Egho1m

Egho1m — CS2 Stats

DK76561199047343628[U:1:1087077900]Steam profile ↗✓ No bans

590Tracked matches53%Win rate2022Tracked since
CSDB Rating4.6 DevelopingAll-Rounder
Premier CS Rating16,788Purple band · top ~21.3% of ranked players (population est.)
FaceitLevel 7 · 1,298 ELOTop 42.3% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 26 Sep 2026 (31 days ago). Ranks are recorded once per day this page is viewed.

0Premier CS Rating · 16,788 → 16,788
0Faceit ELO · 1,298 → 1,298
+1Tracked matches · now 590
0.0ppWin rate · 53.3% → 53.3%

Rating over time

Premier CS Rating: 16,788 +353 20 Mar – 26 Sept · 28 days played
16,12518,451peak 18,45120 Mar26 Sept
Faceit ELO: 1,298 +0 18 Sept – 26 Sept · 2 observations
1,2981,298peak 1,29818 Sept26 Sept
18,451Peak Premier in tracked matches
1,298Highest Faceit ELO seen on CSDB
40Days played since 2026-03-16

Faceit ELO

  • At peak — 1,298
  • Next: Level 7 at 1,351 — 53 to go
  • Reached: Level 6 · Level 5 · Level 4 · Level 3
  • Level 6 first seen 2026-09-18
  • Level 5 first seen 2026-09-18

Premier CS Rating

  • 1,663 below peak (18,451)
  • +253 over 90 days
  • Next: Pink band at 20,000 — 3,212 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-09-18
  • 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.GGEgho1mFACEITLevel 7 · 1,298 ELOSTANDINGTop 42.3% of rankedPREMIER16,788 · Purple bandPEAK ELO1,298csdb.gg/stats

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Performance scores

Aim48
Positioning49
Utility48

0–100 skill scores via Leetify.

Recent form

STEADY46–51–3Last 10046%Win rateLLWLLWWWWL

Last 10 vs previous 10: −20pp win rate · −0.00 avg rating · +0.9pp headshot accuracy · +62ms 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

  • 1–4 · 20% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 9%
  • Avg reaction 651ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 12%
  • Avg reaction 634ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 12%
  • Avg reaction 603ms

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: All-Rounder — No style dimension stands clear of the others in this profile.

Aim4.8
Utility4.8
Positioning4.9
Opening Duels3.2
Clutch4.0

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

ZywOo

Plays most like ZywOo 78% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: lower utility contribution; 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. 580ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% 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

Aim4.8
Positioning4.9
Utility4.8
Mechanics4.2
Opening Duels2.7
Win Impact6.1

Composite 4.6/10 (Developing), 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 rating-0.00+0.01
first ⅓ avg -0.01 → last ⅓ avg -0.00
Reaction time590ms−26ms
first ⅓ avg 616ms → last ⅓ avg 590ms
Headshot accuracy11.9%+2.6%
first ⅓ avg 9.2% → last ⅓ avg 11.9%

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

0.14Best match rating · 13–5 · nuke, 4 Jul →
28%Best headshot accuracy · 3–13 · anubis, 14 Jul →
438msFastest reaction time · 13–11 · ancient, 13 Jul →
13–3Biggest win · dust2, 27 Jul →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L2Current streak
10–8In matches decided by ≤2 rounds
8Overtime games

Map breakdown

dust2Best map · 63% over 19overpassWeakest map · 14% over 7
MapGradePlayedRecordWin rateAvg rating
dust2A1912–763%0.00
ancientC156–940%-0.01
infernoC146–843%0.01
nukeA148–657%0.03
cacheB115–645%-0.01
mirageC104–640%-0.02
anubisB84–450%-0.02
overpassD71–614%-0.02
office—20–20%-0.02

Across the last 100 tracked matches.

Overpass is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Overpass lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

464Matches
50%Win rate
1.09Avg K/D
76.8ADR
37%Headshot %

Clutches & streaks

40%1v1 clutch win
21%1v2 clutch win
9Longest win streak

Recent Faceit resultsWWLLW

MapMatchesWin rateAvg K/DAvg kills
Ancient8648%1.0915.2
Dust28049%1.1414.5
Inferno7939%1.0616.0
Nuke7755%1.1116.4
Mirage6349%0.9714.0
Overpass3762%1.2715.3
Train2560%1.0916.1
Anubis1759%0.8913.7

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.

11.8%Headshot accuracy
33.1%Accuracy (enemy spotted)
34.7%Spray accuracy
69.1%Counter-strafing
10.4°Preaim
580msReaction time
37.1%T opening success
44.9%CT opening success
0.53Enemies flashed / flash
3.3%Flash assists
8.92HE damage / grenade
9.70Flashes / 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. 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 11.7897% — below the 15% mark we flag

    Aim Training →
  2. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 37.0525% — below the 40% mark we flag

Spend your practice time on Overpass

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

14% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Overpass callouts & strategy →Overpass grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage8–13-0.0710%27 Jul →
cache7–13-0.096%27 Jul →
dust213–9-0.028%27 Jul →
mirage0–13-0.018%27 Jul →
inferno4–130.0514%27 Jul →
cache13–70.0711%27 Jul →
dust213–30.0716%27 Jul →
nuke13–70.0116%21 Jul →
inferno13–110.0210%21 Jul →
ancient9–130.0322%21 Jul →
nuke13–90.028%18 Jul →
nuke11–130.0211%18 Jul →
mirage4–13-0.072%16 Jul →
dust213–90.0619%16 Jul →
inferno13–11-0.037%15 Jul →
mirage13–90.0514%15 Jul →
mirage13–11-0.0111%14 Jul →
anubis3–13-0.0428%14 Jul →
anubis13–11-0.007%14 Jul →
cache13–40.075%14 Jul →
ancient4–13-0.068%14 Jul →
dust28–13-0.0111%14 Jul →
ancient10–130.0015%13 Jul →
ancient13–11-0.0113%13 Jul →
nuke13–5-0.0316%12 Jul →
inferno11–130.0113%12 Jul →
anubis0–13-0.0613%12 Jul →
anubis13–6-0.0119%11 Jul →
dust213–50.0414%11 Jul →
ancient9–13-0.035%11 Jul →
cache14–160.0310%10 Jul →
inferno13–50.0212%10 Jul →
mirage6–13-0.0413%10 Jul →
inferno7–130.0112%10 Jul →
ancient15–15-0.048%10 Jul →
cache5–13-0.088%10 Jul →
cache13–110.049%10 Jul →
nuke13–100.0913%9 Jul →
dust216–130.0118%9 Jul →
mirage13–40.052%9 Jul →
cache11–13-0.027%9 Jul →
mirage13–8-0.0120%9 Jul →
ancient13–11-0.0115%9 Jul →
dust23–13-0.055%9 Jul →
cache6–13-0.007%9 Jul →
inferno8–13-0.0313%9 Jul →
cache7–13-0.0416%7 Jul →
cache13–40.0412%7 Jul →
overpass9–13-0.0513%4 Jul →
nuke13–50.147%4 Jul →
dust24–130.039%4 Jul →
inferno13–30.0911%4 Jul →
anubis13–11-0.0113%4 Jul →
mirage4–13-0.0714%4 Jul →
dust216–14-0.0012%4 Jul →
inferno13–50.0616%4 Jul →
overpass14–160.045%28 Jun →
ancient13–10-0.046%27 Jun →
dust213–80.0312%25 Jun →
inferno15–150.0711%25 Jun →
inferno11–130.0411%23 Jun →
nuke7–13-0.025%23 Jun →
dust213–70.0212%22 Jun →
office5–13-0.075%21 Jun →
dust210–130.0613%16 Jun →
nuke10–13-0.009%16 Jun →
ancient6–13-0.039%12 Jun →
dust211–13-0.057%12 Jun →
nuke4–13-0.023%12 Jun →
ancient8–130.0310%8 Jun →
ancient9–130.025%5 Jun →
inferno13–50.0412%5 Jun →
overpass5–13-0.000%2 Jun →
dust213–100.0211%2 Jun →
mirage5–130.0526%2 Jun →
dust213–9-0.0516%30 May →
nuke13–110.1311%30 May →
nuke7–130.0110%23 May →
dust213–4-0.0218%16 May →
anubis13–3-0.029%16 May →
overpass4–13-0.046%16 May →
cache13–9-0.0810%8 May →
inferno1–13-0.095%8 May →
anubis14–16-0.039%4 May →
nuke13–90.079%15 Apr →
nuke10–13-0.048%12 Apr →
ancient13–50.029%11 Apr →
dust213–6-0.016%6 Apr →
ancient13–6-0.080%6 Apr →
office4–130.0411%5 Apr →
ancient5–130.019%3 Apr →
overpass4–130.029%3 Apr →
dust27–130.0210%30 Mar →
dust26–13-0.0510%27 Mar →
overpass7–13-0.079%20 Mar →
inferno0–13-0.116%20 Mar →
ancient16–13-0.0215%20 Mar →
overpass13–6-0.008%17 Mar →
nuke13–50.068%16 Mar →
anubis12–120.0210%16 Mar →

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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