YoobeL

YoobeL — CS2 Stats

MT76561199132822979[U:1:1172557251]Steam profile ↗✓ No bans

1,071Tracked matches58%Win rate2021Tracked since
2,251Hours in CS10Hrs last 2 wks
CSDB Rating6.6 SolidPositional Player
Premier CS Rating14,533Blue band · top ~30.9% of ranked players (population est.)
WingmanLegendary Eagle Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 11 Nov 2026 (3 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: 14,533 +962 2 Aug – 11 Nov · 36 days played
11,65014,837peak 14,8372 Aug11 Nov
14,999Peak Premier in tracked matches
46Days played since 2026-07-28

Premier CS Rating

  • 304 below peak (14,837)
  • +1,892 over 30 days · improving
  • +2,855 over 90 days
  • Next: Purple band at 15,000 — 467 to go
  • Reached: Blue band · Light Blue band
  • Blue band first seen 2026-09-13
  • Light Blue band first seen 2026-09-13

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 Blue band among CSDB-tracked players (n=21,222), 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 playerBlue band medianPurple band medianvs Purple band
Headshot rate42.5%42.0%44.4%1.9% short
Shot accuracy8.6%9.6%11.9%3.3% short
Kill/death ratio1.220.981.03above
Match win rate39.5%43.8%45.2%5.7% short

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

Widest gap: Shot accuracy. That is the metric furthest from the Purple band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGYoobeLPREMIER14,533 · Blue bandcsdb.gg/stats

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Performance scores

Aim83
Positioning70
Utility36

0–100 skill scores via Leetify.

Recent form

STEADY47–46–7Last 10047%Win rateWWLLLLTLWW

Last 10 vs previous 10: 0pp win rate · −0.03 avg rating · −3.7pp headshot accuracy · −26ms 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 0.02
  • Avg headshot accuracy 16%
  • Avg reaction 545ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 14%
  • Avg reaction 556ms

Last 20

  • 8–8–4 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 16%
  • Avg reaction 569ms

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 (+2.2 against its own average).

Aim8.3
Utility3.6
Positioning7.0
Opening Duels5.8
Clutch3.0

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 88% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: lower aim profile; 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

Strengths

T openings. 62% T opening-duel success — entries that actually open the round.

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. 558ms 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

Aim8.3
Positioning7.0
Utility3.6
Mechanics6.5
Opening Duels7.4
Win Impact7.6

Composite 6.6/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.04+0.02
first ⅓ avg 0.02 → last ⅓ avg 0.04
Reaction time563ms−42ms
first ⅓ avg 605ms → last ⅓ avg 563ms
Headshot accuracy17.2%−6.4%
first ⅓ avg 23.7% → last ⅓ avg 17.2%

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

0.32Best match rating · 9–1 · nuke, 28 Jul →
47%Best headshot accuracy · 5–13 · ancient, 1 Oct →
406msFastest reaction time · 2–9 · inferno, 28 Jul →
13–0Biggest win · cache, 24 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
W2Current streak
7–9In matches decided by ≤2 rounds
8Overtime games

Map breakdown

nukeBest map · 64% over 14infernoWeakest map · 39% over 23
MapGradePlayedRecordWin rateAvg rating
mirageC2611–1542%0.02
infernoC239–1439%0.01
nukeA149–564%0.03
dust2A95–456%0.01
ancientA95–456%0.07
cacheC94–544%0.06
anubisC73–443%0.04
italy—10–10%0.09
overpass—11–0100%0.04
office—10–10%-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (39% over 23). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

86,114Lifetime kills
1.22K/D · Top 25% of Blue band
4,000Matches
39.5%Match win rate
42.5%Headshot % · Top 50% of Blue band
8.6%Shot accuracy
8,952MVPs
1,386Hours (in match)
1,597Bombs planted
640Bombs defused

Most-used weapons

AK-4724,006
Negev9,192
AWP7,875
SSG 081,696
Knife1,401
P2501,367

Lifetime map wins

2,571nuke
2,329inferno
1,926dust2
1,200vertigo
545train
416cbble
333office
177lake

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

Faceit stats

Combat

201Matches
50%Win rate
1.19Avg K/D
87.3ADR
48%Headshot %

Clutches & streaks

35%1v1 clutch win
26%1v2 clutch win
7Longest win streak

Recent Faceit resultsWLLLW

MapMatchesWin rateAvg K/DAvg kills
Mirage7858%1.2417.5
Ancient2854%1.1415.5
Dust22438%1.6117.6
Nuke2050%1.1318.0
Anubis1937%0.9615.6
Inferno1656%1.1618.8
Overpass520%1.0019.0
Vertigo3100%0.889.3

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.

17.1%Headshot accuracy
37.5%Accuracy (enemy spotted)
42.2%Spray accuracy
79.4%Counter-strafing
7.4°Preaim
558msReaction time
62.5%T opening success
56.8%CT opening success
0.41Enemies flashed / flash
6.0%Flash assists
9.72HE damage / grenade
4.91Flashes / 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 0.4116 — below the 0.5 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.

39% win rate across 23 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust213–40.0921%11 Nov →
ancient13–50.0619%11 Nov →
dust25–13-0.0216%11 Nov →
cache6–13-0.0511%9 Nov →
dust211–130.0315%9 Nov →
mirage5–13-0.046%31 Oct →
mirage15–150.0514%31 Oct →
nuke11–130.0419%31 Oct →
inferno13–10-0.024%31 Oct →
cache13–60.0619%31 Oct →
dust213–90.0922%31 Oct →
italy4–130.0914%31 Oct →
nuke3–13-0.0324%30 Oct →
anubis15–150.0316%30 Oct →
mirage15–15-0.0411%29 Oct →
inferno13–110.1026%29 Oct →
inferno13–50.0712%29 Oct →
anubis12–120.0219%26 Oct →
inferno9–130.0821%26 Oct →
overpass8–20.0414%24 Oct →
cache13–00.1214%24 Oct →
cache13–70.2018%24 Oct →
nuke6–9-0.0017%24 Oct →
anubis13–100.0926%23 Oct →
mirage11–130.0317%23 Oct →
anubis13–100.0320%23 Oct →
mirage13–80.0316%22 Oct →
ancient13–100.0918%22 Oct →
dust28–13-0.0917%16 Oct →
nuke13–50.0523%16 Oct →
cache11–130.0920%15 Oct →
nuke13–90.0522%15 Oct →
office11–13-0.0417%11 Oct →
nuke13–30.0121%11 Oct →
anubis13–100.0517%10 Oct →
mirage8–70.0922%10 Oct →
inferno11–130.0325%6 Oct →
ancient13–50.0116%6 Oct →
mirage12–120.0429%4 Oct →
inferno6–9-0.0721%3 Oct →
mirage11–130.0216%2 Oct →
ancient5–130.0847%1 Oct →
dust213–110.0629%30 Sept →
cache5–130.0823%30 Sept →
inferno12–160.0123%27 Sept →
cache10–130.0129%26 Sept →
ancient13–40.1442%26 Sept →
nuke1–13-0.0237%26 Sept →
dust26–13-0.0613%26 Sept →
inferno9–130.0027%26 Sept →
mirage13–70.0729%25 Sept →
inferno13–70.0822%25 Sept →
mirage16–130.0517%24 Sept →
mirage13–110.0213%24 Sept →
nuke13–90.0519%23 Sept →
inferno10–13-0.0621%18 Sept →
mirage9–130.0723%10 Sept →
mirage9–13-0.0421%7 Sept →
mirage13–7-0.0121%6 Sept →
inferno9–3-0.0314%6 Sept →
inferno8–80.1332%4 Sept →
cache5–130.0427%2 Sept →
nuke13–6-0.0613%1 Sept →
mirage6–2-0.0235%26 Aug →
inferno13–30.0344%26 Aug →
dust213–8-0.0121%23 Aug →
inferno13–90.0518%23 Aug →
mirage15–15-0.0216%20 Aug →
ancient2–13-0.0222%19 Aug →
inferno6–13-0.0619%19 Aug →
nuke13–90.0235%18 Aug →
mirage13–90.0223%18 Aug →
mirage8–13-0.0125%11 Aug →
mirage11–130.0134%11 Aug →
inferno6–13-0.0017%10 Aug →
mirage11–130.1221%10 Aug →
mirage10–13-0.0413%10 Aug →
anubis10–13-0.0124%8 Aug →
mirage7–13-0.0427%8 Aug →
nuke4–13-0.0233%7 Aug →
inferno5–130.0622%7 Aug →
ancient5–130.1019%6 Aug →
inferno13–70.0129%6 Aug →
mirage13–10-0.0118%6 Aug →
ancient5–130.1126%3 Aug →
nuke16–14-0.0118%3 Aug →
inferno6–13-0.0519%3 Aug →
nuke13–110.0934%2 Aug →
cache13–110.0429%2 Aug →
mirage10–130.0127%2 Aug →
mirage16–120.0524%1 Aug →
anubis9–130.0732%1 Aug →
ancient13–60.0317%1 Aug →
inferno3–130.0933%1 Aug →
mirage13–60.0520%31 Jul →
inferno13–60.1225%31 Jul →
dust213–7-0.0426%31 Jul →
nuke9–10.3246%28 Jul →
inferno1–9-0.267%28 Jul →
inferno2–9-0.100%28 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 →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.