Skoda octavia enjoyer

Skoda octavia enjoyer — CS2 Stats

CZ76561198353180436[U:1:392914708]Steam profile ↗✓ No bans

701Tracked matches36%Win rate2022Tracked since
2,210Hours in CS1Hrs last 2 wks
CSDB Rating4.2 DevelopingSupport
Premier CS Rating17,071Purple band · top ~20.2% of ranked players (population est.)
FaceitLevel 3Top 90.6% of ranked FACEIT players
WingmanLegendary Eagle
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 20 Sep 2026 (39 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

Premier CS Rating: 17,071 +2,588 21 Jun – 20 Sept · 15 days played
14,48317,292peak 17,29221 Jun20 Sept
17,414Peak Premier in tracked matches
49Days played since 2026-06-21

Premier CS Rating

  • 221 below peak (17,292)
  • +2,588 over 90 days
  • Next: Pink band at 20,000 — 2,929 to go
  • Reached: Purple band · Blue band · Light Blue band

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 Level 3 among CSDB-tracked players (n=10,505), 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 3 medianLevel 4 medianvs Level 4
Headshot rate36.1%41.8%42.7%6.6% short
Shot accuracy11.1%12.2%11.2%meets
Kill/death ratio0.990.980.99meets
Match win rate46.5%43.3%43.9%above

This profile matches the typical Level 4 player on 3 of 4 comparable metrics.

Widest gap: Headshot rate. That is the metric furthest from the Level 4 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGSkoda octavia enjoyerFACEITLevel 3STANDINGTop 90.6% of rankedPREMIER17,071 · Purple bandcsdb.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

Aim52
Positioning44
Utility51

0–100 skill scores via Leetify.

Recent form

STEADY48–47–5Last 10048%Win rateLLLWWLTWWL

Last 10 vs previous 10: +20pp win rate · −0.01 avg rating · −0.4pp headshot accuracy · +29ms reaction

Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (−0.01), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 2–3 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 20%
  • Avg reaction 571ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 16%
  • Avg reaction 567ms

Last 20

  • 6–12–2 · 30% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 17%
  • Avg reaction 552ms

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 (+2.2 against its own average).

Aim5.2
Utility5.1
Positioning4.4
Opening Duels1.7
Clutch0.4

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.

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 83% 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

T-side openings. Opening success drops from 48% on CT to 25% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 577ms 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

Aim5.2
Positioning4.4
Utility5.1
Mechanics4.9
Opening Duels2.3
Win Impact0.2

Composite 4.2/10 (Developing), 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-0.03−0.03
first ⅓ avg 0.00 → last ⅓ avg -0.03
Reaction time577ms−37ms
first ⅓ avg 614ms → last ⅓ avg 577ms
Headshot accuracy17.8%+3.5%
first ⅓ avg 14.3% → last ⅓ avg 17.8%

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.

Personal bests

0.11Best match rating · 13–1 · cache, 4 Sept →
50%Best headshot accuracy · 3–5 · dust2, 6 Sept →
391msFastest reaction time · 5–13 · mirage, 30 Aug →
13–0Biggest win · dust2, 9 Sept →

Across the last 100 tracked matches.

Highlights

9Longest win streak
L3Current streak
5–4In matches decided by ≤2 rounds
9Overtime games

Map breakdown

anubisBest map · 83% over 6infernoWeakest map · 27% over 15
MapGradePlayedRecordWin rateAvg rating
mirageB3519–1654%-0.01
dust2B2815–1354%-0.01
infernoD154–1127%-0.03
anubisS65–183%0.03
cacheC52–340%0.02
overpass—42–250%0.00
nuke—31–233%-0.02
train—10–10%-0.03
ancient—10–10%-0.03
office—10–10%0.07
shelter—10–10%-0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (27% over 15). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

49,366Lifetime kills
0.99K/D · Top 50% of Level 3 players
2,867Matches
46.5%Match win rate · Top 25% of Level 3 players
36.1%Headshot %
11.1%Shot accuracy
6,886MVPs
1,242Hours (in match)
1,988Bombs planted
544Bombs defused

Most-used weapons

AK-479,951
AWP7,353
MP91,494
UMP-451,460
MAC-101,458
MP71,350

Lifetime map wins

5,608inferno
5,021dust2
1,331office
1,206nuke
561cbble
398train
198vertigo
107lake

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

Faceit stats

Combat

18Matches
44%Win rate
0.95Avg K/D
68.3ADR
32%Headshot %

Clutches & streaks

22%1v1 clutch win
0%1v2 clutch win
3Longest win streak

Recent Faceit resultsLWWWL

MapMatchesWin rateAvg K/DAvg kills
Mirage743%0.7812.4
Dust2633%0.8114.3
Inferno250%1.7617.0
Nuke1100%1.3619.0

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.

17.4%Headshot accuracy
29.6%Accuracy (enemy spotted)
31.9%Spray accuracy
72.1%Counter-strafing
9.8°Preaim
577msReaction time
25.2%T opening success
48.1%CT opening success
0.62Enemies flashed / flash
6.4%Flash assists
9.57HE damage / grenade
5.42Flashes / 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 25.2446% — 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 15 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage8–13-0.0721%28 Oct →
mirage2–130.0113%15 Oct →
mirage2–13-0.0133%12 Oct →
mirage13–90.0417%11 Oct →
mirage13–80.0616%5 Oct →
mirage4–12-0.0517%30 Sept →
overpass12–12-0.0319%20 Sept →
anubis5–00.000%20 Sept →
dust213–2-0.0613%20 Sept →
mirage1–13-0.0516%20 Sept →
dust28–13-0.0322%20 Sept →
dust212–12-0.0712%19 Sept →
mirage5–13-0.0317%16 Sept →
overpass13–100.0015%16 Sept →
dust29–13-0.0410%16 Sept →
mirage10–130.0417%15 Sept →
anubis13–80.0616%15 Sept →
inferno11–13-0.0511%15 Sept →
mirage7–130.0422%13 Sept →
dust22–13-0.0126%13 Sept →
mirage0–13-0.0811%12 Sept →
cache13–5-0.0220%12 Sept →
mirage16–14-0.0011%10 Sept →
mirage13–4-0.0726%9 Sept →
dust213–0-0.0812%9 Sept →
nuke13–16-0.0618%9 Sept →
inferno11–13-0.0430%9 Sept →
train5–13-0.0314%8 Sept →
inferno10–13-0.0219%8 Sept →
mirage13–16-0.0619%8 Sept →
cache2–13-0.0615%7 Sept →
dust23–5-0.1550%6 Sept →
dust28–13-0.0311%5 Sept →
cache13–10.119%4 Sept →
inferno2–9-0.1636%4 Sept →
ancient10–13-0.0317%4 Sept →
mirage16–12-0.0036%3 Sept →
dust213–80.0138%3 Sept →
overpass13–100.0319%3 Sept →
inferno13–10-0.0217%3 Sept →
mirage13–5-0.098%3 Sept →
dust213–100.0117%2 Sept →
dust213–110.0412%1 Sept →
mirage13–10-0.0223%1 Sept →
anubis13–40.0526%31 Aug →
mirage9–130.0613%31 Aug →
dust24–130.0522%31 Aug →
overpass6–13-0.0015%31 Aug →
nuke13–30.0519%31 Aug →
mirage13–10.0415%31 Aug →
inferno2–130.0025%31 Aug →
dust213–8-0.027%30 Aug →
inferno12–120.0113%30 Aug →
mirage5–13-0.045%30 Aug →
mirage13–40.0339%28 Aug →
mirage13–80.0620%27 Aug →
mirage9–13-0.0817%26 Aug →
dust25–13-0.036%26 Aug →
inferno6–9-0.158%26 Aug →
dust26–130.0021%23 Aug →
inferno4–13-0.0325%23 Aug →
dust213–7-0.0113%23 Aug →
inferno9–50.0626%23 Aug →
inferno13–30.0620%22 Aug →
cache4–130.0522%22 Aug →
mirage13–110.0823%18 Aug →
cache10–130.0321%18 Aug →
anubis9–130.0519%16 Aug →
mirage2–13-0.056%2 Aug →
dust216–12-0.0318%2 Aug →
office11–130.0720%28 Jul →
inferno13–5-0.0510%17 Jul →
dust213–3-0.063%15 Jul →
anubis16–13-0.0310%15 Jul →
inferno7–13-0.0419%15 Jul →
dust213–100.0714%13 Jul →
dust213–40.0323%12 Jul →
mirage13–80.0112%11 Jul →
dust23–13-0.0127%11 Jul →
shelter7–13-0.0012%10 Jul →
dust213–80.0422%10 Jul →
mirage13–90.0314%5 Jul →
mirage7–13-0.0520%5 Jul →
dust213–8-0.0117%4 Jul →
dust213–50.0113%4 Jul →
dust215–150.0210%1 Jul →
inferno6–130.0112%28 Jun →
mirage9–130.0320%27 Jun →
mirage13–6-0.0111%26 Jun →
dust22–13-0.0815%25 Jun →
dust210–130.0818%24 Jun →
mirage13–110.0113%24 Jun →
mirage16–13-0.016%24 Jun →
anubis13–30.0715%24 Jun →
nuke6–13-0.0413%23 Jun →
mirage13–9-0.0112%23 Jun →
mirage16–140.0220%23 Jun →
mirage13–30.0212%23 Jun →
inferno8–80.049%23 Jun →
dust213–9-0.048%21 Jun →

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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