-maV. — CS2 Stats

CA76561197982702431[U:1:22436703]Steam profile ↗

7,406Tracked matches47%Win rate2020Tracked since

CSDB Rating3.5 Learning

FaceitLevel 5 · 957 ELOTop 67.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim33

Positioning50

Utility49

0–100 skill scores via Leetify.

Recent form

STEADY51–48–1Last 10051%Win rateLWLLWWLWLW

Last 10 vs previous 10: +20pp win rate · +0.02 avg rating

Player DNA

Aim3.3

Aggression6.3

Utility4.9

Positioning5.0

Opening Duels1.6

Clutch3.8

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 Twistzz 80% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

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 44% on CT to 29% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 616ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% 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

Aim3.3

Positioning5.0

Utility4.9

Mechanics4.3

Opening Duels1.8

Win Impact3.9

Composite 3.5/10 (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-0.02−0.01

first ⅓ avg -0.01 → last ⅓ avg -0.02

Reaction time623ms+31ms

first ⅓ avg 592ms → last ⅓ avg 623ms

Headshot accuracy15.6%+2.6%

first ⅓ avg 13.0% → last ⅓ avg 15.6%

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

0.27Best rating — dust2 13–3

13–2Biggest win — mirage

5Longest win streak

12–5In matches decided by ≤2 rounds

13Overtime games

Map breakdown

ancientBest map · 73% over 11anubisWeakest map · 33% over 9

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	27	14–13	52%	0.01
dust2	C	20	8–12	40%	0.00
inferno	B	13	7–6	54%	-0.01
nuke	B	12	6–6	50%	-0.01
ancient	S	11	8–3	73%	0.00
anubis	D	9	3–6	33%	-0.02
train	—	4	3–1	75%	0.03
cache	—	2	1–1	50%	-0.03
overpass	—	2	1–1	50%	-0.00

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

4,115Matches

49%Win rate

1.02Avg K/D

79.3ADR

37%Headshot %

Clutches & streaks

39%1v1 clutch win

23%1v2 clutch win

10Longest win streak

Recent Faceit resultsWLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	303	48%	1.10	14.2
Inferno	196	53%	1.05	14.8
Ancient	144	49%	1.00	13.8
Dust2	141	48%	1.08	15.3
Anubis	128	44%	1.03	14.0
Nuke	112	46%	1.12	15.1
Vertigo	67	46%	1.01	14.8
Overpass	34	35%	1.04	14.7

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.

16.3%Headshot accuracy

26.7%Accuracy (enemy spotted)

29.5%Spray accuracy

69.1%Counter-strafing

11.3°Preaim

616msReaction time

28.7%T opening success

44.4%CT opening success

0.50Enemies flashed / flash

5.3%Flash assists

7.83HE damage / grenade

9.11Flashes / 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
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 28.6559% — 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.

33% win rate across 9 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
mirage	7–13	0.03	18%	4 Aug →
dust2	13–9	0.04	19%	4 Aug →
mirage	16–19	0.03	23%	3 Aug →
ancient	7–13	-0.01	9%	3 Aug →
mirage	13–6	0.04	16%	2 Aug →
inferno	13–10	-0.03	11%	24 Jul →
cache	2–13	-0.03	11%	8 Jul →
inferno	22–20	0.02	10%	6 Jul →
anubis	9–13	-0.01	18%	4 Jul →
cache	13–6	-0.03	18%	28 May →
nuke	13–6	0.14	26%	9 Apr →
mirage	11–13	-0.05	16%	3 Apr →
nuke	9–13	0.00	13%	1 Apr →
ancient	13–8	-0.03	21%	31 Mar →
mirage	13–8	0.00	23%	27 Jan →
anubis	2–13	-0.06	6%	22 Jan →
dust2	16–19	0.04	21%	21 Jan →
dust2	6–13	-0.09	6%	19 Jan →
dust2	11–13	-0.05	19%	18 Jan →
mirage	5–13	-0.07	17%	13 Jan →
dust2	3–13	-0.05	11%	11 Jan →
ancient	3–13	-0.04	20%	11 Jan →
mirage	13–10	-0.06	6%	11 Jan →
mirage	13–10	-0.05	13%	11 Jan →
nuke	13–9	-0.05	24%	3 Jan →
mirage	13–10	-0.02	24%	3 Jan →
overpass	13–9	-0.03	7%	3 Jan →
mirage	6–13	-0.04	17%	5 Nov →
inferno	13–8	0.01	20%	3 Nov →
inferno	2–13	-0.05	17%	1 Nov →
overpass	3–13	0.02	13%	1 Nov →
nuke	2–6	-0.08	0%	27 Oct →
dust2	13–11	-0.04	19%	27 Oct →
dust2	10–13	-0.04	11%	2 Aug →
mirage	13–10	-0.01	15%	1 Aug →
nuke	9–13	-0.01	12%	31 Jul →
mirage	5–13	0.00	21%	28 Jul →
ancient	11–13	-0.01	9%	27 Jul →
inferno	13–9	0.00	17%	24 Jul →
mirage	10–13	0.02	13%	21 Jul →
mirage	13–8	-0.01	14%	7 Jun →
mirage	10–13	0.08	9%	17 May →
ancient	13–7	0.11	13%	13 May →
train	13–3	0.01	7%	13 May →
ancient	13–8	0.02	7%	13 May →
mirage	13–5	0.04	18%	6 Apr →
anubis	13–8	0.07	9%	17 Mar →
dust2	6–13	-0.02	7%	15 Mar →
dust2	13–3	0.27	16%	18 Jan →
mirage	16–14	0.02	14%	12 Jan →
nuke	4–13	-0.07	11%	11 Jan →
mirage	13–11	0.06	17%	10 Jan →
mirage	6–13	0.01	11%	10 Jan →
dust2	13–16	0.06	21%	10 Jan →
ancient	16–13	-0.06	20%	5 Jan →
inferno	13–9	0.09	16%	29 Dec →
anubis	5–13	-0.03	19%	29 Dec →
anubis	2–13	-0.05	25%	29 Dec →
dust2	13–16	0.01	14%	28 Dec →
train	13–9	0.15	16%	11 Dec →
mirage	13–6	0.07	9%	8 Dec →
inferno	13–8	0.07	12%	8 Dec →
nuke	16–13	0.03	12%	7 Dec →
inferno	14–16	-0.02	19%	5 Dec →
ancient	13–3	0.06	6%	1 Dec →
train	6–13	0.01	6%	1 Dec →
inferno	7–13	-0.03	18%	28 Nov →
anubis	4–13	-0.06	13%	24 Nov →
dust2	13–3	0.11	12%	23 Nov →
train	13–11	-0.04	2%	23 Nov →
dust2	4–13	-0.07	18%	17 Nov →
mirage	13–5	0.05	10%	17 Nov →
nuke	11–13	-0.05	15%	17 Nov →
mirage	3–13	-0.06	5%	13 Nov →
anubis	13–8	0.03	14%	13 Nov →
mirage	9–13	0.01	26%	31 Oct →
anubis	5–13	-0.05	17%	30 Oct →
mirage	13–2	0.09	13%	30 Oct →
inferno	13–11	0.02	19%	29 Oct →
nuke	12–12	0.03	16%	29 Oct →
dust2	16–14	0.09	24%	29 Oct →
inferno	8–13	-0.04	15%	28 Oct →
mirage	19–16	0.06	9%	27 Oct →
nuke	16–13	0.02	7%	27 Oct →
dust2	10–13	-0.06	12%	26 Oct →
anubis	13–11	-0.07	7%	26 Oct →
nuke	13–11	-0.04	18%	25 Oct →
ancient	13–10	0.01	15%	25 Oct →
mirage	10–13	-0.00	21%	24 Oct →
ancient	13–11	-0.02	16%	20 Oct →
dust2	13–2	-0.01	10%	20 Oct →
dust2	12–16	0.01	8%	20 Oct →
ancient	13–6	0.02	12%	20 Oct →
mirage	7–13	-0.04	12%	20 Oct →
inferno	10–13	-0.04	11%	19 Oct →
dust2	4–13	-0.08	18%	19 Oct →
inferno	5–13	-0.10	3%	19 Oct →
nuke	13–7	-0.06	13%	19 Oct →
dust2	13–11	-0.06	10%	19 Oct →
dust2	13–11	0.02	12%	19 Oct →