76561197963559603

nuke
dust2
train
anubis
mirage
ancient
inferno
vertigo
overpass
Trusted
insights

Performance Snapshot

Everything at a glance — full context in the Aim, Mechanics & Trust tabs
38
TeamDocks
our rating
44
Aim
leetify
50
Positioning
leetify
58
Utility
leetify
Best match
19–11 · 1.45
Nuke · peak rating
Matches analysed
27 · 0.87 avg
our demo parsing
Core mechanics vs pro benchmark
Weak Normal Slightly Sus Suspicious Highly Sus
Overall K/D 0.80 · Weak
HS % 29.4% · Weak
Spray Control 56.8 · Normal
Preaim 9.0° · Normal
Counter-Strafing 70.8% · Normal
Time to Damage 690ms · Weak
CS2 Hours
private
Account Age
Steam Level
Bans
0
clean
Games
private
Friends
private
Country
unknown
TeamDocks Rating
38
27 matches with us
database

TeamDocks Match Data

27 matches · our own demo analysis
Performance
TD Rating
38
our skill index
Ø Rating
0.87
Ø K/D
0.8
Ø ADR
59.8
Ø KAST
69.9%
Ø HS
29.4%
Kill-level signals
Wallbang Kills
0.3%
Smoke Kills
2.7%
Ø Kill Distance
16.9m
Duel & utility signals
Opening Duel Win
36.7%
29–50 openings
Trade Kills
46
teammate deaths avenged
Clutch Win
16.1%
15/93 1vX won
Ø Utility Dmg
50.1
HE + molotov, per match
Flash Assists
3
enemies blinded → team frag
Ø Equip Value
$3,487
post-buy, per round
Full-buy Win
54.5%
rounds won on a full buy
military_tech

TeamDocks Rating

27 matches · high confidence

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.

Weighted across 8 measured dimensions; weights renormalize over whatever data we have.

38
050100
Impact Rating27ADR28KAST57K/D17Headshot %19Spray Control57Counter-Strafe76Flash Quality28
KAST 69.9%
14% weight +8.1
Impact Rating 0.87
27% weight +7.2
Counter-Strafe 76
10% weight +7.2
Spray Control 56.8
11% weight +6.5
ADR 59.8
14% weight +4.0
K/D 0.8
11% weight +1.9
Headshot % 29.4%
8% weight +1.4
Flash Quality 28%
5% weight +1.3

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.