3vvvs — CS2 Stats

76561197984563062[U:1:24297334]✓ No bans

1,351Tracked matches41%Win rate2020Tracked since

CSDB Rating5.7 SolidHybrid Rifler

FaceitLevel 4Top 81.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim67

Positioning56

Utility61

0–100 skill scores via Leetify.

Recent form

STEADY44–53–3Last 10044%Win rateWLWLLLTWLW

Last 10 vs previous 10: +0pp win rate · +0.03 avg rating

Player DNA

Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.

Aim6.7

Aggression7.4

Utility6.1

Positioning5.6

Opening Duels3.2

Clutch0.0

Strong CT-side opener

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 b1t 92% playstyle similarity

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

Where you differ: 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 52% on CT to 33% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 652ms 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

Aim6.7

Positioning5.6

Utility6.1

Mechanics7.2

Opening Duels3.2

Win Impact2.1

Composite 5.7/10 (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 rating0.02−0.02

first ⅓ avg 0.04 → last ⅓ avg 0.02

Reaction time657ms+1ms

first ⅓ avg 656ms → last ⅓ avg 657ms

Headshot accuracy13.5%−0.1%

first ⅓ avg 13.6% → last ⅓ avg 13.5%

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 — dust2 13–2

13–2Biggest win — inferno

5Longest win streak

6–9In matches decided by ≤2 rounds

12Overtime games

Map breakdown

anubisBest map · 60% over 15ancientWeakest map · 35% over 20

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	33	15–18	45%	0.04
ancient	C	20	7–13	35%	0.02
anubis	A	15	9–6	60%	0.03
inferno	C	14	6–8	43%	0.01
cache	C	11	4–7	36%	-0.00
nuke	—	3	1–2	33%	0.00
overpass	—	2	1–1	50%	0.05
mirage	—	2	1–1	50%	0.07

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (35% over 20). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

29Matches

52%Win rate

1.26Avg K/D

66.2ADR

35%Headshot %

Clutches & streaks

0%1v1 clutch win

0%1v2 clutch win

4Longest win streak

Recent Faceit resultsLLWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	2	100%	2.11	16.5
Nuke	2	50%	0.88	7.5
Inferno	2	100%	0.94	17.0
Mirage	1	100%	0.94	16.0
Dust2	1	0%	0.61	11.0
Anubis	1	0%	0.58	11.0

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.

13.3%Headshot accuracy

38.4%Accuracy (enemy spotted)

37.5%Spray accuracy

82.4%Counter-strafing

9.5°Preaim

652msReaction time

33.2%T opening success

52.3%CT opening success

0.58Enemies flashed / flash

9.0%Flash assists

13.26HE damage / grenade

8.00Flashes / 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.

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 13.3012% — below the 15% mark we flag
Aim Training →
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 33.213% — below the 40% mark we flag

Spend your practice time on Ancient

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

35% win rate across 20 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	13–10	0.10	21%	29 Aug →
cache	6–13	0.05	16%	29 Aug →
inferno	13–2	0.08	17%	29 Aug →
dust2	14–16	0.01	15%	29 Aug →
inferno	9–13	-0.05	10%	23 Aug →
dust2	8–13	-0.03	10%	23 Aug →
inferno	15–15	0.03	7%	22 Aug →
ancient	13–10	0.11	12%	15 Aug →
inferno	7–13	-0.02	13%	15 Aug →
dust2	13–9	0.06	18%	15 Aug →
cache	6–13	0.05	11%	15 Aug →
ancient	13–2	0.07	22%	26 Jul →
inferno	11–13	0.01	9%	26 Jul →
dust2	10–13	-0.05	12%	26 Jul →
anubis	13–5	0.01	9%	25 Jul →
ancient	11–13	-0.02	11%	24 Jul →
nuke	13–7	0.05	13%	24 Jul →
cache	7–13	-0.05	10%	22 Jul →
anubis	13–10	0.02	12%	19 Jul →
nuke	8–13	-0.02	11%	19 Jul →
ancient	13–6	0.07	10%	17 Jul →
dust2	5–13	-0.02	15%	11 Jul →
cache	13–4	-0.02	14%	11 Jul →
dust2	6–13	-0.01	19%	11 Jul →
anubis	13–8	0.02	7%	4 Jul →
dust2	8–13	0.13	21%	4 Jul →
dust2	7–13	-0.01	25%	4 Jul →
ancient	6–13	-0.06	11%	21 Jun →
dust2	13–10	0.07	12%	21 Jun →
ancient	3–13	-0.02	14%	31 May →
ancient	13–5	0.13	18%	31 May →
anubis	4–13	-0.02	16%	31 May →
ancient	7–13	-0.00	7%	13 May →
inferno	11–13	0.00	12%	13 May →
cache	13–3	0.04	23%	10 May →
overpass	3–13	-0.04	14%	10 May →
anubis	13–10	0.08	16%	10 May →
ancient	13–9	0.05	15%	10 May →
cache	0–13	-0.03	54%	9 May →
anubis	13–8	0.02	11%	9 May →
ancient	8–13	0.02	10%	9 May →
dust2	15–15	0.01	12%	9 May →
dust2	6–13	-0.03	18%	9 May →
cache	9–13	-0.01	11%	7 May →
dust2	10–13	0.04	15%	7 May →
inferno	13–10	-0.00	19%	7 May →
dust2	15–15	0.03	21%	6 May →
anubis	13–6	0.03	18%	6 May →
cache	2–13	-0.07	17%	2 May →
dust2	13–10	0.13	17%	2 May →
anubis	11–13	0.04	11%	2 May →
ancient	14–16	0.03	13%	2 May →
cache	8–13	-0.02	5%	2 May →
cache	13–10	0.07	19%	30 Apr →
cache	13–9	-0.00	17%	30 Apr →
ancient	7–13	0.00	13%	26 Apr →
dust2	4–13	-0.06	12%	26 Apr →
mirage	8–13	-0.00	12%	26 Apr →
dust2	5–13	0.02	18%	26 Apr →
dust2	10–13	0.01	12%	26 Apr →
dust2	13–7	0.08	16%	19 Apr →
inferno	13–11	0.09	11%	19 Apr →
dust2	13–5	0.10	18%	19 Apr →
anubis	16–13	0.05	12%	19 Apr →
overpass	13–6	0.14	13%	18 Apr →
ancient	8–13	-0.04	7%	18 Apr →
dust2	7–13	0.09	18%	18 Apr →
ancient	10–13	0.04	7%	18 Apr →
dust2	13–16	-0.04	12%	11 Apr →
inferno	13–11	-0.05	19%	11 Apr →
anubis	11–13	0.00	21%	11 Apr →
ancient	6–13	0.06	19%	11 Apr →
inferno	13–3	0.07	9%	4 Apr →
anubis	13–16	0.07	8%	4 Apr →
dust2	13–2	0.06	16%	4 Apr →
dust2	13–6	0.07	25%	4 Apr →
anubis	9–13	-0.07	7%	29 Mar →
anubis	16–14	0.04	9%	29 Mar →
dust2	13–4	0.07	17%	29 Mar →
inferno	13–11	0.01	16%	29 Mar →
dust2	13–8	0.08	14%	29 Mar →
inferno	13–16	-0.01	14%	28 Mar →
dust2	9–13	0.03	17%	28 Mar →
ancient	11–13	-0.01	6%	28 Mar →
dust2	13–11	0.08	14%	28 Mar →
nuke	8–13	-0.02	9%	22 Mar →
ancient	8–13	-0.09	18%	22 Mar →
dust2	13–2	0.07	17%	21 Mar →
anubis	11–13	0.06	12%	21 Mar →
inferno	8–13	0.06	9%	21 Mar →
dust2	13–2	0.15	7%	21 Mar →
ancient	16–12	0.07	7%	20 Mar →
ancient	13–7	0.02	13%	20 Mar →
dust2	13–16	0.03	16%	14 Mar →
inferno	8–13	-0.01	14%	14 Mar →
ancient	10–13	0.03	23%	1 Mar →
dust2	13–11	0.09	14%	1 Mar →
dust2	13–6	0.11	11%	1 Mar →
anubis	13–7	0.08	18%	1 Mar →
mirage	13–3	0.13	9%	1 Mar →