Alucard — CS2 Stats

76561198415242920[U:1:454977192]✓ No bans

741Tracked matches60%Win rate2023Tracked since

CSDB Rating4.5 Developing

Premier CS Rating12,340Blue band · top ~42.5% of ranked players (population est.)

FaceitLevel 5 · 1,176 ELOTop 67.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim52

Positioning44

Utility41

0–100 skill scores via Leetify.

Recent form

HOT50–44–6Last 10050%Win rateWLWLWWWWWL

Last 10 vs previous 10: +20pp win rate · +0.04 avg rating

Player DNA

Aim5.2

Aggression4.8

Utility4.1

Positioning4.4

Opening Duels1.1

Clutch1.8

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: 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

Reaction time. 689ms 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

Positioning4.4

Utility4.1

Mechanics5.1

Opening Duels1.1

Win Impact8.3

Composite 4.5/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01+0.01

first ⅓ avg -0.02 → last ⅓ avg -0.01

Reaction time679ms−20ms

first ⅓ avg 699ms → last ⅓ avg 679ms

Headshot accuracy16.7%+1.9%

first ⅓ avg 14.8% → last ⅓ avg 16.7%

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

0.24Best rating — vertigo 9–3

13–0Biggest win — mirage

6Longest win streak

9–7In matches decided by ≤2 rounds

10Overtime games

Map breakdown

overpassBest map · 80% over 5anubisWeakest map · 20% over 5

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	20	9–11	45%	-0.00
mirage	B	17	9–8	53%	-0.01
inferno	B	14	7–7	50%	-0.02
ancient	B	14	7–7	50%	-0.03
nuke	B	14	7–7	50%	-0.01
overpass	S	5	4–1	80%	-0.00
anubis	D	5	1–4	20%	-0.04
train	S	5	4–1	80%	-0.04
office	—	4	1–3	25%	-0.06
vertigo	—	1	1–0	100%	0.24
palacio	—	1	0–1	0%	-0.02

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

118Matches

52%Win rate

0.91Avg K/D

76.5ADR

36%Headshot %

Clutches & streaks

29%1v1 clutch win

18%1v2 clutch win

8Longest win streak

Recent Faceit resultsLLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	32	56%	0.93	14.6
Ancient	27	44%	0.88	16.1
Nuke	17	65%	1.13	14.2
Inferno	16	44%	0.73	12.8
Dust2	14	50%	0.97	12.6
Vertigo	7	57%	0.73	11.3
Train	2	50%	0.51	8.0
Anubis	2	50%	1.46	12.0

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.

16.2%Headshot accuracy

36.8%Accuracy (enemy spotted)

38.2%Spray accuracy

73.1%Counter-strafing

11.5°Preaim

689msReaction time

32.7%T opening success

36.1%CT opening success

0.58Enemies flashed / flash

2.5%Flash assists

6.92HE damage / grenade

3.49Flashes / 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
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 3.4927 — below the 4 mark we flag
Grenade Lineups →
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 32.6741% — below the 40% mark we flag

Spend your practice time on Anubis

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	13–11	-0.03	13%	28 May →
mirage	7–13	-0.06	11%	18 May →
inferno	13–8	-0.05	10%	16 May →
mirage	11–13	-0.02	18%	16 May →
inferno	13–7	0.07	16%	16 May →
overpass	13–5	0.01	19%	16 May →
ancient	13–9	0.01	11%	16 May →
mirage	16–12	-0.05	8%	16 May →
inferno	13–2	0.09	20%	16 May →
nuke	14–16	0.01	14%	16 May →
overpass	4–13	-0.03	9%	16 May →
inferno	8–13	-0.01	16%	15 May →
anubis	5–13	-0.12	31%	15 May →
nuke	13–11	-0.05	26%	15 May →
anubis	13–8	-0.05	14%	15 May →
nuke	13–7	-0.05	18%	15 May →
dust2	13–10	-0.03	14%	15 May →
ancient	9–4	-0.03	26%	15 May →
dust2	6–13	-0.02	17%	15 May →
office	1–6	-0.06	11%	15 May →
dust2	8–13	-0.02	12%	15 May →
dust2	10–13	-0.02	9%	15 May →
overpass	16–14	0.05	18%	15 May →
inferno	13–7	0.02	25%	14 May →
mirage	11–13	-0.03	21%	14 May →
dust2	13–5	-0.02	23%	14 May →
dust2	10–13	0.03	7%	14 May →
dust2	13–2	0.08	19%	14 May →
mirage	13–10	0.02	15%	14 May →
mirage	13–2	0.03	26%	14 May →
anubis	6–13	-0.05	21%	14 May →
anubis	5–13	-0.00	20%	14 May →
ancient	13–10	-0.01	13%	23 Apr →
nuke	13–2	-0.03	20%	23 Apr →
office	13–7	-0.06	12%	22 Apr →
train	13–9	-0.03	23%	22 Apr →
anubis	8–13	0.02	15%	9 Apr →
train	13–11	-0.05	9%	7 Apr →
mirage	7–13	0.02	21%	10 Mar →
inferno	13–5	-0.06	14%	10 Mar →
ancient	7–13	-0.01	16%	10 Mar →
dust2	4–13	-0.03	12%	10 Mar →
dust2	13–6	0.08	21%	10 Mar →
inferno	11–13	-0.03	19%	10 Mar →
dust2	13–5	-0.02	12%	5 Mar →
dust2	11–13	-0.05	9%	5 Mar →
dust2	13–11	0.01	20%	5 Mar →
nuke	6–13	0.04	7%	5 Mar →
dust2	15–15	-0.03	13%	5 Mar →
mirage	13–0	0.06	21%	5 Mar →
mirage	4–13	-0.01	18%	4 Mar →
inferno	8–13	-0.05	13%	4 Mar →
nuke	13–11	0.04	18%	4 Mar →
mirage	13–7	-0.08	10%	4 Mar →
nuke	16–13	-0.05	11%	4 Mar →
overpass	13–8	-0.02	18%	4 Mar →
mirage	4–13	0.09	17%	4 Mar →
mirage	13–8	0.02	18%	3 Mar →
office	12–12	-0.06	14%	3 Mar →
nuke	8–13	-0.01	13%	3 Mar →
inferno	2–9	-0.24	14%	3 Mar →
train	13–10	-0.02	16%	3 Mar →
vertigo	9–3	0.24	10%	3 Mar →
ancient	13–5	0.03	11%	24 Feb →
inferno	9–13	-0.04	20%	24 Feb →
mirage	6–13	-0.06	20%	21 Feb →
nuke	14–16	-0.03	17%	20 Feb →
nuke	0–13	-0.07	13%	20 Feb →
dust2	12–12	0.01	12%	20 Feb →
nuke	13–10	0.02	17%	19 Feb →
mirage	2–13	-0.02	21%	9 Jan →
ancient	9–13	-0.05	21%	9 Jan →
inferno	12–12	0.04	21%	9 Jan →
overpass	13–9	-0.04	7%	3 Jan →
dust2	13–7	0.02	14%	3 Jan →
inferno	13–6	-0.02	20%	3 Jan →
dust2	7–13	0.04	13%	1 Jan →
dust2	3–13	-0.01	10%	12 Nov →
dust2	12–12	0.01	21%	9 Nov →
ancient	4–13	-0.13	12%	9 Nov →
inferno	10–13	-0.04	14%	9 Nov →
mirage	13–8	0.03	27%	8 Nov →
ancient	13–10	-0.02	15%	21 Oct →
dust2	13–11	-0.02	21%	20 Oct →
ancient	13–16	-0.03	8%	16 Oct →
ancient	7–13	-0.06	6%	14 Oct →
ancient	6–13	-0.05	11%	14 Oct →
nuke	4–13	-0.05	15%	13 Oct →
nuke	12–12	0.03	16%	12 Oct →
palacio	7–13	-0.02	19%	11 Oct →
ancient	19–16	-0.02	12%	11 Oct →
mirage	16–13	-0.04	9%	11 Oct →
inferno	13–11	-0.02	8%	8 Oct →
ancient	13–6	0.04	15%	8 Oct →
mirage	13–9	-0.03	16%	7 Oct →
nuke	16–14	0.01	11%	6 Oct →
train	11–13	-0.10	10%	4 Oct →
ancient	7–13	-0.06	11%	4 Oct →
office	7–13	-0.05	8%	4 Oct →
train	13–1	-0.00	36%	4 Oct →