fat goku

fat goku — CS2 Stats

CN76561198110033862[U:1:149768134]Steam profile ↗1 game ban

216Tracked matches45%Win rate2020Tracked since
CSDB Rating5.6 SolidHybrid Rifler
Ladder ranks via Leetify

Performance scores

Aim64
Positioning57
Utility56

0–100 skill scores via Leetify.

Recent form

STEADY53452Last 10053%Win rateLLWWWWLLLW

Last 10 vs previous 10: +0pp win rate · -0.01 avg rating

Player DNA

Primary style: Hybrid RiflerAim-led profile without a single dominant tendency.

Aim6.4
Aggression9.0
Utility5.6
Positioning5.7
Opening Duels3.8

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

jL

Plays most like jL 89% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

Where you differ: lower aim profile.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Areas to improve

Reaction time. 645ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim6.4
Positioning5.7
Utility5.6
Mechanics6.4
Opening Duels3.8
Win Impact3.3

Composite 5.6/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01−0.02
first ⅓ avg 0.04 → last ⅓ avg 0.01
Reaction time640ms−30ms
first ⅓ avg 670ms → last ⅓ avg 640ms
Headshot accuracy16.5%−0.4%
first ⅓ avg 16.9% → last ⅓ avg 16.5%

Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Highlights

0.23Best rating — anubis 13–0
130Biggest win — anubis
5Longest win streak
L2Current streak
812In matches decided by ≤2 rounds
8Overtime games

Map breakdown

anubisBest map · 82% over 11trainWeakest map · 33% over 6
MapGradePlayedRecordWin rateAvg rating
dust2B30151550%0.02
infernoB168850%-0.00
mirageA169756%0.01
ancientB136746%-0.00
anubisS119282%0.04
trainD62433%0.02
nukeB63350%-0.00
cache1010%0.02
vertigo110100%0.03

Across the last 100 tracked matches.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

16.7%Headshot accuracy
35.0%Accuracy (enemy spotted)
35.9%Spray accuracy
78.6%Counter-strafing
9.1°Preaim
645msReaction time
42.9%T opening success
47.3%CT opening success
0.63Enemies flashed / flash
7.8%Flash assists
11.17HE damage / grenade
6.89Flashes / match

Recommended for you

Spend your practice time on Train

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

33% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy

Recent matches

MapScoreRatingHS%Date
cache11–130.029%11 Jun
dust23–7-0.0414%11 Jun
dust213–100.0524%23 Mar
dust213–1-0.0133%21 Mar
dust213–30.0511%19 Mar
dust213–10.1517%19 Mar
inferno9–13-0.0220%15 Mar
dust24–13-0.1222%15 Mar
mirage8–130.0211%4 Mar
mirage13–100.0015%3 Mar
dust213–70.0324%2 Mar
inferno9–13-0.0219%2 Mar
dust213–90.0420%30 Oct
inferno13–110.0222%25 Apr
ancient13–11-0.055%22 Feb
dust25–13-0.0121%22 Feb
inferno10–130.0213%20 Feb
dust210–13-0.0111%19 Feb
dust213–50.0718%19 Feb
train9–130.0915%18 Feb
dust214–16-0.0313%18 Feb
train13–40.0312%18 Feb
inferno12–12-0.0024%17 Feb
anubis6–130.0313%17 Feb
ancient10–13-0.0318%17 Feb
mirage13–40.0612%13 Feb
dust211–130.0217%13 Feb
dust211–130.0314%13 Feb
ancient13–5-0.0018%13 Feb
dust211–130.0521%12 Feb
anubis13–9-0.075%12 Feb
dust213–160.0619%9 Feb
ancient2–90.0216%8 Feb
inferno13–90.0011%7 Feb
dust28–13-0.0213%7 Feb
inferno8–13-0.069%7 Feb
anubis0–13-0.0510%6 Feb
mirage9–13-0.0312%6 Feb
ancient13–110.0217%5 Feb
dust214–16-0.0510%5 Feb
dust213–50.1519%5 Feb
nuke13–80.0119%4 Feb
nuke13–90.0010%4 Feb
nuke14–160.0315%3 Feb
inferno13–6-0.0314%3 Feb
mirage13–70.0018%3 Feb
anubis13–3-0.0211%3 Feb
mirage13–80.0617%3 Feb
train11–13-0.0120%2 Feb
mirage13–6-0.027%1 Feb
anubis16–14-0.0510%1 Feb
ancient4–13-0.057%1 Feb
anubis13–60.0617%1 Feb
inferno16–140.0115%1 Feb
mirage10–30.0010%1 Feb
anubis13–110.0312%1 Feb
mirage11–13-0.039%1 Feb
dust29–130.0021%31 Jan
dust213–50.0420%31 Jan
mirage13–90.0418%31 Jan
nuke13–10-0.0620%31 Jan
inferno11–13-0.0020%31 Jan
ancient8–13-0.0610%31 Jan
ancient13–10-0.032%31 Jan
inferno7–13-0.0417%31 Jan
ancient9–13-0.0320%31 Jan
mirage13–10-0.0217%30 Jan
train16–14-0.0310%29 Jan
dust213–6-0.038%29 Jan
ancient8–13-0.0311%29 Jan
dust211–3-0.0317%29 Jan
ancient13–70.1310%29 Jan
inferno12–00.0920%28 Jan
dust213–10-0.0230%28 Jan
anubis13–00.178%28 Jan
train7–130.0230%28 Jan
train11–130.0112%28 Jan
dust25–13-0.0026%28 Jan
anubis13–30.0619%27 Jan
mirage11–13-0.0522%27 Jan
mirage7–130.0322%27 Jan
anubis13–40.026%27 Jan
vertigo13–70.0317%27 Jan
dust210–130.1029%27 Jan
inferno13–50.0310%27 Jan
dust215–150.0220%25 Jan
inferno13–110.0214%25 Jan
dust213–60.1119%24 Jan
ancient13–90.1016%24 Jan
mirage3–13-0.094%23 Jan
nuke4–13-0.0120%21 Jan
dust213–20.0613%21 Jan
mirage13–40.1115%21 Jan
inferno1–13-0.1021%20 Jan
nuke7–130.0018%20 Jan
ancient7–13-0.0315%20 Jan
dust213–60.1217%19 Jan
anubis13–00.2319%19 Jan
mirage9–130.1220%19 Jan
inferno13–90.0121%19 Jan

Match data via Leetify.

Recent teammates

Milestones

100 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →