Xuskie

Xuskie — CS2 Stats

76561198058458233[U:1:98192505]Steam profile ↗✓ No bans

1,134Tracked matches59%Win rate2022Tracked since
CSDB Rating7.5 StrongPositional Player
Premier CS Rating23,006Top 25% of 213,399 CSDB-tracked playersPink band · top ~5.2% of ranked players (population est.)
CSDB Leaderboard#43600 of 260004 tracked
FaceitLevel 10 · 1,786 ELOTop 12.4% of ranked FACEIT players
WingmanMaster Guardian I
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 2 Nov 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.

Rating over time

Premier CS Rating: 23,006 +421 7 Oct – 2 Nov · 9 days played
22,31823,859peak 23,8597 Oct2 Nov
Faceit ELO: 1,786 +0 29 Aug – 2 Sept · 2 observations
1,7861,786peak 1,78629 Aug2 Sept
23,897Peak Premier in tracked matches
1,786Highest Faceit ELO seen on CSDB
24Days played since 2026-08-29

Faceit ELO

  • At peak — 1,786
  • Next: Level 10 at 2,001 — 215 to go
  • Reached: Level 9 · Level 8 · Level 7 · Level 6
  • Level 9 first seen 2026-08-29
  • Level 8 first seen 2026-08-29

Premier CS Rating

  • 853 below peak (23,859)
  • +421 over 30 days · improving
  • Next: Red band at 25,000 — 1,994 to go
  • Reached: Pink band · 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. 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.GGXuskieFACEITLevel 10 · 1,786 ELOSTANDINGTop 12.4% of rankedPREMIER23,006 · Pink bandPEAK ELO1,786csdb.gg/stats

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Performance scores

Aim85
Positioning89
Utility27

0–100 skill scores via Leetify.

Recent form

STEADY50–44–6Last 10050%Win rateLLLWWTWWWL

Last 10 vs previous 10: −10pp win rate · +0.03 avg rating · −0.5pp 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

  • 2–3 · 40% win rate
  • Avg rating 0.13
  • Avg headshot accuracy 27%
  • Avg reaction 522ms

Last 10

  • 5–4–1 · 50% win rate
  • Avg rating 0.09
  • Avg headshot accuracy 22%
  • Avg reaction 507ms

Last 20

  • 11–8–1 · 55% win rate
  • Avg rating 0.07
  • Avg headshot accuracy 23%
  • Avg reaction 520ms

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 (+3 against its own average).

Aim8.5
Utility2.7
Positioning8.9
Opening Duels8.6
Clutch3.4

Sharp aimerLimited utility dependenceStrong positioning

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

s1mple

Plays most like s1mple 63% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: lower utility contribution.

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 85 — the mechanical foundation is a clear strength.

CT openings. 61% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

T openings. 67% T opening-duel success — entries that actually open the round.

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

Aim8.5
Positioning8.9
Utility2.7
Mechanics6.3
Opening Duels8.5
Win Impact8.1

Composite 7.5/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.06+0.02
first ⅓ avg 0.04 → last ⅓ avg 0.06
Reaction time496ms−34ms
first ⅓ avg 530ms → last ⅓ avg 496ms
Headshot accuracy23.1%+2.4%
first ⅓ avg 20.7% → last ⅓ avg 23.1%

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

0.27Best match rating · 13–3 · mirage, 4 Nov →
42%Best headshot accuracy · 13–5 · cache, 16 Oct →
328msFastest reaction time · 13–1 · mirage, 26 Oct →
13–1Biggest win · mirage, 26 Oct →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L3Current streak
6–5In matches decided by ≤2 rounds
2Overtime games

Map breakdown

infernoBest map · 89% over 9ancientWeakest map · 38% over 13
MapGradePlayedRecordWin rateAvg rating
mirageB2813–1546%0.04
dust2C2511–1444%0.05
ancientC135–838%0.03
infernoS98–189%0.08
nukeC83–538%0.05
cacheB63–350%0.03
anubisS64–267%0.05
train—42–250%0.09
overpass—11–0100%0.06

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (38% over 13). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

126Matches
66%Win rate
1.43Avg K/D
97.2ADR
46%Headshot %

Clutches & streaks

37%1v1 clutch win
28%1v2 clutch win
7Longest win streak

Recent Faceit resultsWWLWW

MapMatchesWin rateAvg K/DAvg kills
Mirage4168%1.5620.5
Ancient1765%1.4821.7
Dust21362%1.3118.3
Nuke1250%1.1119.4
Inferno1173%1.7318.3
Overpass875%1.4019.8
Anubis367%1.1517.7
Train2100%1.3016.0

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.

22.5%Headshot accuracy
35.6%Accuracy (enemy spotted)
39.6%Spray accuracy
78.5%Counter-strafing
8.7°Preaim
500msReaction time
66.9%T opening success
61.3%CT opening success
0.41Enemies flashed / flash
8.3%Flash assists
8.52HE damage / grenade
2.22Flashes / 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 0.4145 — 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.

38% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient3–13-0.0218%5 Nov →
dust28–130.1124%5 Nov →
ancient9–130.0828%5 Nov →
train13–90.2034%5 Nov →
mirage13–30.2733%4 Nov →
dust212–120.0922%4 Nov →
mirage13–110.1015%4 Nov →
cache13–80.0524%4 Nov →
dust213–50.0113%4 Nov →
ancient5–130.0113%3 Nov →
inferno13–40.2216%3 Nov →
dust210–130.0926%3 Nov →
mirage2–4-0.0925%3 Nov →
dust213–80.0531%3 Nov →
inferno13–100.0617%2 Nov →
cache11–130.0319%2 Nov →
anubis13–50.0531%2 Nov →
nuke13–70.0413%1 Nov →
dust210–13-0.0125%1 Nov →
inferno13–30.1025%1 Nov →
ancient8–13-0.0517%31 Oct →
dust213–110.0820%31 Oct →
mirage12–120.1227%31 Oct →
ancient12–120.0226%31 Oct →
nuke13–4-0.0518%31 Oct →
dust211–130.0323%30 Oct →
ancient13–100.0825%28 Oct →
anubis7–10.1136%28 Oct →
mirage2–130.0318%28 Oct →
inferno13–90.1621%28 Oct →
nuke3–13-0.0029%28 Oct →
dust26–130.0222%28 Oct →
mirage13–10.1430%26 Oct →
mirage12–120.0325%26 Oct →
dust28–30.0113%26 Oct →
mirage5–130.0417%24 Oct →
anubis13–100.0216%24 Oct →
nuke5–130.1214%24 Oct →
mirage13–70.0112%24 Oct →
ancient13–16-0.0211%21 Oct →
dust211–13-0.0038%21 Oct →
mirage5–13-0.0318%21 Oct →
ancient7–130.0313%21 Oct →
mirage13–110.1019%21 Oct →
dust212–120.0819%20 Oct →
ancient13–110.1515%20 Oct →
train10–130.0914%20 Oct →
anubis7–130.0224%20 Oct →
mirage9–130.0818%20 Oct →
dust213–80.0418%20 Oct →
inferno13–50.0320%18 Oct →
cache6–130.0520%17 Oct →
inferno13–30.1018%17 Oct →
anubis8–130.0426%17 Oct →
mirage13–70.0820%16 Oct →
cache13–50.0142%16 Oct →
dust211–13-0.0121%16 Oct →
inferno13–110.0519%15 Oct →
nuke3–130.0813%15 Oct →
mirage12–120.0514%15 Oct →
mirage2–13-0.0625%12 Oct →
dust213–40.0818%12 Oct →
inferno7–13-0.0021%12 Oct →
dust28–130.0631%11 Oct →
dust213–100.0214%11 Oct →
mirage13–7-0.0526%11 Oct →
mirage13–20.0618%11 Oct →
ancient13–80.0114%11 Oct →
dust210–130.0025%11 Oct →
anubis13–100.0621%11 Oct →
mirage2–13-0.0020%11 Oct →
train13–110.0724%11 Oct →
cache13–70.0327%11 Oct →
inferno13–60.0122%10 Oct →
ancient16–130.0325%10 Oct →
dust210–130.0415%10 Oct →
mirage13–90.0015%10 Oct →
ancient8–130.0723%10 Oct →
mirage13–70.1023%10 Oct →
mirage7–13-0.0716%9 Oct →
mirage10–130.0320%9 Oct →
mirage10–13-0.0116%8 Oct →
mirage4–90.0421%8 Oct →
dust25–13-0.0515%8 Oct →
cache9–130.0125%8 Oct →
mirage13–40.0815%7 Oct →
train2–130.0132%7 Oct →
dust213–90.0923%7 Oct →
nuke9–130.0724%7 Oct →
nuke8–130.0922%7 Oct →
dust213–90.0922%7 Oct →
dust213–80.0415%6 Oct →
overpass13–80.0617%6 Oct →
dust29–130.1325%6 Oct →
mirage13–50.0721%6 Oct →
mirage2–13-0.0123%6 Oct →
dust213–90.1225%5 Oct →
ancient13–60.0415%5 Oct →
mirage13–30.1318%5 Oct →
nuke13–100.0522%5 Oct →

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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