Alvarh4 — CS2 Stats

76561198982171290[U:1:1021905562]

1,488Tracked matches57%Win rate2020Tracked since

CSDB Rating5.2 Developing

Premier CS Rating21,681Pink band · top ~6.7% of ranked players (population est.)

WingmanLegendary Eagle Master

Ladder ranks via Leetify

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Performance scores

Aim52

Positioning52

Utility62

0–100 skill scores via Leetify.

Recent form

STEADY48–52Last 10048%Win rateLWLWWLWWWL

Last 10 vs previous 10: +0pp win rate · +0.00 avg rating

Player DNA

Aim5.2

Aggression3.0

Utility6.2

Positioning5.2

Opening Duels0.0

Clutch3.4

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 82% playstyle similarity

Most alike: utility contribution, positioning profile.

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. 626ms 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

Aim5.2

Positioning5.2

Utility6.2

Mechanics5.6

Opening Duels0.1

Win Impact7.2

Composite 5.2/10 (Developing), 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 rating-0.02−0.02

first ⅓ avg 0.01 → last ⅓ avg -0.02

Reaction time635ms+41ms

first ⅓ avg 594ms → last ⅓ avg 635ms

Headshot accuracy14.0%−2.1%

first ⅓ avg 16.2% → last ⅓ avg 14.0%

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

0.14Best rating — ancient 13–4

13–1Biggest win — train

4Longest win streak

7–8In matches decided by ≤2 rounds

13Overtime games

Map breakdown

mirageBest map · 57% over 21dust2Weakest map · 30% over 10

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	21	10–11	48%	-0.01
mirage	A	21	12–9	57%	-0.01
inferno	C	19	7–12	37%	-0.01
nuke	A	16	9–7	56%	-0.00
dust2	D	10	3–7	30%	-0.01
anubis	C	9	4–5	44%	-0.01
train	—	3	2–1	67%	-0.01
overpass	—	1	1–0	100%	0.04

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

2,029Matches

51%Win rate

1.13Avg K/D

75.4ADR

40%Headshot %

Clutches & streaks

37%1v1 clutch win

15%1v2 clutch win

13Longest win streak

Recent Faceit resultsLWWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	222	53%	1.04	15.3
Ancient	206	50%	0.99	14.8
Inferno	165	46%	1.06	15.0
Nuke	150	56%	1.09	15.4
Anubis	48	42%	1.04	14.9
Train	48	58%	1.15	16.4
Dust2	30	30%	0.80	13.7
Overpass	9	56%	0.84	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.

14.2%Headshot accuracy

32.9%Accuracy (enemy spotted)

36.7%Spray accuracy

75.2%Counter-strafing

10.6°Preaim

626msReaction time

21.5%T opening success

30.5%CT opening success

0.63Enemies flashed / flash

10.9%Flash assists

9.66HE damage / grenade

8.83Flashes / 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 14.2379% — 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 21.543% — below the 40% mark we flag

Spend your practice time on Dust 2

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

30% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
ancient	10–13	-0.10	5%	10 Aug →
ancient	13–4	0.14	18%	24 Apr →
anubis	10–13	0.01	15%	24 Apr →
mirage	13–8	-0.05	24%	12 Apr →
nuke	13–7	-0.07	16%	12 Apr →
inferno	6–13	-0.02	11%	17 Mar →
anubis	13–10	-0.02	4%	16 Mar →
inferno	13–8	0.05	8%	16 Mar →
anubis	13–4	-0.01	10%	16 Mar →
ancient	7–13	-0.06	20%	16 Mar →
nuke	19–15	0.00	16%	15 Mar →
ancient	16–12	-0.01	13%	15 Mar →
inferno	13–6	0.06	20%	15 Mar →
ancient	4–13	-0.09	6%	15 Mar →
mirage	5–13	-0.00	19%	15 Mar →
mirage	13–4	-0.00	20%	15 Mar →
ancient	8–13	-0.03	23%	14 Mar →
ancient	13–7	-0.01	18%	14 Mar →
mirage	8–13	-0.07	7%	14 Mar →
inferno	13–6	-0.01	19%	13 Mar →
overpass	13–8	0.04	15%	13 Mar →
mirage	2–13	-0.09	4%	13 Mar →
dust2	13–4	0.07	18%	13 Mar →
inferno	13–7	-0.01	18%	13 Mar →
nuke	7–13	-0.04	19%	12 Mar →
inferno	5–13	-0.09	6%	11 Mar →
mirage	10–13	-0.06	20%	11 Mar →
anubis	13–10	0.03	14%	11 Mar →
mirage	13–11	0.03	15%	11 Mar →
nuke	10–13	0.01	8%	11 Mar →
inferno	7–13	-0.08	12%	10 Mar →
dust2	10–13	-0.07	10%	10 Mar →
anubis	9–13	-0.08	15%	9 Mar →
ancient	13–10	0.05	13%	9 Mar →
mirage	16–13	-0.02	18%	9 Mar →
dust2	9–13	0.00	20%	9 Mar →
inferno	7–13	-0.07	10%	9 Mar →
dust2	7–13	-0.08	14%	8 Mar →
inferno	13–10	0.02	10%	8 Mar →
ancient	19–16	0.04	15%	8 Mar →
nuke	16–13	0.01	12%	8 Mar →
mirage	13–10	-0.02	13%	7 Mar →
anubis	8–13	-0.05	13%	6 Mar →
ancient	13–7	0.00	29%	6 Mar →
anubis	13–10	0.06	24%	5 Mar →
ancient	13–10	-0.05	16%	5 Mar →
inferno	3–13	-0.01	33%	5 Mar →
ancient	13–6	0.02	14%	25 Feb →
mirage	6–13	-0.07	19%	21 Feb →
ancient	6–13	-0.06	15%	21 Feb →
mirage	6–13	-0.04	17%	18 Feb →
nuke	16–13	0.01	18%	18 Feb →
mirage	13–2	0.09	27%	18 Feb →
mirage	25–23	-0.03	21%	16 Feb →
inferno	9–13	-0.02	18%	12 Feb →
nuke	13–4	0.06	30%	12 Feb →
nuke	4–13	-0.06	18%	11 Feb →
inferno	10–13	-0.02	18%	11 Feb →
ancient	14–16	-0.03	14%	11 Feb →
dust2	18–22	0.01	20%	10 Feb →
mirage	11–13	0.05	15%	9 Feb →
dust2	11–13	-0.03	9%	8 Feb →
inferno	12–16	-0.02	15%	8 Feb →
mirage	13–8	-0.00	14%	8 Feb →
inferno	6–13	-0.06	17%	6 Feb →
ancient	13–16	-0.05	8%	6 Feb →
dust2	13–11	-0.01	18%	4 Feb →
ancient	11–13	-0.05	15%	4 Feb →
ancient	19–16	0.04	12%	3 Feb →
mirage	10–13	0.06	13%	1 Feb →
inferno	16–19	-0.03	17%	1 Feb →
mirage	8–13	0.02	27%	29 Jan →
nuke	8–13	-0.02	22%	29 Jan →
dust2	9–13	0.03	27%	29 Jan →
inferno	10–13	0.01	12%	29 Jan →
ancient	9–13	0.02	11%	29 Jan →
nuke	13–4	0.03	18%	28 Jan →
inferno	10–13	-0.05	7%	28 Jan →
nuke	13–10	0.01	8%	26 Jan →
inferno	13–5	0.09	15%	26 Jan →
nuke	6–13	-0.05	23%	26 Jan →
mirage	13–3	0.06	22%	26 Jan →
nuke	13–7	0.03	18%	26 Jan →
nuke	13–11	0.01	10%	25 Jan →
dust2	13–3	0.02	15%	25 Jan →
nuke	10–13	-0.02	13%	25 Jan →
ancient	10–13	-0.03	18%	25 Jan →
mirage	13–11	-0.01	27%	22 Jan →
nuke	11–13	0.03	6%	21 Jan →
ancient	13–9	0.01	23%	21 Jan →
anubis	11–13	0.04	11%	20 Jan →
ancient	11–13	0.03	13%	20 Jan →
inferno	13–11	-0.01	7%	19 Jan →
train	13–11	-0.05	19%	19 Jan →
train	13–1	0.02	26%	19 Jan →
anubis	2–13	-0.06	11%	19 Jan →
mirage	13–10	-0.03	15%	19 Jan →
mirage	13–9	-0.00	27%	18 Jan →
train	11–13	0.01	10%	16 Jan →
dust2	10–13	-0.01	20%	15 Jan →