/ p / *K.o?
🔗 suspect.gg/76561199156147013
LVL 10

*K.o?

LEGIT
76561199156147013|FACEIT oneKeno|5.4 yrs old
SteamFACEITLeetify
0
SUSPECT INDEX
LEGIT
DEMO-VERIFIED
449MS
TIME TO DAMAGENormal
%
WIN RATErecent

Signals suggest reviewing this account — the rendered clip shows the flagged rounds frame by frame.

SIGNAL BREAKDOWN
vs 1,846 analysed players
Aim accuracy28.9%
Share of shots that landed a hit, with aimed weapons, across analysed rounds.higher than 80% of analysed players
Headshot share10.6%
Of the hits that landed, how many struck the head. High alone is not proof.higher than 33% of analysed players
Damage-to-kill449ms
Average time from first landing damage to the kill (lower = closer to an instant kill).faster than 29% of analysed players
Crosshair pre-aim10.2°
How far the crosshair sat off the enemy at first contact (lower = already aimed before seeing them).tighter than 16% of analysed players
PROOFrendered evidence clip
VERIFIED DEMO
free · rate-limited
MULTI-SOURCE STATS
Playtime1,456h
Account age5.4y
VAC bans0
Game bans0
No Premier rating available
FACEIT level 4
ELO 953
K/D1.28
HS %37%
No Leetify data
FACEIT · PERFORMANCE BY MAP
Premier is a single rating · shown above
vertigo
1m
Win rate0%
K/D0.83
HS%40%
dust2
22m
Win rate55%
K/D1.14
HS%38%
nuke
11m
Win rate55%
K/D1.38
HS%38%
anubis
6m
Win rate67%
K/D1.39
HS%32%
train
3m
Win rate33%
K/D1.13
HS%35%
inferno
15m
Win rate47%
K/D1.14
HS%40%
mirage
34m
Win rate47%
K/D1.30
HS%37%
ancient
11m
Win rate64%
K/D1.76
HS%31%
overpass
4m
Win rate75%
K/D0.83
HS%42%
STEAM INVENTORY
ACTIVITY · LAST 120 DAYS
lessmore
MATCH HISTORY
Leetify history · demos enrich rosters & signals
INFERNO
K / D12/15
ADR80
HS%42%
RATING1.00
Clean
Analysed
ROSTER01Syrusas02Gambit_X03AcmuX04Squanchy.05bigV06Autistic dumpster fire07amxmodmenu08*K.o?09ReZ110Lee
WEAPON BREAKDOWN
Per-weapon kills are collected as we analyse this player's demos — this section fills in on the next analysis pass.
Seen enough? Put it on record.
File a report, render the evidence, or keep an eye out.
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◆ ALLEGEDSignals are model-flagged from demo analysis and public data — triage, not a verdict. Every finding is appealable.