cızıen — CS2 Stats

SA76561198845414632[U:1:885148904]Steam profile ↗

3,510Tracked matches67%Win rate2020Tracked since

CSDB Rating7.4 StrongHybrid Rifler

Premier CS Rating20,699Pink band · top ~7.7% of ranked players (population est.)

CSDB Leaderboard#6823 of 17008 tracked

FaceitLevel 10 · 2,407 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim89

Positioning49

Utility74

0–100 skill scores via Leetify.

Recent form

STEADY55–45Last 10055%Win rateWLLWLLWWWW

Last 10 vs previous 10: -20pp win rate · +0.00 avg rating

Player DNA

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

Aim8.9

Aggression6.0

Utility7.4

Positioning4.9

Opening Duels2.9

Clutch3.2

Sharp aimerStrong 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 Twistzz 96% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

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

Strengths

Aim. Aim score of 89 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 40 points — deaths here waste a strong aim profile.

T-side openings. Opening success drops from 54% on CT to 29% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim8.9

Positioning4.9

Utility7.4

Mechanics7.7

Opening Duels3.0

Win Impact10.0

Composite 7.4/10 (Strong), 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 rating0.01+0.01

first ⅓ avg 0.00 → last ⅓ avg 0.01

Reaction time507ms−31ms

first ⅓ avg 538ms → last ⅓ avg 507ms

Headshot accuracy23.4%−1.5%

first ⅓ avg 24.8% → last ⅓ avg 23.4%

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 — dust2 13–7

13–2Biggest win — nuke

5Longest win streak

14–10In matches decided by ≤2 rounds

9Overtime games

Map breakdown

nukeBest map · 86% over 7infernoWeakest map · 43% over 14

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	22	10–12	45%	0.00
dust2	B	20	9–11	45%	-0.00
mirage	S	20	16–4	80%	0.01
inferno	C	14	6–8	43%	0.00
anubis	A	11	6–5	55%	0.01
nuke	S	7	6–1	86%	0.01
overpass	—	3	1–2	33%	-0.03
train	—	2	0–2	0%	0.01
vertigo	—	1	1–0	100%	0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (43% over 14). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

6,703Matches

51%Win rate

1.15Avg K/D

83.0ADR

49%Headshot %

Clutches & streaks

36%1v1 clutch win

22%1v2 clutch win

8Longest win streak

Recent Faceit resultsLLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	620	51%	1.14	16.6
Inferno	419	52%	1.14	16.4
Ancient	406	48%	1.10	17.4
Dust2	401	52%	1.15	16.2
Anubis	314	51%	1.12	17.2
Nuke	107	49%	1.01	15.3
Vertigo	58	50%	1.22	17.7
Overpass	55	47%	1.02	17.3

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.

23.1%Headshot accuracy

38.7%Accuracy (enemy spotted)

36.3%Spray accuracy

84.4%Counter-strafing

8.9°Preaim

499msReaction time

29.4%T opening success

53.9%CT opening success

0.67Enemies flashed / flash

10.6%Flash assists

12.52HE damage / grenade

11.45Flashes / 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 29.403% — below the 40% mark we flag

Spend your practice time on Inferno

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

43% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	13–8	-0.05	21%	26 Aug →
anubis	9–13	0.07	30%	23 Aug →
ancient	8–13	-0.01	24%	18 Aug →
dust2	13–7	0.14	24%	17 Aug →
anubis	14–16	-0.02	25%	14 Aug →
inferno	9–13	-0.02	17%	14 Aug →
ancient	13–6	0.03	28%	12 Aug →
anubis	13–8	-0.00	21%	8 Aug →
ancient	13–6	-0.01	14%	2 Aug →
mirage	13–10	0.04	26%	15 Jul →
inferno	11–13	0.01	20%	7 May →
nuke	13–2	0.08	41%	1 May →
anubis	13–6	-0.04	30%	27 Apr →
mirage	13–11	0.00	20%	26 Apr →
mirage	13–10	0.06	32%	24 Apr →
dust2	13–5	0.07	29%	16 Apr →
ancient	7–13	-0.03	19%	16 Apr →
nuke	13–9	-0.02	20%	16 Apr →
dust2	13–10	-0.03	25%	16 Apr →
mirage	13–6	0.04	28%	15 Apr →
inferno	6–13	-0.01	21%	3 Apr →
mirage	13–9	0.03	19%	3 Apr →
ancient	3–13	-0.03	11%	3 Apr →
inferno	13–10	-0.03	20%	3 Apr →
anubis	13–5	0.06	24%	28 Mar →
ancient	13–11	-0.01	19%	20 Mar →
dust2	6–13	-0.02	12%	18 Mar →
dust2	13–2	-0.00	37%	14 Mar →
anubis	6–13	-0.06	18%	14 Mar →
mirage	13–10	0.00	24%	12 Mar →
dust2	13–11	-0.03	26%	7 Mar →
ancient	14–16	-0.00	16%	7 Mar →
mirage	13–11	0.02	31%	28 Feb →
ancient	11–13	-0.04	14%	28 Feb →
dust2	2–13	-0.05	17%	28 Feb →
nuke	13–3	0.07	17%	14 Feb →
nuke	13–11	0.04	20%	14 Feb →
dust2	13–9	0.03	13%	12 Feb →
mirage	13–11	-0.03	17%	2 Feb →
dust2	5–13	-0.03	30%	31 Jan →
mirage	3–13	-0.07	19%	29 Jan →
inferno	12–16	0.01	25%	20 Jan →
ancient	9–13	0.02	21%	17 Jan →
inferno	13–9	0.03	25%	30 Dec →
mirage	10–13	-0.09	15%	28 Dec →
vertigo	13–10	0.04	18%	18 Dec →
dust2	7–13	-0.03	33%	14 Dec →
ancient	16–14	0.06	15%	6 Dec →
overpass	11–13	0.00	30%	23 Nov →
mirage	13–9	-0.02	12%	23 Nov →
inferno	13–11	0.02	23%	19 Nov →
mirage	10–13	0.04	22%	19 Nov →
overpass	2–13	-0.04	13%	18 Nov →
nuke	1–13	-0.10	13%	13 Nov →
ancient	13–5	0.14	23%	7 Nov →
inferno	13–2	-0.03	18%	2 Nov →
ancient	14–16	0.04	28%	2 Nov →
mirage	13–9	0.01	12%	31 Oct →
dust2	9–13	0.00	25%	31 Oct →
inferno	5–13	-0.07	14%	28 Sept →
ancient	9–13	-0.06	22%	27 Sept →
ancient	13–11	0.00	21%	18 Sept →
dust2	13–11	0.05	14%	14 Sept →
inferno	13–7	0.02	29%	14 Sept →
mirage	13–10	0.03	21%	13 Sept →
dust2	10–13	-0.02	35%	13 Sept →
inferno	13–7	0.09	29%	9 Sept →
overpass	13–7	-0.03	31%	7 Sept →
inferno	11–13	0.00	20%	6 Sept →
dust2	24–28	0.01	24%	21 Aug →
dust2	9–12	-0.05	25%	17 Aug →
mirage	16–14	-0.03	19%	14 Aug →
mirage	13–7	0.03	30%	13 Aug →
ancient	13–7	0.05	25%	9 Aug →
mirage	13–6	-0.01	45%	8 Aug →
mirage	13–16	-0.02	26%	25 Jul →
dust2	7–13	-0.05	22%	24 Jul →
inferno	6–13	-0.01	25%	18 Jul →
inferno	11–13	0.00	18%	13 Jun →
train	7–13	0.01	32%	10 Jun →
dust2	13–8	-0.01	26%	10 Jun →
nuke	13–11	0.01	16%	10 Jun →
anubis	13–9	0.12	25%	10 Jun →
dust2	10–13	0.01	32%	24 May →
mirage	13–11	0.07	21%	17 May →
ancient	13–9	-0.05	21%	16 May →
dust2	10–13	-0.01	18%	15 May →
nuke	13–7	0.01	30%	10 May →
anubis	13–11	0.01	23%	8 May →
ancient	11–13	0.02	25%	7 May →
mirage	13–7	0.02	23%	3 May →
ancient	6–13	-0.04	19%	1 May →
ancient	8–13	-0.03	20%	25 Apr →
ancient	22–18	0.01	24%	23 Apr →
train	10–13	0.01	17%	21 Apr →
anubis	8–13	0.04	26%	20 Apr →
ancient	13–10	-0.01	27%	18 Apr →
anubis	13–8	-0.02	18%	17 Apr →
ancient	11–13	0.00	27%	17 Apr →
anubis	2–13	-0.03	39%	14 Apr →