JugglingLars

JugglingLars — CS2 Stats

76561198302421549[U:1:342155821]Steam profile ↗✓ No bans

495Tracked matches41%Win rate2023Tracked since
CSDB Rating4.3 DevelopingClutch Specialist
Ladder ranks via Leetify

Rating over time

10,712Peak Premier in tracked matches
34Days played since 2026-05-16

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

Performance scores

Aim49
Positioning59
Utility21

0–100 skill scores via Leetify.

Recent form

STEADY41–51–8Last 10041%Win rateWWWLLWWLLL

Last 10 vs previous 10: +20pp win rate · +0.00 avg rating · −0.9pp headshot accuracy · +40ms 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

  • 3–2 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 12%
  • Avg reaction 537ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 10%
  • Avg reaction 541ms

Last 20

  • 8–11–1 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 11%
  • Avg reaction 521ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+4.9 against its own average).

Aim4.9
Utility2.1
Positioning5.9
Opening Duels2.5
Clutch10.0

Limited utility dependenceReliable in 1v1s

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

ZywOo

Plays most like ZywOo 73% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower aim profile; lower opening-duel success.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

CSDB Rating breakdown

Aim4.9
Positioning5.9
Utility2.1
Mechanics5.7
Opening Duels3.0
Win Impact2.1

Composite 4.3/10 (Developing), 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 rating-0.01−0.01
first ⅓ avg -0.00 → last ⅓ avg -0.01
Reaction time532ms−91ms
first ⅓ avg 623ms → last ⅓ avg 532ms
Headshot accuracy11.6%−0.8%
first ⅓ avg 12.4% → last ⅓ avg 11.6%

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

0.15Best match rating · 13–0 · alpine, 11 Jun →
29%Best headshot accuracy · 6–13 · cache, 26 Aug →
422msFastest reaction time · 13–10 · office, 1 Oct →
13–0Biggest win · alpine, 11 Jun →

Across the last 100 tracked matches.

Highlights

5Longest win streak
W3Current streak
7–4In matches decided by ≤2 rounds
2Overtime games

Map breakdown

nukeBest map · 62% over 21infernoWeakest map · 22% over 9
MapGradePlayedRecordWin rateAvg rating
officeC238–1535%-0.01
nukeA2113–862%-0.00
vertigoD134–931%-0.01
cacheD113–827%-0.01
infernoD92–722%-0.02
mirageD82–625%-0.02
anubisB63–350%-0.01
ancient—32–167%-0.04
overpass—20–20%-0.05
dust2—22–0100%0.07
alpine—11–0100%0.15
train—11–0100%0.06

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (22% over 9). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1Matches
0%Win rate
1.00Avg K/D
90.1ADR
33%Headshot %

Clutches & streaks

100%1v1 clutch win
0%1v2 clutch win
0Longest win streak

Recent Faceit resultsLLLLL

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.

11.5%Headshot accuracy
30.0%Accuracy (enemy spotted)
35.1%Spray accuracy
75.7%Counter-strafing
11.5°Preaim
532msReaction time
41.8%T opening success
42.6%CT opening success
0.32Enemies flashed / flash
7.0%Flash assists
8.92HE damage / grenade
1.19Flashes / 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 11.5094% — below the 15% mark we flag

    Aim Training →
  2. 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 0.3216 — 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.

22% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
office13–110.0411%1 Oct →
nuke13–60.049%1 Oct →
office13–10-0.0114%1 Oct →
vertigo9–13-0.0513%28 Sept →
vertigo10–13-0.0111%28 Sept →
anubis13–4-0.045%16 Sept →
anubis13–110.009%16 Sept →
overpass8–13-0.0512%15 Sept →
office9–13-0.037%15 Sept →
nuke5–13-0.0212%15 Sept →
office7–13-0.055%14 Sept →
inferno7–13-0.0215%14 Sept →
cache13–100.0414%14 Sept →
inferno9–13-0.0411%10 Sept →
office13–8-0.0411%10 Sept →
inferno4–13-0.049%10 Sept →
mirage3–13-0.0211%10 Sept →
nuke13–100.0717%10 Sept →
nuke12–12-0.0411%10 Sept →
vertigo9–13-0.019%9 Sept →
cache13–110.0613%9 Sept →
nuke13–160.1014%9 Sept →
vertigo10–130.0017%3 Sept →
nuke13–11-0.004%3 Sept →
office13–80.0110%3 Sept →
office13–50.0511%2 Sept →
office11–13-0.0418%2 Sept →
office10–13-0.016%30 Aug →
overpass5–13-0.0613%30 Aug →
anubis9–130.0119%30 Aug →
ancient13–3-0.0212%30 Aug →
office13–11-0.029%26 Aug →
inferno2–9-0.1220%26 Aug →
cache13–5-0.0017%26 Aug →
cache6–130.0929%26 Aug →
nuke2–13-0.028%26 Aug →
nuke13–10-0.0211%23 Aug →
nuke13–5-0.019%23 Aug →
ancient13–6-0.028%23 Aug →
vertigo13–90.0212%23 Aug →
nuke13–8-0.039%23 Aug →
anubis8–13-0.0712%21 Aug →
office8–13-0.066%21 Aug →
nuke5–13-0.029%15 Aug →
mirage5–13-0.066%15 Aug →
inferno12–12-0.0010%15 Aug →
nuke13–4-0.0316%15 Aug →
mirage11–13-0.0213%10 Aug →
inferno13–50.017%9 Aug →
office12–12-0.034%9 Aug →
mirage13–60.017%9 Aug →
vertigo13–90.088%6 Aug →
mirage7–13-0.0610%6 Aug →
office5–13-0.1514%3 Aug →
office2–13-0.154%3 Aug →
vertigo13–5-0.0118%3 Aug →
vertigo7–13-0.0511%3 Aug →
vertigo3–13-0.0812%3 Aug →
anubis12–120.017%25 Jul →
office12–12-0.0116%19 Jul →
office8–130.0222%11 Jul →
nuke13–80.0111%6 Jul →
dust213–40.1419%6 Jul →
office13–40.068%6 Jul →
office7–130.0314%5 Jul →
inferno1–13-0.0420%5 Jul →
cache8–13-0.0828%5 Jul →
cache2–7-0.065%5 Jul →
nuke8–13-0.0221%2 Jul →
office13–60.0420%2 Jul →
nuke13–2-0.0314%2 Jul →
nuke8–13-0.0314%2 Jul →
inferno15–15-0.058%1 Jul →
cache9–13-0.007%1 Jul →
cache2–13-0.0417%1 Jul →
mirage12–120.0518%20 Jun →
vertigo3–13-0.0815%20 Jun →
nuke13–70.0221%20 Jun →
office7–130.076%20 Jun →
nuke13–11-0.0011%11 Jun →
inferno13–40.088%11 Jun →
alpine13–00.156%11 Jun →
train13–40.069%11 Jun →
cache7–13-0.026%11 Jun →
office4–13-0.0518%10 Jun →
nuke13–100.0110%10 Jun →
vertigo13–8-0.0012%10 Jun →
mirage2–13-0.039%10 Jun →
mirage13–9-0.0421%8 Jun →
nuke11–13-0.0711%8 Jun →
cache2–13-0.0411%3 Jun →
vertigo11–130.0310%3 Jun →
vertigo12–120.0315%3 Jun →
office1–130.0113%3 Jun →
anubis13–100.0320%1 Jun →
dust213–11-0.0013%31 May →
office3–80.0311%31 May →
cache4–13-0.0110%31 May →
nuke9–50.0812%25 May →
ancient9–13-0.089%16 May →

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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