xanaxenjoyer

xanaxenjoyer — CS2 Stats

IL76561199889150303[U:1:1928884575]Steam profile ↗✓ No bans

1,067Tracked matches66%Win rate2025Tracked since
CSDB Rating6.8 SolidPositional Player
Premier CS Rating13,410Blue band · top ~36.8% of ranked players (population est.)
FaceitLevel 10 · 1,443 ELOTop 12.4% of ranked FACEIT players
WingmanSilver Elite Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 21 Oct 2026 (7 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: 13,410 +11,064 30 May – 21 Oct · 26 days played
2,34613,410peak 13,41030 May21 Oct
Faceit ELO: 1,443 +0 18 Sept – 4 Oct · 2 observations
1,4431,443peak 1,44318 Sept4 Oct
13,410Peak Premier in tracked matches
1,443Highest Faceit ELO seen on CSDB
53Days played since 2026-05-30

Faceit ELO

  • At peak — 1,443
  • Next: Level 8 at 1,531 — 88 to go
  • Reached: Level 7 · Level 6 · Level 5 · Level 4
  • Level 7 first seen 2026-09-18
  • Level 6 first seen 2026-09-18

Premier CS Rating

  • At peak — 13,410
  • +1,949 over 30 days · improving
  • Next: Purple band at 15,000 — 1,590 to go
  • Reached: Blue band · Light Blue band
  • Blue band first seen 2026-09-18
  • 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. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

Share this profile

CSDB.GGxanaxenjoyerFACEITLevel 10 · 1,443 ELOSTANDINGTop 12.4% of rankedPREMIER13,410 · Blue bandPEAK ELO1,443csdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim90
Positioning65
Utility44

0–100 skill scores via Leetify.

Recent form

HOT62–36–2Last 10062%Win rateTWLWWWWWLW

Last 10 vs previous 10: +10pp win rate · −0.01 avg rating · −6.1pp headshot accuracy · +26ms 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

  • 3–1–1 · 60% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 20%
  • Avg reaction 484ms

Last 10

  • 7–2–1 · 70% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 18%
  • Avg reaction 527ms

Last 20

  • 13–6–1 · 65% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 21%
  • Avg reaction 513ms

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 (+1.3 against its own average).

Aim9.0
Utility4.4
Positioning6.5
Opening Duels6.2
Clutch3.8

Sharp aimer

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

donk

Plays most like donk 94% playstyle similarity

Most alike: aim profile, utility contribution.

Where you differ: lower opening-duel success; 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

Strengths

Aim. Aim score of 90 — the mechanical foundation is a clear strength.

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

Aim9.0
Positioning6.5
Utility4.4
Mechanics6.0
Opening Duels6.0
Win Impact10.0

Composite 6.8/10 (Solid), 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 rating0.05+0.04
first ⅓ avg 0.01 → last ⅓ avg 0.05
Reaction time486ms−55ms
first ⅓ avg 542ms → last ⅓ avg 486ms
Headshot accuracy23.2%+2.4%
first ⅓ avg 20.8% → last ⅓ avg 23.2%

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

0.21Best match rating · 13–7 · ancient, 30 Jun →
67%Best headshot accuracy · 9–1 · mirage, 16 Sept →
195msFastest reaction time · 2–3 · dust2, 24 Aug →
13–1Biggest win · ancient, 14 Oct →

Across the last 100 tracked matches.

Highlights

9Longest win streak
6–10In matches decided by ≤2 rounds
9Overtime games

Map breakdown

cacheBest map · 75% over 12ancientWeakest map · 47% over 17
MapGradePlayedRecordWin rateAvg rating
dust2A2818–1064%0.03
ancientB178–947%0.05
mirageB137–654%0.02
cacheS129–375%0.02
infernoS129–375%0.05
nukeA74–357%0.04
anubisS75–271%0.07
train—10–10%0.03
overpass—11–0100%0.08
vertigo—11–0100%-0.07
boulder—10–10%-0.10

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (47% over 17). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

566Matches
53%Win rate
1.03Avg K/D
76.0ADR
48%Headshot %

Clutches & streaks

39%1v1 clutch win
24%1v2 clutch win
9Longest win streak

Recent Faceit resultsWWWLL

MapMatchesWin rateAvg K/DAvg kills
Dust217763%1.0515.9
Mirage8445%0.9714.4
Ancient8041%0.9915.0
Inferno6349%1.0614.9
Anubis5857%1.0616.2
Nuke5751%0.9914.8
Overpass1937%0.8413.5
Cache1958%1.1516.7

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.

21.5%Headshot accuracy
39.3%Accuracy (enemy spotted)
41.0%Spray accuracy
77.2%Counter-strafing
7.7°Preaim
486msReaction time
53.4%T opening success
54.5%CT opening success
0.45Enemies flashed / flash
8.9%Flash assists
10.11HE damage / grenade
7.73Flashes / 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 0.4525 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Ancient

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

47% win rate across 17 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke15–150.0317%21 Oct →
dust213–110.0019%21 Oct →
mirage9–130.0718%21 Oct →
cache13–60.0611%20 Oct →
nuke13–20.1135%20 Oct →
ancient13–100.0922%20 Oct →
cache13–50.0513%20 Oct →
ancient13–110.0319%18 Oct →
cache11–13-0.037%16 Oct →
cache13–80.0416%14 Oct →
ancient13–6-0.0516%14 Oct →
mirage11–13-0.0622%14 Oct →
ancient13–10.1114%14 Oct →
mirage9–130.1715%6 Oct →
train7–130.0312%5 Oct →
mirage0–2-0.0250%5 Oct →
inferno13–9-0.0426%5 Oct →
dust213–10.1117%5 Oct →
inferno13–40.0715%4 Oct →
dust213–30.1851%3 Oct →
dust213–70.0838%3 Oct →
nuke13–11-0.0113%3 Oct →
ancient4–130.0217%2 Oct →
cache7–13-0.0754%2 Oct →
nuke2–130.1144%1 Oct →
dust213–70.0721%1 Oct →
mirage13–10.1219%30 Sept →
mirage8–130.0223%30 Sept →
anubis13–60.1814%30 Sept →
inferno13–100.1027%29 Sept →
dust25–13-0.0427%29 Sept →
inferno2–13-0.0036%29 Sept →
ancient12–140.0917%27 Sept →
ancient11–130.0318%27 Sept →
anubis13–20.1216%26 Sept →
cache13–90.0611%26 Sept →
ancient11–130.0614%24 Sept →
ancient16–130.0412%22 Sept →
ancient13–10.1814%22 Sept →
ancient12–160.0619%20 Sept →
dust213–80.0620%20 Sept →
mirage0–6-0.0433%20 Sept →
dust213–100.0930%19 Sept →
mirage13–40.0118%19 Sept →
anubis13–30.0423%16 Sept →
inferno13–110.0223%16 Sept →
mirage9–10.0167%16 Sept →
anubis16–190.0313%14 Sept →
dust211–13-0.0121%13 Sept →
cache13–100.0122%9 Sept →
inferno6–130.0231%8 Sept →
dust29–13-0.0125%8 Sept →
dust213–50.0328%8 Sept →
dust213–60.0832%7 Sept →
ancient11–130.0227%7 Sept →
anubis13–110.0736%7 Sept →
dust29–130.0025%7 Sept →
ancient13–20.0445%6 Sept →
dust213–90.0427%6 Sept →
mirage13–30.0216%6 Sept →
dust26–130.0024%6 Sept →
inferno16–130.0415%6 Sept →
ancient5–13-0.0413%5 Sept →
dust213–8-0.0216%5 Sept →
anubis13–30.0324%5 Sept →
dust213–70.0516%5 Sept →
inferno13–10.0724%5 Sept →
nuke13–100.0426%5 Sept →
cache13–10.1235%4 Sept →
inferno13–50.0216%3 Sept →
dust213–20.1414%1 Sept →
cache11–5-0.0019%26 Aug →
dust22–30.0762%24 Aug →
mirage13–50.0224%20 Aug →
mirage13–11-0.0238%16 Aug →
overpass13–20.0841%16 Aug →
dust213–5-0.0823%9 Aug →
dust213–70.0013%9 Aug →
vertigo13–7-0.0718%26 Jul →
dust213–90.0316%22 Jul →
dust210–13-0.0411%19 Jul →
boulder4–13-0.1021%18 Jul →
anubis15–150.0118%18 Jul →
dust213–6-0.0414%17 Jul →
mirage13–8-0.0813%16 Jul →
dust213–10-0.0117%12 Jul →
nuke10–13-0.0110%11 Jul →
cache14–160.0516%6 Jul →
nuke13–4-0.0218%5 Jul →
ancient7–130.0210%4 Jul →
ancient13–70.2122%30 Jun →
inferno9–30.2123%26 Jun →
ancient3–13-0.0322%26 Jun →
dust213–160.0519%26 Jun →
dust210–13-0.0111%25 Jun →
cache13–8-0.0420%22 Jun →
inferno9–00.0833%16 Jun →
inferno9–13-0.0516%15 Jun →
cache13–6-0.0521%15 Jun →
dust20–13-0.087%30 May →

Match data via Leetify.

Recent teammates

Milestones

Faceit Level 101,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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