/ p / NaWeed
🔗 suspect.gg/p/76561198115455604

NaWeed

NOT ENOUGH DATA
76561198115455604|FACEIT navidmadrid
Steam↗FACEIT↗Leetify↗
0/1
REVIEW SIGNALS
NOT ENOUGH DATA
ANALYSED FROM DEMOS

No verdict yet: we have analysed 1 of this player's matches, 1 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.

110MS
TIME TO DAMAGEFast reactions
—%
WIN RATErecent

Analysed 1 match: nothing flagged.

SIGNAL BREAKDOWN
vs 39,745 analysed player-matches
Aim accuracy20.6%
Share of shots that landed a hit, with aimed weapons, across analysed rounds.higher than 34% of analysed player-matches
Headshot share14.3%
Of the hits that landed, how many struck the head. High alone is not proof.higher than 53% of analysed player-matches
Damage-to-kill110ms
Average time from first landing damage to the kill (lower = closer to an instant kill).faster than 93% of analysed player-matches
Crosshair pre-aim2.8°
How far the crosshair sat off the enemy at first contact (lower = already aimed before seeing them).tighter than 96% 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 age—
VAC bans0
Game bans0
bans checked less than an hour ago
No Premier rating available
FACEIT level 2
ELO 816
Couldn't check Leetify this time. Try again in a few minutes.
STEAM INVENTORY
ACTIVITY · LAST 120 DAYS
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MATCH HISTORY
Leetify history · demos enrich rosters & signals
✓
DUST2
K / D15/8
ADR77
HS%27%
RATING1.35
No signal
ROSTER01Toji02NaWeed03ROGUE04Prometheus036705232carterjec06DerZüchter07Revenge08Сидни Суини09Pgil_lll10YungMmd
WEAPON BREAKDOWN · ANALYSED DEMOS
AWP8 kills · 25% HS
AK-472 kills · 50% HS
Glock-182 kills · 50% HS
P20002 kills · 0% HS
SSG 081 kills · 0% 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.
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â—† ALLEGEDSignals are model-flagged from demo analysis and public data: triage, not a verdict. Every finding is appealable.