vant — CS2 Stats

76561198246488850[U:1:286223122]Steam profile ↗

384Tracked matches63%Win rate2020Tracked since

CSDB Rating7.4 StrongAggressive Rifler

FaceitLevel 10 · 2,004 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim92

Positioning63

Utility35

0–100 skill scores via Leetify.

Recent form

STEADY54–43–3Last 10054%Win rateLWWLWLWLWL

Last 10 vs previous 10: -20pp 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

Utility3.5

Positioning6.3

Opening Duels5.5

Clutch2.6

Sharp aimerExcellent counter-strafing

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 device 90% playstyle similarity

Most alike: positioning profile, opening-fight frequency.

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 92 — the mechanical foundation is a clear strength.

Counter-strafing. 91% of shots taken properly stopped — movement discipline most players never reach.

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. 646ms 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

Aim9.2

Positioning6.3

Utility3.5

Mechanics9.0

Opening Duels5.5

Win Impact9.4

Composite 7.4/10 (Strong), 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 rating0.02+0.00

first ⅓ avg 0.02 → last ⅓ avg 0.02

Reaction time637ms−46ms

first ⅓ avg 683ms → last ⅓ avg 637ms

Headshot accuracy40.2%−2.1%

first ⅓ avg 42.3% → last ⅓ avg 40.2%

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

0.18Best rating — ancient 13–6

13–2Biggest win — dust2

7Longest win streak

9–11In matches decided by ≤2 rounds

14Overtime games

Map breakdown

overpassBest map · 80% over 5infernoWeakest map · 41% over 17

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	34	20–14	59%	0.02
mirage	B	19	9–10	47%	0.01
inferno	C	17	7–10	41%	0.01
nuke	B	10	5–5	50%	0.03
ancient	B	8	4–4	50%	0.07
overpass	S	5	4–1	80%	0.05
train	—	4	4–0	100%	0.02
anubis	—	2	1–1	50%	0.09
golden	—	1	0–1	0%	-0.02

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (41% over 17). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

192Matches

58%Win rate

1.30Avg K/D

91.7ADR

76%Headshot %

Clutches & streaks

33%1v1 clutch win

25%1v2 clutch win

6Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	57	65%	1.40	21.0
Mirage	45	60%	1.27	20.5
Inferno	20	45%	1.22	20.2
Ancient	19	47%	1.32	19.4
Nuke	15	60%	1.14	18.9
Train	6	50%	1.38	26.3
Overpass	4	25%	1.11	16.8
Vertigo	3	67%	1.16	17.3

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.

40.1%Headshot accuracy

35.3%Accuracy (enemy spotted)

37.5%Spray accuracy

90.5%Counter-strafing

9.4°Preaim

646msReaction time

55.8%T opening success

48.0%CT opening success

0.43Enemies flashed / flash

2.6%Flash assists

6.04HE damage / grenade

6.76Flashes / 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 0.4341 — below the 0.5 mark we flag
Grenade Lineups →

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.

41% win rate across 17 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
dust2	7–13	-0.06	38%	5 Jun →
inferno	13–7	0.08	63%	5 Jun →
dust2	13–6	0.06	52%	5 Jun →
mirage	3–13	-0.05	41%	15 May →
mirage	13–6	0.07	56%	15 May →
dust2	8–13	0.06	37%	8 May →
ancient	13–10	0.03	31%	8 May →
ancient	5–13	0.03	63%	8 May →
nuke	13–9	0.07	44%	25 Apr →
inferno	0–13	-0.07	34%	15 Jan →
dust2	13–8	0.02	26%	28 Dec →
dust2	16–13	0.06	44%	26 Dec →
dust2	13–8	0.03	62%	26 Dec →
inferno	6–13	-0.03	43%	25 Dec →
mirage	13–9	0.01	42%	25 Dec →
dust2	13–9	0.01	40%	25 Dec →
nuke	17–19	0.02	22%	25 Dec →
dust2	13–9	0.01	48%	25 Dec →
mirage	9–13	0.00	36%	24 Dec →
inferno	13–11	0.02	27%	24 Dec →
mirage	16–13	0.12	30%	23 Dec →
inferno	6–13	-0.08	32%	23 Dec →
train	25–23	0.01	41%	23 Dec →
nuke	13–8	0.06	25%	23 Dec →
nuke	2–13	-0.04	67%	22 Dec →
nuke	13–6	0.13	38%	22 Dec →
dust2	13–7	0.04	38%	21 Dec →
ancient	7–13	0.01	32%	21 Dec →
dust2	13–4	-0.02	44%	18 Dec →
dust2	16–14	-0.02	36%	18 Dec →
inferno	14–16	-0.01	36%	17 Dec →
ancient	6–13	-0.01	32%	16 Dec →
ancient	13–6	0.18	26%	14 Dec →
mirage	13–11	0.03	42%	14 Dec →
dust2	15–19	0.12	45%	12 Dec →
dust2	5–13	-0.05	25%	12 Dec →
mirage	10–13	-0.00	37%	11 Dec →
mirage	13–16	0.02	36%	11 Dec →
dust2	13–9	0.03	35%	11 Dec →
nuke	13–7	-0.03	50%	10 Dec →
mirage	12–16	0.02	47%	9 Dec →
overpass	5–13	0.02	37%	9 Dec →
mirage	13–9	0.05	58%	7 Dec →
dust2	11–13	0.06	45%	5 Dec →
dust2	13–4	-0.02	54%	4 Dec →
inferno	13–7	0.12	57%	2 Dec →
dust2	13–10	0.01	59%	2 Dec →
mirage	10–13	-0.05	35%	2 Dec →
dust2	11–13	0.05	37%	28 Nov →
dust2	4–13	-0.00	45%	28 Nov →
overpass	13–5	0.07	66%	28 Nov →
inferno	11–13	-0.01	32%	28 Nov →
dust2	13–8	0.17	41%	18 Nov →
dust2	8–13	0.09	45%	18 Nov →
dust2	13–4	0.06	56%	18 Nov →
dust2	13–2	0.05	48%	18 Nov →
dust2	13–11	0.10	40%	18 Nov →
ancient	13–6	0.06	61%	17 Nov →
mirage	13–8	0.02	46%	17 Nov →
mirage	16–12	-0.03	40%	13 Nov →
inferno	13–11	0.02	40%	13 Nov →
inferno	10–13	-0.05	63%	12 Nov →
mirage	11–13	-0.01	30%	11 Nov →
anubis	12–12	0.06	66%	11 Nov →
inferno	13–10	0.08	43%	11 Nov →
ancient	6–13	0.09	52%	11 Nov →
train	13–11	0.01	55%	11 Nov →
mirage	6–13	0.05	33%	10 Nov →
inferno	12–12	0.05	39%	10 Nov →
dust2	12–12	0.03	50%	10 Nov →
inferno	13–7	0.12	48%	5 Nov →
dust2	13–10	0.02	51%	5 Nov →
train	13–8	0.05	51%	5 Nov →
dust2	13–3	-0.02	48%	5 Nov →
overpass	13–5	0.12	45%	5 Nov →
dust2	11–13	-0.01	43%	5 Nov →
dust2	13–5	-0.06	42%	31 Oct →
dust2	13–16	0.02	37%	31 Oct →
dust2	8–13	-0.01	39%	29 Oct →
mirage	13–10	0.11	52%	28 Oct →
nuke	13–7	0.06	60%	28 Oct →
train	13–6	0.02	57%	28 Oct →
inferno	9–13	0.00	43%	27 Oct →
inferno	13–11	0.01	49%	27 Oct →
dust2	16–12	-0.01	45%	27 Oct →
overpass	13–10	0.01	37%	27 Oct →
nuke	10–13	0.05	38%	24 Oct →
nuke	10–13	0.00	40%	23 Oct →
inferno	12–16	0.00	41%	19 Oct →
overpass	13–8	0.03	38%	19 Oct →
anubis	13–11	0.12	55%	18 Oct →
ancient	13–4	0.15	56%	18 Oct →
golden	10–13	-0.02	54%	18 Oct →
inferno	9–13	-0.07	20%	12 Jun →
mirage	13–4	-0.04	24%	12 Jun →
nuke	11–13	0.01	31%	12 Jun →
dust2	11–13	-0.02	32%	12 Jun →
dust2	4–13	-0.01	29%	4 Jun →
mirage	11–13	-0.07	38%	4 Jun →
mirage	14–16	0.03	32%	3 Jun →