vegemite

vegemite — CS2 Stats

AU76561198855795910[U:1:895530182]Steam profile ↗✓ No bans

125Tracked matches34%Win rate2021Tracked since
337Hours in CS
CSDB Rating4.2 DevelopingPositional Player
FaceitLevel 3Top 90.6% of ranked FACEIT players
WingmanSilver I
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 26 Sep 2026 (12 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 125 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 7,767 +775 15 Feb – 2 Apr · 15 days played
6,9929,166peak 9,16615 Feb2 Apr
9,166Peak Premier in tracked matches
39Days played since 2024-06-19

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

Compare periods

Last 30 days vs previous 30

No matches recorded between 10 Sep 2026 and 8 Oct 2026.

Measured 10 Sep 2026 → 8 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Level 3 among CSDB-tracked players (n=10,051), 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 rate43.8%41.8%42.7%above
Shot accuracy18.9%12.2%11.3%above
Kill/death ratio1.320.980.99above
Match win rate82.4%43.3%43.9%above

Across every metric we can compare, this profile already matches the typical Level 4 player. Rank still comes from winning matches — this is a performance comparison, not a prediction.

Share this profile

CSDB.GGvegemiteFACEITLevel 3STANDINGTop 90.6% of rankedcsdb.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

Aim44
Positioning52
Utility36

0–100 skill scores via Leetify.

Recent form

COLD42–52–6Last 10042%Win rateLWLLLLLLLL

Last 10 vs previous 10: −40pp win rate · +0.03 avg rating · +2.0pp headshot accuracy · −47ms reaction

Win rate down 40pp 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 (+0.03), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 15%
  • Avg reaction 764ms

Last 10

  • 1–9 · 10% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 15%
  • Avg reaction 716ms

Last 20

  • 6–14 · 30% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 14%
  • Avg reaction 740ms

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: Positional Player — Positioning stands above the rest of this profile (+1 against its own average).

Aim4.4
Utility3.6
Positioning5.2
Opening Duels3.7

Effective flashesLimited utility dependence

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

donk

Plays most like donk 78% 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. 709ms 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

Aim4.4
Positioning5.2
Utility3.6
Mechanics6.8
Opening Duels2.7
Win Impact0.0

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-0.02−0.01
first ⅓ avg -0.01 → last ⅓ avg -0.02
Reaction time700ms+7ms
first ⅓ avg 693ms → last ⅓ avg 700ms
Headshot accuracy13.6%+1.2%
first ⅓ avg 12.4% → last ⅓ avg 13.6%

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

0.18Best match rating · 13–11 · mirage, 29 Jan →
26%Best headshot accuracy · 10–13 · inferno, 28 Jan →
500msFastest reaction time · 13–4 · inferno, 20 Mar →
13–0Biggest win · ancient, 31 Jan →

Across the last 100 tracked matches.

Highlights

5Longest win streak
4–3In matches decided by ≤2 rounds
3Overtime games

Map breakdown

nukeBest map · 56% over 9infernoWeakest map · 32% over 22
MapGradePlayedRecordWin rateAvg rating
mirageB2512–1348%-0.00
infernoD227–1532%-0.02
dust2C219–1243%0.00
ancientB115–645%-0.03
nukeA95–456%0.00
anubis—42–250%0.02
vertigo—30–30%-0.04
overpass—31–233%-0.01
train—11–0100%0.07
warden—10–10%-0.06

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (32% over 22). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

24,699Lifetime kills
1.32K/D · Top 10% of Level 3 players
4,782Matches
82.4%Match win rate · Top 1% of Level 3 players
43.8%Headshot % · Top 50% of Level 3 players
18.9%Shot accuracy · Top 10% of Level 3 players
3,850MVPs
337Hours (in match)
671Bombs planted
475Bombs defused

Most-used weapons

Lifetime map wins

1,853dust2
633nuke
622inferno
500vertigo
451lake
327safehouse
306ar_shoots
262train

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

Skill profile

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

13.8%Headshot accuracy
30.8%Accuracy (enemy spotted)
30.3%Spray accuracy
80.8%Counter-strafing
9.0°Preaim
709msReaction time
33.7%T opening success
48.0%CT opening success
0.71Enemies flashed / flash
5.3%Flash assists
4.55HE damage / grenade
3.99Flashes / 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 13.7906% — below the 15% mark we flag

    Aim Training →
  2. Best CS2 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 708.5372ms — above the 700ms mark we flag

    Aim Training →
  3. Grenades & Utility

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 3.9871 — below the 4 mark we flag

    Grenade Lineups →
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.

32% 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
mirage9–130.0322%10 May →
ancient13–80.0116%19 Apr →
inferno8–13-0.0716%19 Apr →
mirage10–13-0.0715%2 Apr →
nuke7–130.138%2 Apr →
dust25–13-0.0218%2 Apr →
dust210–13-0.0310%2 Apr →
mirage14–160.0315%29 Mar →
ancient3–13-0.0312%29 Mar →
mirage3–13-0.0219%29 Mar →
ancient3–13-0.0824%28 Mar →
dust26–13-0.0714%28 Mar →
inferno4–13-0.0910%28 Mar →
dust213–9-0.0315%28 Mar →
dust22–130.0811%28 Mar →
ancient5–13-0.068%22 Mar →
ancient13–8-0.097%22 Mar →
nuke13–40.0119%22 Mar →
mirage16–130.0012%20 Mar →
mirage13–9-0.0212%20 Mar →
inferno13–40.005%20 Mar →
dust211–130.0014%20 Mar →
ancient9–13-0.0518%20 Mar →
mirage13–10-0.0324%15 Mar →
vertigo12–12-0.0313%10 Mar →
overpass10–13-0.0810%1 Mar →
anubis7–130.0014%1 Mar →
mirage13–110.0510%1 Mar →
mirage5–13-0.0615%1 Mar →
overpass13–60.037%28 Feb →
mirage13–50.0615%23 Feb →
inferno13–4-0.0012%23 Feb →
dust210–13-0.027%22 Feb →
mirage7–13-0.0910%21 Feb →
inferno3–13-0.047%19 Feb →
mirage6–130.0113%19 Feb →
mirage1–13-0.0219%19 Feb →
dust213–20.0419%18 Feb →
mirage13–80.0311%18 Feb →
dust213–70.1111%17 Feb →
mirage10–13-0.0217%15 Feb →
dust213–90.0812%15 Feb →
nuke13–9-0.0124%15 Feb →
nuke10–13-0.048%14 Feb →
dust213–60.0112%14 Feb →
mirage9–13-0.008%14 Feb →
inferno13–5-0.067%13 Feb →
dust213–40.0315%13 Feb →
dust212–120.0120%13 Feb →
mirage13–90.0213%12 Feb →
dust213–9-0.0111%12 Feb →
inferno10–13-0.0116%10 Feb →
ancient13–60.0617%8 Feb →
nuke13–80.0813%8 Feb →
dust212–120.126%7 Feb →
nuke13–6-0.0110%7 Feb →
mirage13–11-0.0313%2 Feb →
nuke5–13-0.0814%2 Feb →
anubis13–70.0310%1 Feb →
nuke13–2-0.0315%1 Feb →
mirage6–13-0.0712%1 Feb →
ancient13–0-0.020%31 Jan →
inferno11–130.0315%31 Jan →
vertigo2–13-0.125%31 Jan →
ancient3–13-0.080%31 Jan →
inferno2–13-0.0411%31 Jan →
ancient13–40.0514%30 Jan →
nuke10–13-0.028%30 Jan →
dust21–13-0.0221%30 Jan →
mirage2–11-0.120%29 Jan →
inferno10–130.007%29 Jan →
mirage13–110.188%29 Jan →
inferno13–70.0418%29 Jan →
anubis6–13-0.037%29 Jan →
mirage13–80.0310%28 Jan →
inferno10–130.0126%28 Jan →
inferno9–130.115%28 Jan →
inferno12–120.0112%28 Jan →
mirage10–130.0117%27 Jan →
vertigo6–130.018%26 Jan →
dust212–12-0.067%26 Jan →
inferno8–13-0.055%25 Jan →
train13–70.079%25 Jan →
inferno13–10.1212%25 Jan →
inferno9–6-0.077%25 Jan →
overpass4–130.018%23 Jan →
dust213–10.0117%23 Jan →
mirage10–50.0317%23 Jan →
dust26–13-0.0316%23 Jan →
ancient12–12-0.0217%23 Jan →
dust213–11-0.0722%23 Jan →
inferno4–13-0.076%23 Jan →
mirage13–5-0.0317%22 Jan →
inferno10–13-0.066%22 Jan →
dust28–13-0.0410%22 Jan →
warden1–6-0.0619%22 Jan →
inferno9–30.0517%20 Jan →
anubis13–30.0822%4 Feb →
inferno3–9-0.2016%20 Jun →
inferno13–16-0.0315%19 Jun →

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 →

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