	-0.04	9%	15 Feb →
nuke	13–6	0.05	9%	13 Feb →
inferno	6–13	-0.08	9%	11 Feb →
dust2	9–13	0.00	22%	11 Feb →