Goelise

Goelise — CS2 Stats

FR76561198388192355[U:1:427926627]Steam profile ↗✓ No bans

2,060Tracked matches53%Win rate2022Tracked since
3,652Hours in CS37Hrs last 2 wks
CSDB Rating5.6 SolidSupport
FaceitLevel 8 · 1,255 ELOTop 31.2% of ranked FACEIT players
WingmanMaster Guardian II
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 19 Sep 2026 (47 days ago). Ranks are recorded once per day this page is viewed.

0Faceit ELO · 1,255 → 1,255
+99Tracked matches · now 2,060
+13.3ppWin rate · 40.0% → 53.3%

Rating over time

Faceit ELO: 1,255 +0 31 Aug – 19 Sept · 3 observations
1,2551,255peak 1,25531 Aug19 Sept
1,255Highest Faceit ELO seen on CSDB
56Days played since 2026-06-24

Faceit ELO

  • At peak — 1,255
  • Next: Level 7 at 1,351 — 96 to go
  • Reached: Level 6 · Level 5 · Level 4 · Level 3
  • Level 6 first seen 2026-08-31
  • Level 5 first seen 2026-08-31

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

How this compares with the same rank

Median values for Level 8 among CSDB-tracked players (n=15,525), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerLevel 8 medianLevel 9 medianvs Level 9
Headshot rate64.8%46.8%48.2%above
Shot accuracy8.5%13.0%13.2%4.7% short
Kill/death ratio0.801.061.070.28 short
Match win rate41.9%46.3%46.9%5.0% short

This profile matches the typical Level 9 player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 9 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGGoeliseFACEITLevel 8 · 1,255 ELOSTANDINGTop 31.2% of rankedPEAK ELO1,255csdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim83
Positioning52
Utility64

0–100 skill scores via Leetify.

Recent form

STEADY40–55–5Last 10040%Win rateWWLWWLLWLL

Last 10 vs previous 10: 0pp win rate · +0.03 avg rating · +2.2pp headshot accuracy · −30ms reaction

Win rate 0pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 4–1 · 80% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 18%
  • Avg reaction 455ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 17%
  • Avg reaction 475ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 16%
  • Avg reaction 490ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Support — Utility contribution stands above the rest of this profile (+2.6 against its own average).

Aim8.3
Utility6.4
Positioning5.2
Opening Duels0.3
Clutch3.2

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

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

ropz

Plays most like ropz 78% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-duel success.

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

Positioning. Positioning trails aim by 31 points — deaths here waste a strong aim profile.

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

Aim8.3
Positioning5.2
Utility6.4
Mechanics7.3
Opening Duels0.7
Win Impact6.1

Composite 5.6/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.00+0.01
first ⅓ avg -0.02 → last ⅓ avg -0.00
Reaction time496ms−149ms
first ⅓ avg 644ms → last ⅓ avg 496ms
Headshot accuracy16.3%−7.2%
first ⅓ avg 23.5% → last ⅓ avg 16.3%

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.

Personal bests

0.25Best match rating · 9–3 · debris, 15 Jul →
54%Best headshot accuracy · 9–3 · vertigo, 4 Jul →
328msFastest reaction time · 8–8 · vertigo, 21 Aug →
13–0Biggest win · inferno, 26 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
W2Current streak
6–14In matches decided by ≤2 rounds
5Overtime games

Map breakdown

cacheBest map · 54% over 13infernoWeakest map · 27% over 22
MapGradePlayedRecordWin rateAvg rating
infernoD226–1627%-0.02
dust2C167–944%-0.02
nukeC146–843%-0.02
cacheB137–654%-0.01
vertigoD124–833%-0.01
ancientB63–350%-0.03
anubis—43–175%-0.02
debris—42–250%0.00
overpass—31–233%-0.03
poseidon—20–20%-0.17
eldorado—20–20%-0.03
boulder—10–10%-0.09
mirage—11–0100%-0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (27% over 22). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

99,581Lifetime kills
0.80K/D
4,602Matches
41.9%Match win rate
64.8%Headshot % · Top 5% of Level 8 players
8.5%Shot accuracy
11,350MVPs
4,562Hours (in match)
3,713Bombs planted
1,290Bombs defused

Most-used weapons

AK-4745,473
AWP2,405
MP91,675
MAC-101,233
FAMAS1,080

Lifetime map wins

8,710inferno
5,147nuke
4,208dust2
2,538vertigo
720cbble
448train
35office
26italy

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

807Matches
50%Win rate
0.97Avg K/D
70.8ADR
47%Headshot %

Clutches & streaks

36%1v1 clutch win
17%1v2 clutch win
11Longest win streak

Recent Faceit resultsLLWWW

MapMatchesWin rateAvg K/DAvg kills
Dust218647%0.8913.2
Inferno17847%1.0114.3
Nuke12757%1.0014.2
Ancient10554%1.0215.4
Anubis5654%0.9613.7
Mirage5046%1.0313.7
Cache4635%0.9914.1
Train2752%0.9713.7

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.

16.6%Headshot accuracy
37.0%Accuracy (enemy spotted)
41.3%Spray accuracy
82.8%Counter-strafing
9.9°Preaim
493msReaction time
31.5%T opening success
34.3%CT opening success
0.50Enemies flashed / flash
11.1%Flash assists
9.05HE damage / grenade
15.66Flashes / 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. 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 31.4869% — below the 40% mark we flag

Spend your practice time on Inferno

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

27% win rate across 22 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis13–9-0.0211%2 Nov →
ancient13–80.0215%27 Oct →
dust210–130.0230%26 Oct →
inferno13–00.057%26 Oct →
dust213–70.0827%24 Oct →
nuke4–90.1013%21 Oct →
inferno8–13-0.0118%20 Oct →
cache13–90.0121%17 Oct →
ancient7–13-0.0410%17 Oct →
cache5–13-0.0721%17 Oct →
cache10–13-0.0212%17 Oct →
nuke5–13-0.0712%16 Oct →
dust211–13-0.029%12 Oct →
vertigo11–130.0319%12 Oct →
cache13–90.0318%12 Oct →
ancient10–13-0.0511%12 Oct →
dust213–90.0120%12 Oct →
ancient13–9-0.0417%12 Oct →
vertigo13–90.0021%12 Oct →
anubis13–10-0.0411%9 Oct →
dust213–70.1017%8 Oct →
cache16–19-0.0511%8 Oct →
dust213–8-0.0318%8 Oct →
nuke9–6-0.0024%6 Oct →
vertigo9–50.0118%6 Oct →
vertigo5–9-0.066%26 Sept →
inferno14–160.0123%20 Sept →
cache13–110.0412%13 Sept →
inferno19–160.0215%12 Sept →
nuke13–110.0018%11 Sept →
inferno9–13-0.0525%9 Sept →
dust28–13-0.0219%8 Sept →
anubis16–13-0.0410%7 Sept →
boulder10–13-0.0922%3 Sept →
cache13–80.0232%3 Sept →
nuke8–130.0415%3 Sept →
dust28–13-0.0418%3 Sept →
dust24–13-0.1021%3 Sept →
cache11–13-0.0110%2 Sept →
cache11–13-0.0120%31 Aug →
nuke13–60.1331%30 Aug →
overpass11–13-0.0730%29 Aug →
cache13–9-0.0423%29 Aug →
dust28–13-0.0529%29 Aug →
cache13–60.0317%29 Aug →
cache13–110.0519%25 Aug →
dust213–8-0.0528%24 Aug →
vertigo8–80.0028%21 Aug →
dust28–13-0.0722%21 Aug →
vertigo9–6-0.0315%18 Aug →
debris4–9-0.089%18 Aug →
nuke5–9-0.0928%18 Aug →
inferno9–60.0223%18 Aug →
vertigo8–13-0.0714%17 Aug →
vertigo3–90.0323%11 Aug →
inferno4–9-0.1312%11 Aug →
poseidon1–9-0.2013%9 Aug →
eldorado6–90.0121%9 Aug →
poseidon6–9-0.1436%9 Aug →
inferno4–13-0.0721%3 Aug →
dust213–3-0.029%2 Aug →
overpass9–7-0.0913%1 Aug →
debris4–9-0.1910%30 Jul →
vertigo4–9-0.0621%30 Jul →
nuke9–4-0.1010%30 Jul →
inferno8–8-0.1415%29 Jul →
nuke9–20.1011%29 Jul →
inferno4–13-0.0628%27 Jul →
inferno13–7-0.037%26 Jul →
dust210–13-0.0716%25 Jul →
nuke8–13-0.0412%23 Jul →
eldorado7–9-0.0616%22 Jul →
debris9–70.0214%22 Jul →
inferno11–13-0.0418%20 Jul →
inferno11–13-0.0329%18 Jul →
inferno4–13-0.0821%16 Jul →
dust213–10-0.0016%16 Jul →
debris9–30.2541%15 Jul →
inferno9–13-0.1013%14 Jul →
ancient13–11-0.0312%10 Jul →
nuke13–100.0011%9 Jul →
inferno13–50.0842%7 Jul →
vertigo9–30.0554%4 Jul →
inferno6–9-0.0925%4 Jul →
inferno7–90.0329%4 Jul →
anubis11–130.0132%2 Jul →
cache2–13-0.0819%1 Jul →
vertigo6–13-0.1024%1 Jul →
inferno4–9-0.1031%1 Jul →
overpass8–80.0742%1 Jul →
nuke8–8-0.0218%1 Jul →
nuke1–9-0.2127%30 Jun →
vertigo7–90.0532%30 Jun →
inferno8–80.0418%30 Jun →
mirage13–10-0.0018%30 Jun →
dust213–16-0.0128%27 Jun →
inferno11–13-0.0615%24 Jun →
ancient11–13-0.0418%24 Jun →
inferno9–10.2433%24 Jun →
nuke5–9-0.0820%24 Jun →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.