Eating My Zinger Burger

Eating My Zinger Burger — CS2 Stats

76561198006151822[U:1:45886094]Steam profile ↗✓ No bans

1,169Tracked matches33%Win rate2023Tracked since
CSDB Rating5.6 SolidPositional Player
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 11 Sep 2026 (35 days ago). Ranks are recorded once per day this page is viewed.

+17Tracked matches · now 1,169
−11.5ppWin rate · 44.8% → 33.3%

Rating over time

Premier CS Rating: 11,088 -2,536 25 Mar – 24 Jun · 9 days played
10,72714,010peak 14,01025 Mar24 Jun
14,010Peak Premier in tracked matches
33Days played since 2026-03-24

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

Performance scores

Aim79
Positioning59
Utility28

0–100 skill scores via Leetify.

Recent form

STEADY37–60–3Last 10037%Win rateLLLWWWLLWL

Last 10 vs previous 10: 0pp win rate · +0.03 avg rating · +0.0pp headshot accuracy · +24ms 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

  • 2–3 · 40% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 17%
  • Avg reaction 539ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 20%
  • Avg reaction 606ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 20%
  • Avg reaction 594ms

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 (+1.5 against its own average).

Aim7.9
Utility2.8
Positioning5.9
Opening Duels4.5

Limited 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

s1mple

Plays most like s1mple 88% playstyle similarity

Most alike: aim profile, positioning profile.

Where you differ: lower opening-duel success; 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.

Reaction time. 597ms 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

Aim7.9
Positioning5.9
Utility2.8
Mechanics7.3
Opening Duels5.4
Win Impact0.0

Composite 5.6/10 (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 rating0.02+0.00
first ⅓ avg 0.02 → last ⅓ avg 0.02
Reaction time599ms−16ms
first ⅓ avg 616ms → last ⅓ avg 599ms
Headshot accuracy17.6%+2.4%
first ⅓ avg 15.2% → last ⅓ avg 17.6%

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

0.21Best match rating · 13–1 · dust2, 7 Oct →
31%Best headshot accuracy · 8–13 · inferno, 24 Jun →
438msFastest reaction time · 13–8 · inferno, 26 Jun →
13–1Biggest win · dust2, 7 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L3Current streak
2–7In matches decided by ≤2 rounds
2Overtime games

Map breakdown

trainBest map · 71% over 7dust2Weakest map · 17% over 12
MapGradePlayedRecordWin rateAvg rating
cacheC146–843%0.02
infernoD143–1121%-0.01
nukeB137–654%0.02
dust2D122–1017%0.00
vertigoC83–538%0.02
ancientD82–625%0.04
trainS75–271%0.05
mirageD62–433%-0.00
overpassB63–350%0.02
anubis—40–40%0.00
fachwerk—21–150%0.01
stronghold—22–0100%0.07
boulder—10–10%0.02
shelter—10–10%-0.02
italy—11–0100%0.13
warden—10–10%-0.03

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (17% over 12). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Skill profile

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

18.3%Headshot accuracy
38.6%Accuracy (enemy spotted)
40.2%Spray accuracy
82.8%Counter-strafing
9.6°Preaim
597msReaction time
52.4%T opening success
50.4%CT opening success
0.42Enemies flashed / flash
4.1%Flash assists
10.56HE damage / grenade
2.89Flashes / 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 0.4202 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Dust 2

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

17% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
vertigo5–130.0325%7 Oct →
cache9–130.0113%7 Oct →
mirage6–13-0.0211%7 Oct →
dust213–10.2117%7 Oct →
train13–9-0.0216%1 Oct →
cache13–80.0120%1 Oct →
dust25–13-0.0625%30 Sept →
cache10–130.0320%30 Sept →
train13–50.2030%28 Sept →
cache7–13-0.0518%28 Sept →
vertigo5–13-0.0830%28 Sept →
dust213–160.0214%23 Sept →
vertigo7–130.0428%23 Sept →
cache8–13-0.0625%11 Sept →
vertigo13–80.0619%11 Sept →
overpass10–130.0319%11 Sept →
train13–70.0212%11 Sept →
inferno13–110.0222%6 Sept →
vertigo13–100.0113%13 Aug →
cache7–13-0.0515%5 Aug →
anubis5–130.0414%5 Aug →
ancient13–40.1014%5 Aug →
inferno0–13-0.0111%5 Aug →
inferno6–13-0.0314%31 Jul →
train4–13-0.0627%31 Jul →
ancient13–90.0110%25 Jul →
anubis5–130.0214%25 Jul →
ancient8–130.0813%22 Jul →
cache5–130.0417%22 Jul →
fachwerk7–130.0925%16 Jul →
dust22–13-0.044%16 Jul →
nuke6–13-0.0212%16 Jul →
train13–30.0814%16 Jul →
overpass13–11-0.0520%16 Jul →
cache13–6-0.0413%16 Jul →
mirage13–50.0312%15 Jul →
nuke13–5-0.0318%15 Jul →
cache7–130.0724%10 Jul →
nuke7–0-0.050%10 Jul →
mirage3–13-0.029%10 Jul →
boulder4–130.0217%10 Jul →
fachwerk13–5-0.079%10 Jul →
shelter9–13-0.0212%10 Jul →
inferno13–80.0017%26 Jun →
vertigo12–120.0414%26 Jun →
overpass16–120.0414%24 Jun →
inferno8–13-0.0531%24 Jun →
cache13–80.1019%10 Jun →
inferno13–40.0915%7 Jun →
mirage10–13-0.0513%7 Jun →
dust211–13-0.0525%7 Jun →
inferno10–13-0.0510%7 Jun →
nuke7–13-0.0117%7 Jun →
cache13–80.0312%7 Jun →
inferno2–13-0.0518%7 Jun →
vertigo10–130.0815%5 Jun →
cache13–50.0525%5 Jun →
dust212–12-0.0018%5 Jun →
nuke12–120.0427%5 Jun →
ancient11–130.0821%3 Jun →
nuke4–130.0023%3 Jun →
stronghold13–70.1130%16 May →
train13–10.0619%16 May →
cache10–130.0619%16 May →
inferno10–13-0.0220%16 May →
nuke2–130.0320%29 Apr →
cache13–70.0812%29 Apr →
overpass1–13-0.0014%29 Apr →
overpass11–130.0314%28 Apr →
inferno6–130.0228%28 Apr →
nuke11–130.1419%28 Apr →
nuke13–30.1220%25 Apr →
ancient8–130.024%25 Apr →
stronghold13–100.0228%25 Apr →
overpass13–70.0611%25 Apr →
anubis5–13-0.0713%25 Apr →
train11–130.0414%25 Apr →
inferno8–13-0.0325%25 Apr →
dust26–130.0816%19 Apr →
anubis10–130.024%16 Apr →
ancient6–13-0.0213%16 Apr →
dust211–13-0.019%16 Apr →
nuke13–6-0.0215%9 Apr →
inferno7–130.0114%9 Apr →
vertigo13–50.0111%9 Apr →
dust24–13-0.017%9 Apr →
nuke13–30.0617%8 Apr →
inferno10–130.0426%8 Apr →
dust22–13-0.0521%8 Apr →
mirage6–13-0.047%8 Apr →
nuke13–70.0013%30 Mar →
italy13–40.1313%30 Mar →
mirage13–80.0918%30 Mar →
dust22–13-0.058%30 Mar →
ancient10–13-0.0115%26 Mar →
warden11–13-0.0317%26 Mar →
dust213–70.0023%26 Mar →
nuke13–30.0010%25 Mar →
inferno9–13-0.0424%25 Mar →
ancient6–130.0212%24 Mar →

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 →

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