guldlax_

guldlax_ — CS2 Stats

SE76561198364626336[U:1:404360608]Steam profile ↗✓ No bans

410Tracked matches55%Win rate2024Tracked since
CSDB Rating5.9 SolidAggressive Rifler
FaceitLevel 5Top 67.6% of ranked FACEIT players
WingmanGold Nova Master
Ladder ranks via Leetify

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CSDB.GGguldlax_FACEITLevel 5STANDINGTop 67.6% of rankedcsdb.gg/stats

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Performance scores

Aim75
Positioning54
Utility38

0–100 skill scores via Leetify.

Recent form

STEADY52426Last 10052%Win rateLLWLWWWLWL

Last 10 vs previous 10: +10pp win rate · -0.04 avg rating

Player DNA

Primary style: Aggressive RiflerTakes opening fights often, backed by a strong aim profile.

Aim7.5
Aggression8.8
Utility3.8
Positioning5.4
Opening Duels3.5
Clutch5.8

Strong CT-side opener

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 87% playstyle similarity

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

Where you differ: lower aim profile; lower utility contribution.

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 52% on CT to 35% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 584ms 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

Aim7.5
Positioning5.4
Utility3.8
Mechanics6.6
Opening Duels3.5
Win Impact6.7

Composite 5.9/10 (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 rating-0.01−0.03
first ⅓ avg 0.02 → last ⅓ avg -0.01
Reaction time583ms−31ms
first ⅓ avg 615ms → last ⅓ avg 583ms
Headshot accuracy14.8%−2.6%
first ⅓ avg 17.4% → last ⅓ avg 14.8%

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

0.21Best rating — inferno 9–7
130Biggest win — dust2
7Longest win streak
L2Current streak
89In matches decided by ≤2 rounds
8Overtime games

Map breakdown

nukeBest map · 67% over 6anubisWeakest map · 40% over 10
MapGradePlayedRecordWin rateAvg rating
dust2C27121544%-0.02
infernoA22121055%0.02
mirageA1710759%0.01
anubisC104640%-0.01
ancientA95456%0.04
nukeS64267%0.02
cacheA53260%0.01
train220100%-0.04
overpass1010%-0.05
office1010%-0.02

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (40% over 10). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

67Matches
42%Win rate
1.13Avg K/D
83.2ADR
48%Headshot %

Clutches & streaks

49%1v1 clutch win
28%1v2 clutch win
6Longest win streak

Recent Faceit resultsWLLLW

MapMatchesWin rateAvg K/DAvg kills
Mirage2236%1.1114.4
Anubis933%1.6721.0
Dust2757%1.0917.1
Inferno743%1.0114.3
Vertigo633%0.9813.3
Nuke683%0.9914.5
Ancient650%1.0917.8
Overpass30%0.8413.3

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

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

15.0%Headshot accuracy
37.3%Accuracy (enemy spotted)
39.6%Spray accuracy
79.8%Counter-strafing
8.6°Preaim
584msReaction time
35.3%T opening success
52.4%CT opening success
0.42Enemies flashed / flash
3.0%Flash assists
9.14HE damage / grenade
7.20Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

  1. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.4187 — below the 0.5 mark we flag

    Grenade Lineups
  2. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 35.2825% — below the 40% mark we flag

Spend your practice time on Anubis

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

40% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategyAnubis grenade lineups

Recent matches

MapScoreRatingHS%Date
inferno3–9-0.1820%13 Jul
inferno3–9-0.0910%12 Jul
dust213–5-0.0312%11 Jul
dust24–12-0.0512%11 Jul
dust216–130.0113%10 Jul
cache4–2-0.010%10 Jul
anubis13–70.0210%8 Jul
inferno7–90.0010%7 Jul
inferno9–50.0123%7 Jul
inferno5–9-0.096%7 Jul
overpass6–13-0.0515%6 Jul
dust22–13-0.0512%6 Jul
dust213–11-0.0124%5 Jul
ancient4–130.015%3 Jul
anubis15–150.0211%2 Jul
ancient13–70.0411%2 Jul
mirage6–13-0.0418%1 Jul
mirage13–50.038%1 Jul
inferno13–100.0217%30 Jun
anubis8–130.0320%30 Jun
dust213–9-0.0523%29 Jun
ancient11–130.0713%29 Jun
mirage13–6-0.0110%28 Jun
anubis9–13-0.0421%26 Jun
ancient9–13-0.066%26 Jun
office5–13-0.0229%26 Jun
mirage13–2-0.0016%26 Jun
inferno13–9-0.0016%26 Jun
inferno9–20.073%26 Jun
nuke13–100.0822%23 Jun
mirage11–13-0.029%23 Jun
mirage2–13-0.0350%23 Jun
inferno9–00.0915%23 Jun
anubis4–30.0425%23 Jun
anubis13–10-0.0113%22 Jun
mirage13–2-0.0217%22 Jun
dust211–13-0.050%22 Jun
train13–8-0.0225%22 Jun
dust25–13-0.0220%22 Jun
mirage13–5-0.0019%20 Jun
dust212–16-0.0514%19 Jun
nuke16–130.0413%18 Jun
dust213–0-0.1340%17 Jun
dust213–8-0.0612%17 Jun
dust20–5-0.090%17 Jun
ancient13–80.0420%17 Jun
anubis13–7-0.0418%17 Jun
mirage11–13-0.0021%17 Jun
mirage13–8-0.0320%17 Jun
inferno9–20.1612%17 Jun
anubis2–130.0117%15 Jun
dust211–130.0225%15 Jun
dust25–13-0.0614%14 Jun
inferno13–70.064%14 Jun
mirage13–70.0519%14 Jun
dust213–5-0.0346%13 Jun
train13–11-0.0527%13 Jun
inferno12–12-0.0117%13 Jun
mirage11–130.0013%13 Jun
cache13–110.036%13 Jun
inferno7–9-0.018%12 Jun
dust210–130.0224%10 Jun
nuke13–40.1219%5 Jun
dust27–130.0414%4 Jun
inferno13–100.1216%30 May
dust213–80.0316%30 May
anubis1–13-0.1013%30 May
dust29–130.0118%29 May
dust213–8-0.0026%29 May
nuke3–13-0.1015%29 May
dust28–13-0.0126%28 May
dust210–13-0.0210%28 May
ancient16–130.0421%27 May
dust213–70.0624%27 May
ancient13–60.1121%27 May
mirage13–50.0722%27 May
mirage13–60.0928%26 May
ancient13–20.066%26 May
inferno16–140.0227%26 May
inferno8–8-0.0213%26 May
cache10–130.0526%23 May
inferno9–70.002%23 May
nuke6–13-0.0511%22 May
cache11–13-0.0230%22 May
cache13–50.019%22 May
dust29–130.0231%22 May
dust213–6-0.0211%22 May
nuke13–100.0518%21 May
inferno2–9-0.1217%21 May
inferno9–70.2114%21 May
inferno9–40.160%21 May
inferno13–16-0.0717%20 May
mirage13–90.0918%20 May
ancient8–130.0219%20 May
anubis12–12-0.0318%20 May
dust27–130.0019%19 May
mirage8–13-0.0621%19 May
dust213–70.0214%19 May
inferno8–80.0111%18 May
mirage15–150.0414%18 May

Match data via Leetify.

Recent teammates

Milestones

100 Matches
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