/ p / Loman
🔗 suspect.gg/76561199656374600
LVL 4

Loman

WATCH
76561199656374600|FACEIT Loman95|2.4 yrs old
SteamFACEITLeetify
0
SUSPECT INDEX
WATCH
SIGNALS ONLY
305MS
TIME TO DAMAGEFast reactions
%
WIN RATErecent

We parsed the demo and flagged the signals below. Render the evidence to see them on video.

SIGNAL BREAKDOWN
vs 1,846 analysed players
Aim accuracy19.5%
Share of shots that landed a hit, with aimed weapons, across analysed rounds.higher than 28% of analysed players
Headshot share26.3%
Of the hits that landed, how many struck the head. High alone is not proof.higher than 95% of analysed players
Damage-to-kill305ms
Average time from first landing damage to the kill (lower = closer to an instant kill).faster than 63% of analysed players
Crosshair pre-aim7.2°
How far the crosshair sat off the enemy at first contact (lower = already aimed before seeing them).tighter than 44% of analysed players
PROOFsignals flagged · clip not rendered
AWAITING RENDER
No clip rendered yet

We've parsed the demo and flagged the signals on the left. Render the evidence to see the flagged rounds on video.

free · rate-limited
MULTI-SOURCE STATS
Playtime4,175h
Account age2.4y
VAC bans0
Game bans0
No Premier rating available
FACEIT level 6
ELO 1,222
K/D0.94
HS %51%
No Leetify data
FACEIT · PERFORMANCE BY MAP
Premier is a single rating · shown above
cache
1m
Win rate0%
K/D0.53
HS%30%
inferno
8m
Win rate38%
K/D0.86
HS%46%
dust2
45m
Win rate49%
K/D1.00
HS%56%
ancient
25m
Win rate56%
K/D0.91
HS%47%
anubis
17m
Win rate65%
K/D0.91
HS%49%
mirage
33m
Win rate52%
K/D0.91
HS%51%
nuke
1m
Win rate0%
K/D1.18
HS%65%
STEAM INVENTORY
ACTIVITY · LAST 120 DAYS
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MATCH HISTORY
Leetify history · demos enrich rosters & signals
W
MIRAGE
K / D20/18
ADR104
HS%65%
RATING1.38
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Analysed
ROSTER01Autistic dumpster fire02Zbon Remix03Loman04TheUrbanSkunk05OSMAN BEI06киосуке аура07Tonyzaka08TomJum09ReZ110propovednic74
WEAPON BREAKDOWN
Per-weapon kills are collected as we analyse this player's demos — this section fills in on the next analysis pass.
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◆ ALLEGEDSignals are model-flagged from demo analysis and public data — triage, not a verdict. Every finding is appealable.