Just A Bush

Just A Bush — CS2 Stats

76561199082538650[U:1:1122272922]Steam profile ↗✓ No bans

403Tracked matches50%Win rate2023Tracked since
CSDB Rating4.4 DevelopingPositional Player
Premier CS Rating5,534Light Blue band · top ~76.2% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 18 Sep 2026 (29 days ago). Ranks are recorded once per day this page is viewed.

0Premier CS Rating · 5,534 → 5,534
+3Tracked matches · now 403
−3.6ppWin rate · 53.6% → 50.0%

Rating over time

Premier CS Rating: 5,534 +0 1 May – 18 Sept · 2 days played
5,5345,534peak 5,5341 May18 Sept
5,534Peak Premier in tracked matches
23Days played since 2026-04-28

Premier CS Rating

  • At peak — 5,534
  • Next: Blue band at 10,000 — 4,466 to go
  • Reached: Light Blue band
  • Light Blue band first seen 2026-09-18

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

Share this profile

CSDB.GGJust A BushPREMIER5,534 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim54
Positioning53
Utility29

0–100 skill scores via Leetify.

Recent form

STEADY54–40–6Last 10054%Win rateLWWLTWLWLW

Last 10 vs previous 10: +20pp win rate · +0.00 avg rating · +0.8pp headshot accuracy · +68ms reaction

Win rate up 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

  • 2–2–1 · 40% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 16%
  • Avg reaction 667ms

Last 10

  • 5–4–1 · 50% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 15%
  • Avg reaction 733ms

Last 20

  • 8–10–2 · 40% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 15%
  • Avg reaction 699ms

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 (+1.6 against its own average).

Aim5.4
Utility2.9
Positioning5.3
Opening Duels2.9

Strong T-side openerLimited 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 88% 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

Areas to improve

CT openings. Opening success drops from 47% on T to 30% on CT — first contacts on the defending side are being lost.

Reaction time. 696ms 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

Aim5.4
Positioning5.3
Utility2.9
Mechanics6.7
Opening Duels2.2
Win Impact5.0

Composite 4.4/10 (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 rating-0.03−0.04
first ⅓ avg 0.01 → last ⅓ avg -0.03
Reaction time706ms−46ms
first ⅓ avg 752ms → last ⅓ avg 706ms
Headshot accuracy15.0%+2.5%
first ⅓ avg 12.5% → last ⅓ avg 15.0%

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

0.14Best match rating · 13–8 · cache, 4 May →
38%Best headshot accuracy · 2–13 · cache, 5 Sept →
547msFastest reaction time · 8–13 · train, 4 Sept →
13–1Biggest win · train, 12 Oct →

Across the last 100 tracked matches.

Highlights

6Longest win streak
3–3In matches decided by ≤2 rounds

Map breakdown

ancientBest map · 75% over 8trainWeakest map · 43% over 7
MapGradePlayedRecordWin rateAvg rating
dust2A1810–856%-0.02
cacheB178–947%-0.00
nukeS1510–567%-0.02
infernoB115–645%-0.04
mirageA117–464%-0.00
ancientS86–275%0.00
trainC73–443%-0.02
anubisB63–350%-0.02
vertigo—42–250%-0.03
overpass—20–20%-0.08
office—10–10%-0.13

Across the last 100 tracked matches.

Skill profile

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

15.0%Headshot accuracy
33.6%Accuracy (enemy spotted)
33.6%Spray accuracy
80.0%Counter-strafing
9.1°Preaim
696msReaction time
47.4%T opening success
30.4%CT opening success
0.35Enemies flashed / flash
0.9%Flash assists
12.47HE damage / grenade
1.59Flashes / 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 0.3513 — below the 0.5 mark we flag

    Grenade Lineups →
  2. Advanced Mechanics

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 30.3753% — below the 40% mark we flag

Spend your practice time on Train

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

43% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
dust25–13-0.0611%12 Oct →
nuke13–10-0.0217%12 Oct →
train13–10.0222%12 Oct →
inferno1–9-0.1215%13 Sept →
inferno12–12-0.0414%9 Sept →
cache13–70.0317%9 Sept →
dust22–13-0.1020%9 Sept →
nuke13–5-0.0312%9 Sept →
dust28–13-0.048%7 Sept →
mirage13–8-0.0217%7 Sept →
anubis8–13-0.0219%7 Sept →
cache0–13-0.065%7 Sept →
dust213–10-0.1214%7 Sept →
inferno13–60.056%7 Sept →
nuke10–13-0.0611%5 Sept →
ancient8–130.004%5 Sept →
cache2–13-0.0738%5 Sept →
anubis8–13-0.009%5 Sept →
dust212–12-0.0721%4 Sept →
mirage13–4-0.0518%4 Sept →
train8–13-0.109%4 Sept →
inferno13–8-0.036%4 Sept →
overpass3–13-0.096%4 Sept →
vertigo13–100.0117%4 Sept →
dust28–13-0.0524%2 Sept →
mirage13–30.0418%2 Sept →
inferno13–60.0119%1 Sept →
ancient13–90.0417%31 Aug →
dust213–50.0024%31 Aug →
nuke9–13-0.0416%31 Aug →
nuke3–13-0.0816%7 Jun →
mirage13–10-0.0513%7 Jun →
ancient13–7-0.0312%26 May →
inferno5–9-0.1614%26 May →
dust213–10-0.0614%25 May →
cache13–30.0320%25 May →
dust211–130.0611%19 May →
train9–13-0.119%10 May →
dust213–8-0.0317%10 May →
mirage13–110.0019%9 May →
nuke13–100.0013%9 May →
cache12–120.0117%9 May →
dust28–13-0.0627%9 May →
nuke13–110.0217%7 May →
dust213–80.0620%7 May →
nuke3–9-0.2317%5 May →
inferno9–20.053%5 May →
inferno3–9-0.1416%5 May →
cache9–13-0.0117%5 May →
dust213–80.0311%5 May →
cache13–80.1417%4 May →
train11–13-0.067%4 May →
nuke13–100.028%4 May →
anubis13–8-0.0114%4 May →
overpass9–13-0.079%4 May →
mirage4–13-0.095%4 May →
anubis7–13-0.036%4 May →
dust29–13-0.0511%4 May →
vertigo4–13-0.063%3 May →
dust213–110.0315%3 May →
cache12–12-0.099%3 May →
mirage6–130.028%3 May →
office5–13-0.1319%3 May →
nuke13–40.0312%3 May →
cache13–6-0.053%3 May →
ancient13–6-0.0412%3 May →
cache13–8-0.053%3 May →
train13–50.018%3 May →
inferno13–60.0010%3 May →
mirage4–13-0.0421%3 May →
ancient13–60.059%3 May →
anubis13–10-0.0018%3 May →
nuke13–90.0613%3 May →
vertigo7–130.0123%3 May →
dust213–4-0.069%3 May →
cache10–13-0.0012%3 May →
nuke9–6-0.030%3 May →
nuke9–5-0.0423%3 May →
inferno6–130.0122%2 May →
ancient13–90.016%2 May →
nuke7–130.0211%2 May →
dust213–50.035%2 May →
mirage13–60.067%2 May →
anubis13–7-0.0211%2 May →
cache13–7-0.0211%2 May →
vertigo13–9-0.0710%2 May →
inferno7–13-0.015%2 May →
ancient13–70.0511%2 May →
train12–120.0319%2 May →
cache12–12-0.038%2 May →
dust213–60.0717%2 May →
nuke13–100.0316%1 May →
mirage13–70.0212%1 May →
mirage10–130.0416%1 May →
cache13–40.0013%1 May →
cache13–30.0318%1 May →
cache8–130.0413%1 May →
ancient11–13-0.0815%30 Apr →
cache3–130.059%30 Apr →
train13–50.0412%28 Apr →

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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