Zeiko — CS2 Stats

76561198314094354[U:1:353828626]Steam profile ↗✓ No bans

680Tracked matches60%Win rate2020Tracked since

CSDB Rating5.0 DevelopingHybrid Rifler

FaceitLevel 10 · 2,141 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim67

Positioning43

Utility23

0–100 skill scores via Leetify.

Recent form

STEADY55–41–4Last 10055%Win rateWLLWWWWWLL

Last 10 vs previous 10: +10pp win rate · +0.01 avg rating

Player DNA

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

Aim6.7

Aggression4.5

Utility2.3

Positioning4.3

Opening Duels0.2

Clutch5.6

Effective flashesLimited utility dependence

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 b1t 76% playstyle similarity

Most alike: positioning profile, opening-fight frequency.

Where you differ: lower aim profile; lower utility contribution.

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

Flashes. 0.84 enemies blinded per flash — utility that consistently lands.

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 577ms 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

Positioning4.3

Utility2.3

Mechanics6.1

Opening Duels0.7

Win Impact8.3

Composite 5.0/10 (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 rating0.00−0.02

first ⅓ avg 0.02 → last ⅓ avg 0.00

Reaction time565ms−2ms

first ⅓ avg 567ms → last ⅓ avg 565ms

Headshot accuracy14.3%−2.6%

first ⅓ avg 16.9% → last ⅓ avg 14.3%

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

0.25Best rating — vertigo 13–9

13–1Biggest win — vertigo

7Longest win streak

6–6In matches decided by ≤2 rounds

13Overtime games

Map breakdown

nukeBest map · 71% over 7infernoWeakest map · 38% over 16

Map	Grade	Played	Record	Win rate	Avg rating
mirage	S	42	28–14	67%	0.02
inferno	C	16	6–10	38%	-0.00
dust2	C	12	5–7	42%	0.01
vertigo	A	12	7–5	58%	0.03
nuke	S	7	5–2	71%	-0.01
ancient	—	4	2–2	50%	-0.03
anubis	—	3	1–2	33%	0.04
overpass	—	3	1–2	33%	-0.02
train	—	1	0–1	0%	0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 16). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

384Matches

54%Win rate

1.18Avg K/D

87.5ADR

41%Headshot %

Clutches & streaks

48%1v1 clutch win

20%1v2 clutch win

11Longest win streak

Recent Faceit resultsLLLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	112	59%	1.18	17.6
Vertigo	53	62%	1.12	17.9
Inferno	24	42%	1.01	16.6
Ancient	22	41%	0.96	14.1
Dust2	17	41%	1.45	16.5
Overpass	16	44%	1.27	18.3
Nuke	5	40%	0.95	13.8
Anubis	4	0%	0.91	15.3

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.

13.4%Headshot accuracy

35.1%Accuracy (enemy spotted)

40.6%Spray accuracy

77.3%Counter-strafing

9.7°Preaim

577msReaction time

25.9%T opening success

35.8%CT opening success

0.84Enemies flashed / flash

15.3%Flash assists

14.75HE damage / grenade

4.50Flashes / 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 13.378% — 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 25.9167% — 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.

38% win rate across 16 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
anubis	13–10	0.05	16%	23 Aug →
dust2	6–13	-0.04	25%	26 Oct →
mirage	9–13	-0.03	8%	19 Oct →
mirage	13–7	-0.02	11%	19 Oct →
mirage	19–16	0.00	16%	19 Oct →
mirage	13–7	0.04	24%	13 Oct →
mirage	13–8	0.03	20%	12 Oct →
inferno	13–6	0.04	18%	8 Oct →
mirage	10–13	-0.03	7%	7 Oct →
mirage	14–16	-0.02	12%	6 Oct →
ancient	9–13	-0.01	8%	3 Oct →
ancient	13–4	0.00	21%	1 Oct →
mirage	16–13	-0.00	8%	28 Sept →
mirage	13–11	0.00	13%	28 Sept →
mirage	8–13	0.05	14%	24 Aug →
inferno	8–13	0.01	13%	21 Apr →
nuke	13–7	-0.04	18%	20 Mar →
inferno	13–8	-0.01	19%	15 Mar →
nuke	5–13	-0.04	10%	13 Mar →
dust2	0–4	-0.03	29%	13 Mar →
mirage	9–13	-0.03	7%	12 Mar →
mirage	13–8	0.01	8%	12 Mar →
ancient	9–13	-0.07	9%	11 Mar →
mirage	13–9	0.03	10%	11 Mar →
mirage	13–9	0.12	16%	9 Mar →
nuke	16–14	0.03	14%	9 Mar →
inferno	11–13	-0.03	8%	9 Mar →
inferno	13–8	-0.01	13%	7 Mar →
mirage	13–7	0.04	9%	6 Mar →
mirage	13–3	0.08	13%	5 Mar →
mirage	9–13	-0.02	15%	4 Mar →
inferno	13–10	-0.02	25%	4 Mar →
anubis	9–13	0.01	13%	2 Mar →
nuke	13–9	-0.01	13%	2 Mar →
mirage	10–13	0.00	18%	28 Feb →
inferno	4–13	-0.02	9%	27 Feb →
inferno	13–4	0.02	19%	27 Feb →
mirage	10–1	0.10	20%	27 Feb →
mirage	6–13	-0.03	11%	23 Feb →
inferno	6–13	0.00	18%	19 Feb →
nuke	13–16	0.05	22%	16 Feb →
inferno	3–13	-0.07	9%	16 Feb →
mirage	16–12	-0.01	16%	10 Jan →
dust2	7–13	0.07	16%	8 Dec →
train	13–16	0.05	12%	20 Nov →
dust2	13–7	0.04	18%	20 Nov →
vertigo	16–12	0.05	17%	19 Nov →
inferno	9–10	-0.01	24%	29 Oct →
overpass	13–8	0.01	17%	26 Oct →
dust2	12–12	0.09	15%	21 Oct →
dust2	10–13	0.00	27%	17 Oct →
ancient	13–11	-0.03	7%	16 Oct →
mirage	13–10	-0.03	17%	15 Oct →
vertigo	13–1	0.03	9%	13 Oct →
anubis	12–12	0.06	17%	13 Oct →
mirage	13–11	0.05	21%	9 Oct →
nuke	13–5	0.00	26%	9 Oct →
mirage	13–11	0.01	19%	6 Oct →
overpass	10–13	0.03	16%	6 Oct →
mirage	12–12	0.04	16%	6 Oct →
mirage	13–6	-0.01	8%	3 Oct →
inferno	6–13	-0.00	16%	3 Oct →
mirage	13–5	0.17	24%	3 Oct →
inferno	6–13	-0.01	19%	29 Sept →
inferno	6–13	-0.02	21%	29 Sept →
dust2	8–13	0.02	14%	29 Sept →
vertigo	5–13	0.01	13%	29 Sept →
mirage	4–13	-0.06	6%	29 Sept →
dust2	16–13	0.04	21%	28 Sept →
vertigo	13–10	0.03	19%	25 Sept →
mirage	13–9	-0.02	14%	24 Sept →
vertigo	11–13	0.03	10%	24 Sept →
vertigo	13–5	0.05	13%	24 Sept →
mirage	16–13	-0.01	10%	23 Sept →
mirage	10–13	-0.02	12%	22 Sept →
vertigo	15–15	-0.03	10%	22 Sept →
dust2	13–11	-0.01	9%	17 Sept →
mirage	9–13	-0.01	16%	15 Sept →
nuke	13–6	-0.03	18%	15 Sept →
mirage	6–1	-0.01	40%	15 Sept →
mirage	7–2	0.08	21%	10 Sept →
mirage	13–8	0.09	19%	10 Sept →
vertigo	13–2	0.04	23%	10 Sept →
mirage	13–7	0.14	33%	8 Sept →
mirage	13–10	-0.02	12%	8 Sept →
dust2	11–13	-0.00	21%	3 Sept →
mirage	6–13	0.01	17%	1 Sept →
mirage	13–6	0.09	13%	1 Sept →
vertigo	13–5	-0.00	14%	31 Aug →
mirage	7–1	0.12	29%	18 Jun →
mirage	7–11	0.03	14%	26 May →
dust2	13–8	0.00	0%	14 May →
vertigo	14–16	-0.00	18%	28 Apr →
dust2	13–8	-0.05	30%	26 Apr →
vertigo	9–13	-0.09	16%	24 Apr →
inferno	13–10	0.02	15%	23 Apr →
vertigo	13–9	0.25	24%	22 Apr →
mirage	13–5	0.07	17%	21 Apr →
inferno	12–16	0.09	12%	21 Apr →
overpass	5–13	-0.09	13%	19 Apr →