Jxgu.

Jxgu. — CS2 Stats

FI76561198835143332[U:1:874877604]Steam profile ↗✓ No bans

591Tracked matches37%Win rate2023Tracked since
1,228Hours in CS6Hrs last 2 wks
CSDB Rating3.1 LearningPositional Player
Premier CS Rating14,323Blue band · top ~32% of ranked players (population est.)
WingmanMaster Guardian Elite
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 15 Sep 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.

Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 30 days played since 25 Jul 2026. Come back after the next session and the change shows above.

Is this you? Sign in with Steam to claim it and connect match tracking →

Rating over time

Premier CS Rating: 14,323 +2,051 26 Jul15 Sept · 17 days played
12,08715,461peak 15,46126 Jul15 Sept
15,712Peak Premier in tracked matches
30Days played since 2026-07-25

Premier CS Rating

  • 1,138 below peak (15,461)
  • -677 over 30 days · declining
  • Next: Purple band at 15,000 677 to go
  • Reached: 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=19,543), 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 rate37.7%41.9%44.3%6.7% short
Shot accuracy8.3%9.6%11.8%3.6% short
Kill/death ratio0.930.981.030.10 short
Match win rate40.6%43.8%45.2%4.6% short

This profile sits below the typical Purple band player on every metric we can compare.

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.GGJxgu.PREMIER14,323 · Blue bandcsdb.gg/stats

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Performance scores

Aim33
Positioning52
Utility48

0–100 skill scores via Leetify.

Recent form

COLD39565Last 10039%Win rateTWLLLLLLWW

Last 10 vs previous 10: 0pp win rate · −0.01 avg rating · −5.2pp headshot accuracy · −28ms 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

  • 131 · 20% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 15%
  • Avg reaction 635ms

Last 10

  • 361 · 30% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 17%
  • Avg reaction 585ms

Last 20

  • 6122 · 30% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 20%
  • Avg reaction 599ms

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 PlayerPositioning stands above the rest of this profile (+2.1 against its own average).

Aim3.3
Utility4.8
Positioning5.2
Opening Duels2.5
Clutch0.0

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 64% 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. 588ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 53% 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

Aim3.3
Positioning5.2
Utility4.8
Mechanics0.7
Opening Duels2.9
Win Impact0.7

Composite 3.1/10 (Learning), 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 rating-0.03+0.00
first ⅓ avg -0.03 → last ⅓ avg -0.03
Reaction time584ms−39ms
first ⅓ avg 622ms → last ⅓ avg 584ms
Headshot accuracy17.2%+1.9%
first ⅓ avg 15.3% → 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

0.19Best match rating · 9–1 · inferno, 25 Jul
42%Best headshot accuracy · 8–13 · mirage, 20 Aug
422msFastest reaction time · 9–13 · nuke, 16 Aug
13–1Biggest win · mirage, 2 Sept

Across the last 100 tracked matches.

Highlights

8Longest win streak
911In matches decided by ≤2 rounds
6Overtime games

Map breakdown

nukeBest map · 69% over 16infernoWeakest map · 21% over 28
MapGradePlayedRecordWin rateAvg rating
infernoD2862221%-0.04
nukeS1611569%-0.01
anubisC125742%-0.01
cacheD124833%-0.03
mirageC94544%-0.03
dust2D92722%-0.01
ancientS96367%-0.01
vertigo41325%-0.03
train1010%-0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (21% over 28). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

38,766Lifetime kills
0.93K/D
2,448Matches
40.6%Match win rate
37.7%Headshot %
8.3%Shot accuracy
4,956MVPs
695Hours (in match)
1,705Bombs planted
413Bombs defused

Most-used weapons

Lifetime map wins

3,118nuke
3,077inferno
1,140vertigo
1,066dust2
592train
331lake
204cbble
157office

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

Faceit stats

Combat

26Matches
58%Win rate
0.91Avg K/D
75.8ADR
40%Headshot %

Clutches & streaks

17%1v1 clutch win
12%1v2 clutch win
12Longest win streak

Recent Faceit resultsWLWWL

MapMatchesWin rateAvg K/DAvg kills
Dust2667%1.0815.2
Inferno580%0.9511.2
Nuke4100%1.0812.3
Mirage30%0.6810.7
Anubis250%0.6910.5
Ancient250%0.8810.5
Train1100%0.9314.0
Cache10%0.8416.0

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.

17.6%Headshot accuracy
28.9%Accuracy (enemy spotted)
32.5%Spray accuracy
53.0%Counter-strafing
10.6°Preaim
588msReaction time
40.5%T opening success
42.4%CT opening success
0.40Enemies flashed / flash
3.8%Flash assists
5.35HE damage / grenade
11.73Flashes / 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 0.401 — 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.

21% win rate across 28 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
nuke12–12-0.0619%17 Sept
anubis13–2-0.0313%16 Sept
inferno4–13-0.0921%15 Sept
cache7–13-0.0711%13 Sept
inferno11–13-0.0613%13 Sept
anubis5–130.0323%11 Sept
mirage11–130.0013%11 Sept
dust28–13-0.0123%7 Sept
anubis13–8-0.0416%6 Sept
mirage13–1-0.0518%2 Sept
inferno12–12-0.0529%1 Sept
dust213–9-0.0619%31 Aug
cache10–13-0.0115%30 Aug
anubis8–130.0017%30 Aug
cache11–13-0.0017%26 Aug
anubis7–13-0.0619%26 Aug
ancient8–6-0.0618%25 Aug
mirage8–13-0.0542%20 Aug
inferno7–13-0.0426%17 Aug
nuke13–100.0520%17 Aug
ancient13–50.0334%17 Aug
nuke9–13-0.0416%16 Aug
cache13–5-0.009%16 Aug
cache13–50.0113%16 Aug
anubis2–13-0.065%16 Aug
ancient13–7-0.009%16 Aug
cache8–130.002%13 Aug
inferno12–12-0.036%13 Aug
cache9–13-0.0419%12 Aug
dust22–13-0.0423%12 Aug
inferno9–13-0.0416%12 Aug
inferno7–9-0.0718%12 Aug
inferno11–13-0.057%11 Aug
nuke13–90.0225%11 Aug
nuke13–4-0.0225%11 Aug
ancient13–100.0116%11 Aug
inferno13–110.0117%11 Aug
nuke16–140.0412%10 Aug
mirage13–60.0119%10 Aug
anubis13–11-0.0815%10 Aug
inferno9–4-0.1716%10 Aug
inferno7–130.0110%9 Aug
ancient16–13-0.0314%9 Aug
dust22–13-0.0318%7 Aug
nuke13–4-0.047%7 Aug
nuke9–13-0.0315%7 Aug
mirage13–9-0.0510%7 Aug
inferno13–11-0.069%6 Aug
inferno13–50.0723%6 Aug
nuke13–8-0.0211%6 Aug
cache9–13-0.0419%6 Aug
nuke13–110.1120%6 Aug
mirage3–13-0.0619%5 Aug
anubis13–110.026%4 Aug
inferno11–130.0322%4 Aug
mirage13–50.0918%4 Aug
dust215–15-0.0015%4 Aug
inferno8–130.0216%4 Aug
nuke5–9-0.124%4 Aug
dust213–110.0416%4 Aug
nuke16–13-0.0118%3 Aug
anubis10–130.0110%3 Aug
cache13–10-0.0514%3 Aug
ancient6–13-0.0119%3 Aug
nuke13–11-0.028%3 Aug
nuke10–10.0417%3 Aug
cache8–13-0.0214%3 Aug
cache8–13-0.0612%30 Jul
inferno7–9-0.0019%30 Jul
inferno2–9-0.1216%30 Jul
mirage1–13-0.1122%30 Jul
anubis11–13-0.017%30 Jul
vertigo2–130.004%30 Jul
dust21–130.0218%30 Jul
ancient4–13-0.0619%30 Jul
vertigo13–30.0824%30 Jul
train5–13-0.0510%30 Jul
inferno0–9-0.1717%27 Jul
inferno2–9-0.1110%27 Jul
dust212–120.0412%27 Jul
dust214–16-0.076%27 Jul
vertigo6–9-0.089%27 Jul
inferno6–90.0623%27 Jul
inferno3–9-0.0912%27 Jul
mirage11–13-0.102%27 Jul
vertigo4–9-0.1320%26 Jul
nuke3–9-0.1018%26 Jul
inferno6–9-0.0721%26 Jul
anubis7–130.017%26 Jul
inferno5–90.0019%26 Jul
inferno4–13-0.0410%26 Jul
ancient11–130.0312%26 Jul
cache13–9-0.0414%26 Jul
inferno13–16-0.0715%26 Jul
nuke13–10.1124%26 Jul
ancient13–60.0117%26 Jul
inferno9–40.0033%26 Jul
inferno6–9-0.1415%26 Jul
anubis13–20.0518%26 Jul
inferno9–10.1922%25 Jul

Match data via Leetify.

Recent teammates

Milestones

500 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →