BEEG YOSHI ⫍ ⃢ ⫎

BEEG YOSHI ⫍ ⃢ ⫎ — CS2 Stats

76561198088825590[U:1:128559862]Steam profile ↗✓ No bans

1,067Tracked matches40%Win rate2020Tracked since
6,838Hours in CS11Hrs last 2 wks
CSDB Rating4.5 DevelopingPositional Player
Premier CS Rating3,893Grey band · top ~83.5% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 27 Oct 2026 (4 days ago). Ranks are recorded once per day this page is viewed.

−650Premier CS Rating · 4,543 → 3,893

Rating over time

Premier CS Rating: 3,893 -3,415 25 Jul – 31 Oct · 56 days played
3,6887,308peak 7,30825 Jul31 Oct
7,947Peak Premier in tracked matches
55Days played since 2026-07-25

Premier CS Rating

  • 3,415 below peak (7,308)
  • -990 over 30 days · declining
  • -2,497 over 90 days
  • Next: Light Blue band at 5,000 — 1,107 to go
  • Reached: Light Blue band

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

MetricLast 30Previous 30Change
Matches34——
Win rate50%——
K/D1.15——
Headshot %39%——

Measured 4 Oct 2026 → 31 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 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 rate37.9%38.2%39.9%2.0% short
Shot accuracy14.9%3.6%7.0%above
Kill/death ratio0.860.830.920.06 short
Match win rate45.1%40.2%42.3%above

This profile matches the typical Light Blue band player on 2 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.GGBEEG YOSHI ⫍ ⃢ ⫎PREMIER3,893 · Grey bandcsdb.gg/stats

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Performance scores

Aim49
Positioning65
Utility29

0–100 skill scores via Leetify.

Recent form

COLD43–56–1Last 10043%Win rateLLLWWLLLWL

Last 10 vs previous 10: −20pp win rate · −0.02 avg rating · +1.1pp headshot accuracy · +51ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 2–3 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 15%
  • Avg reaction 794ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 14%
  • Avg reaction 722ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 14%
  • Avg reaction 697ms

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 (+2.1 against its own average).

Aim4.9
Utility2.9
Positioning6.5
Opening Duels3.7

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

donk

Plays most like donk 73% playstyle similarity

Most alike: positioning profile, utility contribution.

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

Strengths

T openings. 66% T opening-duel success — entries that actually open the round.

Areas to improve

CT openings. Opening success drops from 66% on T to 47% on CT — first contacts on the defending side are being lost.

Reaction time. 681ms 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

Aim4.9
Positioning6.5
Utility2.9
Mechanics6.3
Opening Duels6.6
Win Impact1.7

Composite 4.5/10 (Developing), 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 rating0.02−0.01
first ⅓ avg 0.03 → last ⅓ avg 0.02
Reaction time673ms−49ms
first ⅓ avg 722ms → last ⅓ avg 673ms
Headshot accuracy14.5%+0.1%
first ⅓ avg 14.4% → last ⅓ avg 14.5%

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

0.27Best match rating · 13–3 · cache, 1 Sept →
29%Best headshot accuracy · 1–13 · dust2, 30 Sept →
438msFastest reaction time · 5–13 · mirage, 1 Oct →
13–3Biggest win · mirage, 12 Oct →

Across the last 100 tracked matches.

Highlights

7Longest win streak
L3Current streak
6–12In matches decided by ≤2 rounds
13Overtime games

Map breakdown

anubisBest map · 60% over 5infernoWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
mirageB3014–1647%0.02
dust2D217–1433%0.02
nukeB157–847%0.00
cacheB136–746%0.04
ancientC94–544%0.03
infernoD72–529%0.01
anubisA53–260%0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

87,148Lifetime kills
0.86K/D · Top 50% of Grey band
4,698Matches
45.1%Match win rate · Top 25% of Grey band
37.9%Headshot %
14.9%Shot accuracy · Top 10% of Grey band
10,074MVPs
2,176Hours (in match)
5,011Bombs planted
1,047Bombs defused

Most-used weapons

AK-4730,998
AWP10,580
Negev6,943
AUG2,219
SG 5532,029
P2501,465

Lifetime map wins

11,005dust2
3,599inferno
3,227nuke
883train
265vertigo
173office
104lake
35assault

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.

14.1%Headshot accuracy
32.3%Accuracy (enemy spotted)
38.3%Spray accuracy
78.4%Counter-strafing
10.6°Preaim
681msReaction time
66.1%T opening success
46.7%CT opening success
0.52Enemies flashed / flash
2.5%Flash assists
1.35HE damage / grenade
4.00Flashes / 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 14.1305% — below the 15% mark we flag

    Aim Training →
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.

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage11–13-0.0213%31 Oct →
cache9–130.0317%31 Oct →
mirage6–130.0522%27 Oct →
cache13–9-0.0112%22 Oct →
nuke13–40.0711%22 Oct →
dust211–13-0.022%22 Oct →
dust28–130.0120%21 Oct →
ancient8–13-0.0115%20 Oct →
mirage13–40.0219%20 Oct →
mirage9–130.0611%18 Oct →
mirage13–100.0118%17 Oct →
anubis13–90.116%17 Oct →
nuke8–130.0112%16 Oct →
dust26–130.0114%16 Oct →
mirage11–130.0013%15 Oct →
inferno13–110.0620%12 Oct →
mirage13–30.057%12 Oct →
anubis5–130.048%11 Oct →
dust213–110.0820%11 Oct →
ancient12–16-0.0015%7 Oct →
ancient8–130.0112%5 Oct →
dust213–80.0922%5 Oct →
anubis13–100.1217%5 Oct →
mirage11–13-0.1021%3 Oct →
inferno7–130.0120%3 Oct →
nuke13–9-0.0013%3 Oct →
nuke11–13-0.029%2 Oct →
anubis5–13-0.048%1 Oct →
mirage5–130.0315%1 Oct →
inferno13–80.0711%1 Oct →
dust21–13-0.0629%30 Sept →
cache13–40.0416%28 Sept →
cache9–130.0612%28 Sept →
dust24–130.0310%28 Sept →
cache13–6-0.0318%28 Sept →
mirage6–13-0.0313%27 Sept →
ancient9–130.1117%27 Sept →
cache13–16-0.0518%25 Sept →
nuke5–13-0.0112%25 Sept →
nuke5–13-0.130%23 Sept →
ancient13–10-0.0110%23 Sept →
nuke13–90.019%22 Sept →
mirage13–7-0.0015%22 Sept →
nuke13–100.017%21 Sept →
mirage13–50.0514%21 Sept →
anubis16–13-0.105%20 Sept →
dust214–16-0.0412%18 Sept →
dust211–13-0.0711%18 Sept →
cache16–140.079%17 Sept →
mirage16–130.0124%17 Sept →
mirage13–90.049%16 Sept →
mirage13–30.0912%16 Sept →
mirage13–70.0220%16 Sept →
dust213–110.0819%15 Sept →
dust213–90.0510%14 Sept →
dust28–13-0.068%13 Sept →
cache9–13-0.0220%13 Sept →
nuke9–13-0.0515%12 Sept →
mirage15–15-0.0118%12 Sept →
dust213–9-0.0910%10 Sept →
dust213–160.0413%8 Sept →
mirage7–13-0.0015%8 Sept →
mirage9–130.0213%6 Sept →
ancient1–13-0.0616%5 Sept →
mirage13–5-0.0010%5 Sept →
nuke13–11-0.0115%2 Sept →
cache13–30.2728%1 Sept →
cache13–90.0810%1 Sept →
dust216–140.0811%30 Aug →
dust23–13-0.0617%29 Aug →
dust25–130.038%29 Aug →
inferno8–13-0.0311%20 Aug →
cache10–130.0024%19 Aug →
nuke6–130.0219%19 Aug →
nuke13–40.116%15 Aug →
mirage13–30.1114%14 Aug →
inferno3–130.019%14 Aug →
mirage10–130.0216%12 Aug →
mirage7–13-0.019%12 Aug →
cache14–160.0211%12 Aug →
nuke13–4-0.0314%6 Aug →
dust211–130.0316%6 Aug →
mirage0–70.0519%5 Aug →
mirage13–100.0914%5 Aug →
mirage11–13-0.0218%4 Aug →
ancient13–60.159%4 Aug →
inferno14–160.0027%3 Aug →
dust29–130.0818%2 Aug →
mirage13–16-0.0118%1 Aug →
mirage16–130.0017%31 Jul →
dust213–60.1419%31 Jul →
ancient9–50.0413%29 Jul →
mirage13–10-0.0217%27 Jul →
nuke11–130.0414%27 Jul →
inferno5–13-0.0510%27 Jul →
cache8–13-0.0110%26 Jul →
mirage3–130.0010%26 Jul →
nuke10–13-0.0019%25 Jul →
dust29–130.0817%25 Jul →
ancient13–70.077%25 Jul →

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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