amale — CS2 Stats

76561198039043964[U:1:78778236]

833Tracked matches45%Win rate2023Tracked since

CSDB Rating5.4 DevelopingPassive Rifler

Premier CS Rating19,590Purple band · top ~10.1% of ranked players (population est.)

Ladder ranks via Leetify

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Performance scores

Aim67

Positioning39

Utility62

0–100 skill scores via Leetify.

Recent form

STEADY47–47–6Last 10047%Win rateWWWLLWLWWL

Last 10 vs previous 10: +30pp win rate · +0.02 avg rating

Player DNA

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

Aim6.7

Aggression3.5

Utility6.2

Positioning3.9

Opening Duels0.0

Clutch4.2

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 NiKo 84% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

Where you differ: lower positioning profile; 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 40% on CT to 18% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 615ms 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

Positioning3.9

Utility6.2

Mechanics7.8

Opening Duels1.3

Win Impact3.3

Composite 5.4/10 (Developing), 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 rating-0.01−0.01

first ⅓ avg -0.01 → last ⅓ avg -0.01

Reaction time616ms−2ms

first ⅓ avg 619ms → last ⅓ avg 616ms

Headshot accuracy21.6%+0.9%

first ⅓ avg 20.7% → last ⅓ avg 21.6%

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

0.10Best rating — nuke 11–13

13–0Biggest win — ancient

4Longest win streak

W3Current streak

13–5In matches decided by ≤2 rounds

18Overtime games

Map breakdown

dust2Best map · 75% over 8anubisWeakest map · 33% over 18

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	19	9–10	47%	0.01
inferno	A	18	11–7	61%	-0.00
nuke	C	18	8–10	44%	0.02
anubis	D	18	6–12	33%	-0.02
mirage	D	9	3–6	33%	-0.02
dust2	S	8	6–2	75%	0.01
cache	S	6	4–2	67%	0.00
overpass	—	3	0–3	0%	-0.01
debris	—	1	0–1	0%	-0.09

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (33% over 18). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

211Matches

50%Win rate

0.98Avg K/D

78.9ADR

37%Headshot %

Clutches & streaks

41%1v1 clutch win

25%1v2 clutch win

7Longest win streak

Recent Faceit resultsLLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	16	56%	1.38	16.3
Anubis	15	67%	0.98	17.1
Nuke	11	27%	1.34	17.6
Dust2	11	27%	0.76	13.0
Mirage	11	36%	1.14	13.8
Inferno	7	43%	1.03	15.6
Overpass	4	25%	1.22	17.5
Train	1	100%	0.92	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.

21.5%Headshot accuracy

30.1%Accuracy (enemy spotted)

31.8%Spray accuracy

85.2%Counter-strafing

9.2°Preaim

615msReaction time

18.1%T opening success

40.4%CT opening success

0.53Enemies flashed / flash

6.4%Flash assists

5.88HE damage / grenade

19.09Flashes / 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 18.0945% — 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 18 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
inferno	13–11	0.02	17%	28 Aug →
cache	13–7	-0.05	30%	26 Aug →
ancient	13–11	0.01	22%	26 Aug →
nuke	11–13	0.10	27%	25 Aug →
anubis	6–13	-0.03	16%	24 Aug →
dust2	13–5	-0.03	29%	24 Aug →
nuke	9–13	-0.01	14%	22 Aug →
ancient	13–11	0.06	24%	22 Aug →
ancient	13–0	0.04	29%	22 Aug →
cache	11–13	-0.04	20%	22 Aug →
nuke	5–13	-0.02	28%	21 Aug →
mirage	13–10	-0.01	29%	15 Aug →
anubis	7–13	-0.07	29%	15 Aug →
inferno	13–16	-0.01	22%	15 Aug →
dust2	13–16	0.02	24%	13 Aug →
inferno	4–13	-0.07	13%	11 Aug →
cache	13–5	0.02	22%	11 Aug →
nuke	13–9	0.02	19%	11 Aug →
inferno	4–13	0.02	15%	10 Aug →
inferno	7–13	-0.07	33%	9 Aug →
anubis	16–14	-0.01	26%	9 Aug →
debris	5–9	-0.09	32%	9 Aug →
anubis	15–15	-0.08	20%	8 Aug →
mirage	10–13	-0.03	17%	8 Aug →
anubis	13–5	-0.03	13%	8 Aug →
ancient	7–1	-0.00	18%	8 Aug →
mirage	11–13	-0.02	23%	6 Aug →
ancient	7–13	-0.04	17%	6 Aug →
cache	13–11	-0.02	11%	5 Aug →
anubis	10–13	-0.08	19%	5 Aug →
anubis	4–13	-0.01	18%	29 Jul →
mirage	6–13	0.01	17%	29 Jul →
ancient	16–12	0.09	23%	29 Jul →
cache	15–15	0.10	23%	29 Jul →
inferno	13–6	0.00	21%	27 Jul →
nuke	16–13	0.10	22%	25 Jul →
mirage	7–13	-0.02	25%	25 Jul →
ancient	10–13	0.01	22%	24 Jul →
dust2	13–10	-0.01	18%	24 Jul →
inferno	4–13	-0.01	21%	24 Jul →
inferno	13–8	-0.00	24%	24 Jul →
nuke	13–10	0.06	27%	24 Jul →
ancient	12–16	-0.03	18%	24 Jul →
inferno	13–4	0.04	10%	23 Jul →
anubis	15–15	0.01	27%	22 Jul →
nuke	7–13	0.03	18%	22 Jul →
ancient	13–6	0.02	19%	22 Jul →
nuke	10–13	-0.01	26%	21 Jul →
mirage	2–13	-0.03	16%	21 Jul →
inferno	13–11	0.02	14%	21 Jul →
ancient	10–13	0.01	29%	21 Jul →
cache	13–11	0.01	19%	15 Jul →
nuke	9–13	-0.02	10%	15 Jul →
dust2	13–5	0.02	20%	14 Jul →
nuke	8–13	0.00	29%	14 Jul →
anubis	5–13	-0.02	18%	14 Jul →
nuke	6–13	0.02	18%	14 Jul →
ancient	6–13	0.00	13%	14 Jul →
ancient	9–13	-0.06	23%	13 Jul →
ancient	15–15	0.06	26%	13 Jul →
anubis	16–14	-0.01	19%	12 Jul →
ancient	13–3	0.07	16%	12 Jul →
dust2	13–11	0.05	21%	11 Jul →
anubis	13–11	0.00	19%	11 Jul →
anubis	6–13	0.06	25%	10 Jul →
nuke	13–11	0.04	23%	18 Jun →
nuke	13–6	0.04	22%	21 May →
inferno	13–11	0.01	16%	30 Apr →
overpass	3–13	-0.08	33%	25 Apr →
dust2	11–13	-0.03	25%	24 Apr →
anubis	13–8	0.01	15%	24 Apr →
anubis	13–16	-0.04	8%	22 Apr →
anubis	5–13	-0.05	29%	30 Mar →
inferno	13–10	-0.05	23%	28 Mar →
nuke	13–7	0.04	20%	28 Mar →
ancient	14–16	-0.01	35%	21 Mar →
inferno	7–13	-0.07	28%	18 Mar →
nuke	13–4	0.04	25%	8 Mar →
ancient	2–13	-0.04	18%	3 Mar →
nuke	7–13	-0.02	23%	3 Mar →
inferno	4–13	0.01	19%	2 Mar →
inferno	13–9	-0.05	18%	1 Mar →
ancient	16–13	0.02	22%	28 Feb →
anubis	13–6	0.01	11%	28 Feb →
mirage	9–13	-0.03	19%	27 Feb →
dust2	13–10	0.02	26%	27 Feb →
overpass	7–13	0.02	15%	26 Feb →
inferno	13–3	0.04	24%	25 Feb →
anubis	15–15	-0.01	16%	25 Feb →
dust2	16–13	0.03	13%	23 Feb →
ancient	13–9	-0.01	8%	23 Feb →
anubis	10–13	-0.04	16%	23 Feb →
inferno	16–14	-0.00	9%	23 Feb →
mirage	13–7	-0.02	17%	23 Feb →
ancient	9–13	0.04	25%	22 Feb →
nuke	13–7	0.04	24%	22 Feb →
mirage	13–10	-0.07	20%	19 Feb →
overpass	2–13	0.04	30%	19 Feb →
nuke	15–15	-0.03	20%	19 Feb →
inferno	13–1	0.08	31%	19 Feb →