FUCKED UP!!

FUCKED UP!! — CS2 Stats

SE76561199472486216[U:1:1512220488]Steam profile ↗✓ No bans

643Tracked matches62%Win rate2025Tracked since
688Hours in CS34Hrs last 2 wks
CSDB Rating6.7 SolidClutch Specialist
Premier CS Rating16,566Purple band · top ~22.2% of ranked players (population est.)
WingmanMaster Guardian II
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 19 Sep 2026 (yesterday). 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. 35 days played since 20 Jun 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: 16,566 +1,091 4 Jul19 Sept · 3 days played
15,47516,566peak 16,5664 Jul19 Sept
16,566Peak Premier in tracked matches
35Days played since 2026-06-20

Premier CS Rating

  • At peak — 16,566
  • +32 over 30 days · steady
  • +1,091 over 90 days
  • Next: Pink band at 20,000 3,434 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 Purple band among CSDB-tracked players (n=36,319), 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 playerPurple band medianPink band medianvs Pink band
Headshot rate52.7%44.3%46.9%above
Shot accuracy1.0%11.8%13.0%12.0% short
Kill/death ratio1.381.031.08above
Match win rate55.9%45.2%46.7%above

This profile matches the typical Pink band player on 3 of 4 comparable metrics.

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

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CSDB.GGFUCKED UP!!PREMIER16,566 · Purple bandcsdb.gg/stats

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Performance scores

Aim84
Positioning57
Utility53

0–100 skill scores via Leetify.

Recent form

STEADY59329Last 10059%Win rateWLTLWWLWLW

Last 10 vs previous 10: 0pp win rate · −0.01 avg rating · −5.5pp headshot accuracy · +14ms 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

  • 221 · 40% win rate
  • Avg rating 0.06
  • Avg headshot accuracy 23%
  • Avg reaction 536ms

Last 10

  • 541 · 50% win rate
  • Avg rating 0.08
  • Avg headshot accuracy 22%
  • Avg reaction 538ms

Last 20

  • 1073 · 50% win rate
  • Avg rating 0.09
  • Avg headshot accuracy 25%
  • Avg reaction 531ms

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 SpecialistLate-round 1vX conversion stands above the rest of this profile (+3.3 against its own average).

Aim8.4
Utility5.3
Positioning5.7
Opening Duels4.2
Clutch9.4

Effective flashesLimited 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

jL

Plays most like jL 97% playstyle similarity

Most alike: aim profile, opening-duel success.

Where you differ: lower utility contribution; lower positioning 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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

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

Aim8.4
Positioning5.7
Utility5.3
Mechanics5.9
Opening Duels4.4
Win Impact8.8

Composite 6.7/10 (Solid), 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 rating0.09+0.05
first ⅓ avg 0.05 → last ⅓ avg 0.09
Reaction time526ms−38ms
first ⅓ avg 564ms → last ⅓ avg 526ms
Headshot accuracy24.3%−4.3%
first ⅓ avg 28.6% → last ⅓ avg 24.3%

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

0.30Best match rating · 13–1 · nuke, 31 Aug
71%Best headshot accuracy · 10–0 · dust2, 6 Jul
375msFastest reaction time · 10–2 · overpass, 1 Sept
13–0Biggest win · inferno, 16 Sept

Across the last 100 tracked matches.

Highlights

8Longest win streak
45In matches decided by ≤2 rounds
2Overtime games

Map breakdown

cacheBest map · 72% over 25infernoWeakest map · 29% over 17
MapGradePlayedRecordWin rateAvg rating
cacheS2518772%0.09
infernoD1751229%0.04
nukeS1711665%0.09
anubisA85363%0.02
mirageS75271%0.10
dust2S75271%0.09
italy41325%0.10
train42250%0.10
office43175%0.06
ancient31233%0.09
vertigo21150%0.13
overpass110100%0.00
poseidon110100%-0.09

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 17). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

16,608Lifetime kills
1.38K/D · Top 10% of Purple band
991Matches
55.9%Match win rate · Top 5% of Purple band
52.7%Headshot % · Top 25% of Purple band
1.0%Shot accuracy
4,592MVPs
278Hours (in match)
559Bombs planted
180Bombs defused

Most-used weapons

Lifetime map wins

2,304inferno
1,012dust2
939nuke
370vertigo
200office
151train
74italy
33lake

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

Faceit stats

Combat

3Matches
33%Win rate
1.37Avg K/D
100.2ADR
57%Headshot %

Clutches & streaks

67%1v1 clutch win
0%1v2 clutch win
1Longest win streak

Recent Faceit resultsLLWLL

MapMatchesWin rateAvg K/DAvg kills
Ancient10%1.3121.0
Inferno10%0.508.0
Mirage1100%2.3130.0

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.

24.3%Headshot accuracy
36.3%Accuracy (enemy spotted)
34.4%Spray accuracy
76.6%Counter-strafing
8.0°Preaim
522msReaction time
43.9%T opening success
51.2%CT opening success
0.74Enemies flashed / flash
8.9%Flash assists
13.98HE damage / grenade
3.13Flashes / 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

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 3.1319 — below the 4 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.

29% win rate across 17 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
anubis13–9-0.0315%19 Sept
italy5–130.0846%18 Sept
ancient12–120.1428%18 Sept
cache10–13-0.0213%17 Sept
train13–110.1312%16 Sept
inferno13–00.1812%16 Sept
office7–13-0.0312%16 Sept
cache13–50.0125%14 Sept
italy7–130.1425%12 Sept
mirage13–30.2536%11 Sept
nuke13–30.1532%11 Sept
anubis12–12-0.0014%9 Sept
cache8–130.1026%9 Sept
cache13–60.1316%9 Sept
inferno10–13-0.0117%8 Sept
inferno11–130.1235%7 Sept
inferno12–120.1131%6 Sept
inferno13–40.2236%4 Sept
office13–40.0833%3 Sept
cache13–30.0639%3 Sept
train9–130.0822%1 Sept
dust213–50.1633%1 Sept
vertigo13–60.1018%1 Sept
overpass10–20.008%1 Sept
nuke13–10.3019%31 Aug
vertigo10–130.1619%31 Aug
nuke12–120.0632%31 Aug
ancient11–130.0224%31 Aug
cache13–100.0231%30 Aug
inferno6–9-0.0119%30 Aug
cache13–80.1124%30 Aug
cache13–60.1023%30 Aug
cache13–90.1630%30 Aug
ancient13–100.1026%28 Aug
nuke13–50.2832%28 Aug
nuke13–80.1250%24 Aug
anubis13–100.0532%24 Aug
cache9–130.1122%24 Aug
mirage12–120.2124%19 Aug
mirage13–60.1018%18 Aug
anubis9–130.0217%18 Aug
nuke3–10-0.0218%18 Aug
dust213–30.0624%18 Aug
dust28–130.0431%18 Aug
nuke13–90.0224%18 Aug
anubis13–40.0414%18 Aug
mirage6–13-0.0717%18 Aug
cache13–100.2228%18 Aug
mirage12–40.0632%18 Aug
nuke13–110.0515%14 Aug
office13–90.0922%14 Aug
italy12–120.1129%14 Aug
nuke4–70.2336%14 Aug
inferno10–130.1227%14 Aug
cache11–130.0623%14 Aug
train7–130.0327%13 Aug
anubis13–90.0723%13 Aug
cache4–130.1019%13 Aug
anubis6–13-0.0336%6 Aug
inferno5–90.0750%4 Aug
dust216–13-0.0224%4 Aug
nuke13–60.0433%4 Aug
mirage13–30.1424%4 Aug
inferno13–30.1726%4 Aug
inferno11–130.0452%4 Aug
inferno13–90.0431%4 Aug
dust213–70.2330%2 Aug
nuke5–13-0.0325%2 Aug
mirage13–50.0344%19 Jul
nuke8–8-0.0925%19 Jul
nuke9–10.1736%19 Jul
poseidon9–2-0.0915%19 Jul
nuke9–30.2116%19 Jul
nuke9–40.0544%19 Jul
dust25–13-0.0920%18 Jul
inferno6–9-0.0137%18 Jul
cache13–90.0528%18 Jul
inferno6–9-0.1110%18 Jul
cache13–110.0628%12 Jul
inferno4–9-0.0616%11 Jul
inferno7–9-0.0031%11 Jul
cache13–60.1332%11 Jul
dust210–00.2671%6 Jul
anubis13–20.0736%6 Jul
nuke13–20.0840%6 Jul
office13–70.1032%6 Jul
italy12–20.0760%6 Jul
cache13–80.0334%6 Jul
cache13–30.0628%6 Jul
nuke5–13-0.0424%4 Jul
inferno16–140.0338%4 Jul
cache13–90.0621%2 Jul
cache13–60.2020%1 Jul
cache12–120.0424%1 Jul
cache13–100.0925%1 Jul
cache0–13-0.140%1 Jul
cache13–40.2432%30 Jun
cache13–100.1420%30 Jun
inferno8–8-0.137%20 Jun
train13–80.1522%20 Jun

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 →