yorgi

yorgi — CS2 Stats

76561198292889307[U:1:332623579]Steam profile ↗✓ No bans

791Tracked matches43%Win rate2023Tracked since
843Hours in CS9Hrs last 2 wks
CSDB Rating2.8 LearningClutch Specialist
Premier CS Rating3,716Grey band · top ~84.2% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 3 Nov 2026 (2 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

3,716Peak Premier in tracked matches
49Days played since 2026-07-25

Premier CS Rating

  • At peak — 3,716
  • Next: Light Blue band at 5,000 — 1,284 to go

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

How this compares with the same rank

Median values for Grey band among CSDB-tracked players (n=3,645), 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 playerGrey band medianLight Blue band medianvs Light Blue band
Headshot rate37.6%38.2%39.9%2.3% short
Shot accuracy7.1%3.6%7.0%above
Kill/death ratio0.680.830.920.23 short
Match win rate35.8%40.2%42.3%6.5% short

This profile matches the typical Light Blue band player on 1 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Light Blue band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGyorgiPREMIER3,716 · Grey bandcsdb.gg/stats

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Performance scores

Aim33
Positioning36
Utility32

0–100 skill scores via Leetify.

Recent form

STEADY41–53–6Last 10041%Win rateWWTLLWWLWL

Last 10 vs previous 10: +10pp win rate · −0.00 avg rating · +2.9pp headshot accuracy · −25ms reaction

Win rate +10pp 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

  • 2–2–1 · 40% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 13%
  • Avg reaction 655ms

Last 10

  • 5–4–1 · 50% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 13%
  • Avg reaction 632ms

Last 20

  • 9–9–2 · 45% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 12%
  • Avg reaction 645ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+5.8 against its own average).

Aim3.3
Utility3.2
Positioning3.6
Opening Duels0.0
Clutch10.0

Strong CT-side openerLimited utility dependenceReliable in 1v1s

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

iM

Plays most like iM 79% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-duel success; 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. 647ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 67% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim3.3
Positioning3.6
Utility3.2
Mechanics3.8
Opening Duels1.1
Win Impact2.6

Composite 2.8/10 (Learning), 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-0.07−0.01
first ⅓ avg -0.05 → last ⅓ avg -0.07
Reaction time639ms−65ms
first ⅓ avg 704ms → last ⅓ avg 639ms
Headshot accuracy11.3%−2.4%
first ⅓ avg 13.7% → last ⅓ avg 11.3%

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

0.15Best match rating · 13–2 · mirage, 27 Jul →
50%Best headshot accuracy · 0–4 · dust2, 26 Jul →
438msFastest reaction time · 0–13 · cache, 7 Oct →
13–0Biggest win · mirage, 26 Jul →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W2Current streak
4–6In matches decided by ≤2 rounds
4Overtime games

Map breakdown

mirageBest map · 41% over 69infernoWeakest map · 38% over 8
MapGradePlayedRecordWin rateAvg rating
mirageC6928–4141%-0.06
dust2C156–940%-0.06
infernoC83–538%-0.08
anubis—31–233%-0.08
ancient—21–150%-0.10
cache—21–150%-0.08
nuke—11–0100%-0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

18,991Lifetime kills
0.68K/D
1,375Matches
35.8%Match win rate
37.6%Headshot %
7.1%Shot accuracy · Top 50% of Grey band
1,413MVPs
498Hours (in match)
472Bombs planted
133Bombs defused

Most-used weapons

Lifetime map wins

859inferno
811dust2
283nuke
46vertigo
35cbble
19train
13italy
12lake

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

Faceit stats

Combat

15Matches
33%Win rate
0.46Avg K/D
53.4ADR
32%Headshot %

Clutches & streaks

100%1v1 clutch win
0%1v2 clutch win
1Longest win streak

Recent Faceit resultsWLWLW

MapMatchesWin rateAvg K/DAvg kills
Mirage633%0.6510.8
Inferno367%0.5210.7
Dust220%0.367.0
Nuke1100%0.5910.0
Ancient10%0.000.0

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.

11.3%Headshot accuracy
27.2%Accuracy (enemy spotted)
28.0%Spray accuracy
67.2%Counter-strafing
7.8°Preaim
647msReaction time
36.2%T opening success
32.7%CT opening success
0.68Enemies flashed / flash
2.7%Flash assists
4.30HE damage / grenade
4.36Flashes / 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. Best CS2 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 11.3079% — below the 15% mark we flag

    Aim Training →
  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 36.2153% — 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.

38% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage13–10-0.0012%4 Nov →
ancient13–10-0.0713%3 Nov →
mirage15–15-0.0811%3 Nov →
anubis9–13-0.0812%2 Nov →
mirage4–13-0.1017%2 Nov →
anubis13–8-0.1010%1 Nov →
inferno13–8-0.0612%1 Nov →
mirage10–13-0.0515%1 Nov →
nuke16–14-0.0314%1 Nov →
dust211–13-0.0620%31 Oct →
mirage2–90.047%30 Oct →
mirage13–8-0.0316%28 Oct →
inferno13–7-0.109%21 Oct →
mirage8–13-0.1114%20 Oct →
mirage13–11-0.0613%20 Oct →
mirage7–13-0.0515%19 Oct →
mirage13–8-0.058%18 Oct →
mirage6–13-0.097%16 Oct →
mirage3–13-0.097%16 Oct →
mirage12–12-0.098%16 Oct →
mirage8–13-0.0415%16 Oct →
mirage2–13-0.089%15 Oct →
mirage10–13-0.096%12 Oct →
mirage6–13-0.115%12 Oct →
inferno11–13-0.0912%11 Oct →
anubis6–13-0.0710%11 Oct →
mirage13–5-0.0317%11 Oct →
mirage1–9-0.0920%9 Oct →
cache13–9-0.080%9 Oct →
mirage13–50.024%9 Oct →
ancient2–13-0.135%7 Oct →
cache0–13-0.0821%7 Oct →
mirage13–8-0.0610%7 Oct →
inferno5–13-0.077%6 Oct →
mirage13–11-0.0616%5 Oct →
mirage13–10-0.108%4 Oct →
mirage13–7-0.0513%4 Oct →
mirage5–13-0.0621%3 Oct →
mirage13–8-0.029%25 Sept →
mirage2–13-0.1010%24 Sept →
mirage13–4-0.0115%24 Sept →
mirage12–12-0.1111%24 Sept →
mirage13–7-0.074%23 Sept →
mirage10–13-0.0922%21 Sept →
mirage13–60.024%20 Sept →
mirage12–12-0.1010%20 Sept →
mirage12–12-0.0416%20 Sept →
mirage12–12-0.109%20 Sept →
mirage13–3-0.1018%20 Sept →
mirage13–8-0.025%19 Sept →
mirage13–8-0.088%19 Sept →
mirage13–8-0.057%18 Sept →
mirage5–13-0.0910%18 Sept →
mirage5–13-0.1117%17 Sept →
mirage10–13-0.118%15 Sept →
mirage6–13-0.0426%14 Sept →
mirage10–13-0.0513%14 Sept →
mirage13–40.0110%13 Sept →
dust211–13-0.0818%13 Sept →
mirage9–13-0.0613%12 Sept →
dust213–10-0.076%12 Sept →
mirage7–13-0.0811%11 Sept →
dust21–9-0.0611%11 Sept →
mirage5–13-0.0822%11 Sept →
mirage7–130.0613%6 Sept →
dust213–4-0.0311%2 Sept →
dust213–9-0.0516%2 Sept →
dust23–13-0.0511%1 Sept →
inferno7–13-0.0414%28 Aug →
dust213–11-0.0713%28 Aug →
mirage1–13-0.080%28 Aug →
inferno13–6-0.0511%27 Aug →
mirage4–13-0.0813%27 Aug →
mirage8–13-0.0516%26 Aug →
mirage13–9-0.099%25 Aug →
mirage13–4-0.078%25 Aug →
mirage11–13-0.098%25 Aug →
dust213–7-0.0333%25 Aug →
mirage13–3-0.0614%24 Aug →
mirage13–10-0.068%24 Aug →
mirage6–13-0.0617%9 Aug →
mirage10–13-0.0331%4 Aug →
dust22–13-0.1011%4 Aug →
mirage13–10-0.029%3 Aug →
mirage9–130.0319%30 Jul →
dust211–13-0.0315%27 Jul →
mirage13–20.1511%27 Jul →
dust212–16-0.1321%26 Jul →
mirage5–13-0.0515%26 Jul →
dust28–13-0.079%26 Jul →
mirage13–00.000%26 Jul →
mirage5–13-0.0615%26 Jul →
mirage14–16-0.1012%26 Jul →
dust213–7-0.046%26 Jul →
inferno7–13-0.098%26 Jul →
mirage13–9-0.0517%26 Jul →
dust20–4-0.0550%26 Jul →
mirage1–13-0.079%26 Jul →
inferno9–13-0.118%25 Jul →
mirage13–5-0.0614%25 Jul →

Match data via Leetify.

Recent teammates

Milestones

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

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