/ p / Ash
🔗 suspect.gg/p/76561198999035959
LVL 6

Ash

NOT ENOUGH DATA
76561198999035959|UZ|7 yrs old
Steam↗Leetify↗
0/0
REVIEW SIGNALS
NOT ENOUGH DATA
ANALYSED FROM DEMOS

No verdict yet: we have analysed 1 of this player's matches, 0 with 12+ kills (the ones we rate), and a verdict needs 10 of those. 0 tripped a review signal; roughly 1 in 20 rated matches does.

647MS
TIME TO DAMAGENormal
—%
WIN RATErecent

Analysed 1 match: nothing flagged.

SIGNAL BREAKDOWN
vs 39,567 analysed player-matches
Aim accuracy17.9%
Share of shots that landed a hit, with aimed weapons, across analysed rounds.higher than 20% of analysed player-matches
Headshot share7.4%
Of the hits that landed, how many struck the head. High alone is not proof.higher than 15% of analysed player-matches
Damage-to-kill647ms
Average time from first landing damage to the kill (lower = closer to an instant kill).faster than 7% of analysed player-matches
Crosshair pre-aim9.1°
How far the crosshair sat off the enemy at first contact (lower = already aimed before seeing them).tighter than 19% of analysed player-matches
Leetify: couldn't check
NO CLIPanalysed · nothing flagged
ANALYSED
No clip rendered yet

We've analysed this player's matches and nothing is flagged.

MULTI-SOURCE STATS
Playtimeprivate
Account age7y
VAC bans0
Game bans0
bans checked less than an hour ago
No Premier rating available
No FACEIT account
Couldn't check Leetify this time. Try again in a few minutes.
STEAM INVENTORY
ACTIVITY · LAST 120 DAYS
lessmore
MATCH HISTORY
Leetify history · demos enrich rosters & signals
✓
INFERNO
K / D10/16
ADR70
HS%20%
RATING0.83
No signal
ROSTER01L R K 8902Maja03LemonSqueezy04oileybat05♿5090Ti Nitro+AeroCock SAS♿06Ash07Borby08SKINS09oileycat10Jimmy
WEAPON BREAKDOWN · ANALYSED DEMOS
AK-476 kills · 0% HS
P902 kills · 50% HS
PP-Bizon1 kills · 0% HS
USP-S1 kills · 100% HS
Seen enough? Put it on record.
Open their newest analysed match and pick them on the scoreboard to report it, or browse the public watchlist.
Report a matchView public watchlist
â—† ALLEGEDSignals are model-flagged from demo analysis and public data: triage, not a verdict. Every finding is appealable.