BleibtQL

BleibtQL — CS2 Stats

76561199232071067[U:1:1271805339]Steam profile ↗✓ No bans

267Tracked matches47%Win rate2023Tracked since
104Hours in CS
CSDB Rating4.2 DevelopingSupport
Premier CS Rating12,612Blue band · top ~41.1% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 22 May 2026 (150 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: 12,612 -1,221 20 Nov – 22 May · 36 days played
12,43421,709peak 21,70920 Nov22 May
22,131Peak Premier in tracked matches
49Days played since 2025-11-20

Premier CS Rating

  • 9,097 below peak (21,709)
  • -4,858 over 30 days · declining
  • Next: Purple band at 15,000 — 2,388 to go
  • Reached: Pink band · 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 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 rate47.8%42.0%44.3%above
Shot accuracy0.0%9.6%11.9%11.9% short
Kill/death ratio1.030.981.03meets
Match win rate50.8%43.8%45.2%above

This profile matches the typical Purple band player on 3 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.GGBleibtQLPREMIER12,612 · Blue bandcsdb.gg/stats

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Performance scores

Aim51
Positioning47
Utility52

0–100 skill scores via Leetify.

Recent form

COLD47–50–3Last 10047%Win rateWLLLLLLWLW

Last 10 vs previous 10: −10pp win rate · −0.03 avg rating · −7.4pp headshot accuracy · −186ms reaction

Win rate −10pp 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

  • 1–4 · 20% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 7%
  • Avg reaction 216ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 10%
  • Avg reaction 297ms

Last 20

  • 7–13 · 35% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 13%
  • Avg reaction 390ms

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 (+0.9 against its own average).

Aim5.1
Utility5.2
Positioning4.7
Opening Duels3.0

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

jL

Plays most like jL 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. 570ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 68% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim5.1
Positioning4.7
Utility5.2
Mechanics4.0
Opening Duels2.2
Win Impact3.9

Composite 4.2/10 (Developing), 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 rating0.02+0.01
first ⅓ avg 0.01 → last ⅓ avg 0.02
Reaction time434ms−186ms
first ⅓ avg 620ms → last ⅓ avg 434ms
Headshot accuracy13.7%−2.8%
first ⅓ avg 16.5% → last ⅓ avg 13.7%

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

0.13Best match rating · 13–4 · inferno, 5 Dec →
60%Best headshot accuracy · 2–6 · dust2, 17 Apr →
391msFastest reaction time · 0–13 · ancient, 27 Mar →
13–2Biggest win · dust2, 26 Apr →

Across the last 100 tracked matches.

Highlights

6Longest win streak
4–4In matches decided by ≤2 rounds
7Overtime games

Map breakdown

infernoBest map · 67% over 27dust2Weakest map · 32% over 22
MapGradePlayedRecordWin rateAvg rating
infernoS2718–967%0.03
dust2D227–1532%0.01
ancientB2110–1148%-0.00
nukeC145–936%0.01
anubisD62–433%-0.02
overpass—42–250%0.01
mirage—31–233%-0.03
train—21–150%0.01
golden—11–0100%0.01

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (32% over 22). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

4,268Lifetime kills
1.03K/D · Top 50% of Blue band
295Matches
50.8%Match win rate · Top 10% of Blue band
47.8%Headshot % · Top 25% of Blue band
0.0%Shot accuracy
556MVPs
104Hours (in match)
281Bombs planted
55Bombs defused

Most-used weapons

Lifetime map wins

998dust2
664inferno
381nuke
80train
21vertigo
13italy

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.

17.0%Headshot accuracy
30.8%Accuracy (enemy spotted)
36.1%Spray accuracy
68.2%Counter-strafing
10.8°Preaim
570msReaction time
31.3%T opening success
46.0%CT opening success
0.62Enemies flashed / flash
7.4%Flash assists
7.70HE damage / grenade
4.94Flashes / 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 31.2952% — below the 40% mark we flag

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.

32% win rate across 22 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
anubis13–90.0118%22 May →
dust211–130.0219%22 May →
anubis0–13-0.000%22 May →
dust20–13-0.000%22 May →
inferno0–13-0.000%22 May →
ancient0–130.000%22 May →
dust20–13-0.120%22 May →
dust213–90.1020%10 May →
dust21–13-0.0222%7 May →
dust213–20.0218%26 Apr →
anubis0–13-0.0129%26 Apr →
ancient1–13-0.090%26 Apr →
dust26–13-0.039%24 Apr →
ancient13–80.0915%24 Apr →
dust213–60.1223%24 Apr →
inferno13–60.1122%21 Apr →
dust213–40.0713%21 Apr →
dust22–60.0360%17 Apr →
dust20–130.000%17 Apr →
dust20–130.000%17 Apr →
inferno10–130.0222%11 Apr →
nuke13–80.0920%11 Apr →
anubis14–16-0.065%10 Apr →
inferno13–70.0213%9 Apr →
overpass9–30.044%9 Apr →
inferno13–50.068%9 Apr →
inferno13–40.0718%8 Apr →
ancient13–50.0518%8 Apr →
overpass16–120.0616%4 Apr →
ancient8–130.0345%4 Apr →
dust20–130.000%4 Apr →
ancient0–130.000%4 Apr →
nuke13–70.0613%31 Mar →
nuke13–100.0216%31 Mar →
dust213–10-0.0020%29 Mar →
dust213–8-0.0315%27 Mar →
dust213–70.0322%27 Mar →
mirage0–130.000%27 Mar →
ancient0–130.000%27 Mar →
dust20–130.000%27 Mar →
ancient0–130.000%27 Mar →
dust20–130.000%27 Mar →
ancient0–13-0.100%27 Mar →
ancient0–13-0.000%27 Mar →
mirage13–10-0.0333%27 Mar →
inferno13–50.019%21 Mar →
inferno11–130.0621%21 Mar →
anubis5–13-0.0425%21 Mar →
inferno13–110.0734%20 Mar →
ancient13–7-0.0122%20 Mar →
inferno6–13-0.0620%15 Mar →
ancient15–150.0314%12 Mar →
nuke8–130.0114%8 Mar →
inferno10–13-0.059%2 Mar →
nuke4–13-0.0229%22 Feb →
dust215–15-0.0218%16 Feb →
ancient13–9-0.0119%13 Feb →
ancient13–5-0.0414%13 Feb →
anubis13–80.0113%6 Feb →
nuke13–6-0.0510%6 Feb →
dust26–130.0317%6 Feb →
inferno13–40.0216%2 Feb →
inferno13–11-0.026%23 Jan →
inferno13–70.1013%23 Jan →
inferno13–10-0.0628%16 Jan →
overpass6–13-0.0221%16 Jan →
inferno13–30.0720%16 Jan →
nuke10–130.0226%14 Jan →
ancient13–60.0416%13 Jan →
train15–15-0.0511%8 Jan →
golden13–70.0113%4 Jan →
inferno3–13-0.0327%4 Jan →
nuke8–13-0.0410%15 Dec →
inferno13–90.0225%9 Dec →
nuke16–140.0216%8 Dec →
nuke10–130.0222%8 Dec →
inferno13–40.0618%7 Dec →
inferno0–10-0.020%7 Dec →
inferno7–130.0036%6 Dec →
inferno13–40.1322%5 Dec →
inferno12–5-0.0115%5 Dec →
train13–110.0721%5 Dec →
nuke6–13-0.0110%1 Dec →
nuke9–130.0414%1 Dec →
ancient13–5-0.0317%30 Nov →
inferno10–130.0214%29 Nov →
nuke11–13-0.0211%29 Nov →
ancient13–100.0114%29 Nov →
inferno13–10-0.0219%28 Nov →
nuke5–13-0.0412%27 Nov →
inferno13–90.1233%26 Nov →
ancient13–10-0.0114%26 Nov →
ancient12–16-0.0515%24 Nov →
dust210–130.0114%24 Nov →
ancient13–60.0017%23 Nov →
dust28–13-0.0124%22 Nov →
ancient9–13-0.0111%21 Nov →
overpass2–13-0.0219%21 Nov →
inferno13–60.1211%21 Nov →
mirage0–9-0.050%20 Nov →

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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