76561198098663455

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76561198098663455

nuke
cache
dust2
train
office
anubis
golden
mirage
ancient
inferno
palacio
overpass
Trusted
insights

Performance Snapshot

Everything at a glance — full context in the Aim, Mechanics & Trust tabs
56
TeamDocks
our rating
3
Aim
leetify
29
Positioning
leetify
70
Utility
leetify
Best match
12–7 · 1.34
Overpass · peak rating
Matches analysed
2 · 1.24 avg
our demo parsing
Core mechanics vs pro benchmark
Weak Normal Slightly Sus Suspicious Highly Sus
Overall K/D 1.33 · Normal
HS % 15.9% · Weak
Spray Control 39.6 · Weak
Preaim 9.8° · Weak
Counter-Strafing 36.2% · Weak
Time to Damage 740ms · Weak
CS2 Hours
private
Account Age
Steam Level
Bans
0
clean
Games
private
Friends
private
Country
unknown
TeamDocks Rating
56
2 matches with us
database

TeamDocks Match Data

2 matches · our own demo analysis
Performance
TD Rating
56
our skill index
Ø Rating
1.24
Ø K/D
1.33
Ø ADR
79.3
Ø KAST
79.3%
Ø HS
15.9%
Kill-level signals
Wallbang Kills
0%
Smoke Kills
10.3%
Ø Kill Distance
14.2m
Duel & utility signals
Ø Utility Dmg
169.5
HE + molotov, per match
Ø Equip Value
$4,272
post-buy, per round
military_tech

TeamDocks Rating

2 matches · provisional

Our own 0–100 skill index, a weighted composite of every performance dimension we can measure from this player's parsed demos — not Leetify's rating. Each row below shows its raw value, its 0–100 sub-score and how many points it contributed to the final number.

Provisional — based on only 2 analyzed matches. Firms up as more of this player's games get processed.

56
050100
Impact Rating64ADR56KAST84K/D61Headshot %0Spray Control40Counter-Strafe59Flash Quality30
Impact Rating 1.24
27% weight +17.1
KAST 79.3%
14% weight +12.0
ADR 79.3
14% weight +8.0
K/D 1.33
11% weight +7.0
Counter-Strafe 59
10% weight +5.6
Spray Control 39.6
11% weight +4.6
Flash Quality 30%
5% weight +1.4
Headshot % 15.9%
8% weight +0.0

Final score = weighted average of each dimension's 0–100 sub-score. Contribution = sub-score × (renormalized weight). Not affiliated with Valve/Leetify/FACEIT — this is our own measure from our own demo parsing.