Il0n4

Il0n4 — CS2 Stats

EE76561198963544774[U:1:1003279046]Steam profile ↗✓ No bans

855Tracked matches27%Win rate2021Tracked since
CSDB Rating1.9 LearningPositional Player
Premier CS Rating14,999Blue band · top ~28.4% of ranked players (population est.)
FaceitLevel 4Top 81.0% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGIl0n4FACEITLevel 4STANDINGTop 81.0% of rankedPREMIER14,999 · Blue bandcsdb.gg/stats

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Performance scores

Aim19
Positioning24
Utility12

0–100 skill scores via Leetify.

Recent form

COLD28–67–5Last 10028%Win rateLLLLLWLLLL

Last 10 vs previous 10: −20pp win rate · −0.00 avg rating · −3.0pp headshot accuracy · +51ms reaction

Win rate down 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

  • 0–5 · 0% win rate
  • Avg rating -0.09
  • Avg headshot accuracy 5%
  • Avg reaction 724ms

Last 10

  • 1–9 · 10% win rate
  • Avg rating -0.08
  • Avg headshot accuracy 7%
  • Avg reaction 707ms

Last 20

  • 4–16 · 20% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 8%
  • Avg reaction 682ms

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 (+1.2 against its own average).

Aim1.9
Utility1.2
Positioning2.4
Opening Duels0.0

Limited utility dependence

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 81% playstyle similarity

Most alike: positioning profile, utility contribution.

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. 686ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

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

Aim1.9
Positioning2.4
Utility1.2
Mechanics5.2
Opening Duels0.0
Win Impact0.0

Composite 1.9/10 (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-0.07+0.00
first ⅓ avg -0.08 → last ⅓ avg -0.07
Reaction time692ms−80ms
first ⅓ avg 772ms → last ⅓ avg 692ms
Headshot accuracy9.1%−1.2%
first ⅓ avg 10.3% → last ⅓ avg 9.1%

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

0.02Best match rating · 11–3 · inferno, 18 Sept →
33%Best headshot accuracy · 3–0 · mirage, 29 Sept →
414msFastest reaction time · 1–9 · mirage, 14 Sept →
13–4Biggest win · anubis, 5 Sept →

Across the last 100 tracked matches.

Highlights

3Longest win streak
L5Current streak
3–6In matches decided by ≤2 rounds

Map breakdown

mirageBest map · 45% over 20trainWeakest map · 0% over 6
MapGradePlayedRecordWin rateAvg rating
mirageB209–1145%-0.06
dust2D183–1517%-0.08
anubisD185–1328%-0.08
infernoD134–931%-0.07
ancientD82–625%-0.08
trainD60–60%-0.08
nukeD50–50%-0.10
vertigo—41–325%-0.08
cache—43–175%-0.04
overpass—30–30%-0.11
office—11–0100%-0.04

Across the last 100 tracked matches.

Faceit stats

Combat

4Matches
25%Win rate
0.46Avg K/D
—ADR
31%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
1Longest win streak

Recent Faceit resultsLLLLW

MapMatchesWin rateAvg K/DAvg kills
Inferno250%0.547.0
Mirage10%0.5310.0
Vertigo10%0.244.0

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.

8.2%Headshot accuracy
27.9%Accuracy (enemy spotted)
27.2%Spray accuracy
73.3%Counter-strafing
12.4°Preaim
686msReaction time
22.1%T opening success
19.6%CT opening success
0.20Enemies flashed / flash
0.0%Flash assists
8.64HE damage / grenade
0.64Flashes / 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. Advanced Mechanics

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 12.368° — above the 12° mark we flag

    Aim Training →
  2. 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 8.2021% — below the 15% mark we flag

    Aim Training →
  3. 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 0.2022 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Train

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

0% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
dust22–13-0.117%1 Oct →
inferno7–13-0.110%1 Oct →
dust22–13-0.070%1 Oct →
dust27–13-0.0910%1 Oct →
ancient2–13-0.086%29 Sept →
inferno13–10-0.034%29 Sept →
mirage5–13-0.066%29 Sept →
mirage4–13-0.084%29 Sept →
nuke5–13-0.0625%29 Sept →
dust22–13-0.078%29 Sept →
mirage0–13-0.035%29 Sept →
mirage3–00.0133%29 Sept →
anubis5–13-0.105%29 Sept →
ancient10–13-0.133%27 Sept →
anubis13–6-0.073%27 Sept →
vertigo13–7-0.078%26 Sept →
dust28–13-0.119%26 Sept →
ancient2–13-0.095%26 Sept →
inferno11–13-0.0520%26 Sept →
vertigo2–13-0.089%26 Sept →
dust213–11-0.058%18 Sept →
anubis9–13-0.094%18 Sept →
mirage2–3-0.045%18 Sept →
inferno11–30.0213%18 Sept →
mirage13–9-0.0710%17 Sept →
ancient0–13-0.104%17 Sept →
anubis3–13-0.1010%17 Sept →
anubis6–13-0.127%17 Sept →
anubis10–13-0.0516%17 Sept →
anubis5–13-0.1115%17 Sept →
inferno11–13-0.075%14 Sept →
mirage1–9-0.1118%14 Sept →
anubis4–13-0.0717%13 Sept →
dust211–13-0.083%13 Sept →
mirage4–13-0.079%13 Sept →
anubis5–13-0.0710%13 Sept →
overpass2–13-0.120%12 Sept →
mirage13–8-0.136%12 Sept →
inferno3–13-0.0317%12 Sept →
nuke6–13-0.129%12 Sept →
vertigo4–13-0.1011%12 Sept →
dust213–9-0.0012%12 Sept →
anubis8–13-0.1013%12 Sept →
dust28–13-0.125%12 Sept →
overpass4–13-0.0919%12 Sept →
office10–6-0.0413%12 Sept →
cache13–9-0.1017%12 Sept →
mirage13–10-0.0810%5 Sept →
nuke4–13-0.1313%5 Sept →
anubis13–4-0.0211%5 Sept →
dust20–2-0.060%5 Sept →
anubis4–13-0.0810%5 Sept →
ancient13–4-0.086%5 Sept →
dust212–12-0.073%4 Sept →
inferno8–13-0.1016%4 Sept →
anubis13–6-0.1010%4 Sept →
inferno13–11-0.045%29 Aug →
anubis13–90.0010%29 Aug →
mirage0–13-0.079%29 Aug →
cache12–12-0.0513%29 Aug →
dust23–13-0.0825%27 Aug →
cache13–40.0017%27 Aug →
mirage13–4-0.075%27 Aug →
ancient12–12-0.079%27 Aug →
anubis9–13-0.0710%19 Aug →
inferno13–7-0.129%19 Aug →
ancient13–70.0016%19 Aug →
mirage12–12-0.068%19 Aug →
train11–13-0.0810%19 Aug →
inferno9–13-0.0810%14 Aug →
train5–13-0.106%14 Aug →
nuke4–13-0.144%14 Aug →
dust24–13-0.088%14 Aug →
anubis7–13-0.1014%14 Aug →
dust25–13-0.039%14 Aug →
inferno11–13-0.0614%14 Aug →
mirage13–40.0016%14 Aug →
mirage13–8-0.0516%14 Aug →
dust29–13-0.1112%14 Aug →
ancient2–13-0.063%14 Aug →
train10–13-0.099%14 Aug →
cache13–6-0.032%13 Aug →
train9–13-0.058%13 Aug →
train8–13-0.104%12 Aug →
overpass4–13-0.1317%12 Aug →
mirage13–10-0.0611%12 Aug →
inferno3–13-0.0815%12 Aug →
dust213–10-0.0615%11 Aug →
mirage2–13-0.0713%11 Aug →
nuke7–13-0.0514%9 Aug →
inferno4–13-0.1014%9 Aug →
dust21–13-0.055%9 Aug →
mirage1–13-0.105%9 Aug →
mirage2–13-0.0712%9 Aug →
anubis2–13-0.1014%9 Aug →
mirage12–12-0.089%9 Aug →
train9–13-0.0716%8 Aug →
vertigo6–13-0.0912%8 Aug →
dust28–13-0.118%8 Aug →
anubis13–9-0.088%8 Aug →

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 →

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