emoney[HH]

emoney[HH] — CS2 Stats

AM76561197960406870[U:1:141142]Steam profile ↗✓ No bans

4,029Tracked matches45%Win rate2020Tracked since
CSDB Rating5.0 DevelopingPositional Player
Premier CS Rating17,480Purple band · top ~18.5% of ranked players (population est.)
FaceitLevel 8 · 1,407 ELOTop 31.2% of ranked FACEIT players
WingmanMaster Guardian I
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 6 Nov 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.

Rating over time

Premier CS Rating: 17,480 -4,162 29 Aug – 6 Nov · 27 days played
16,96422,141peak 22,14129 Aug6 Nov
Faceit ELO: 1,407 +0 29 Aug – 14 Sept · 3 observations
1,4071,407peak 1,40729 Aug14 Sept
22,248Peak Premier in tracked matches
1,407Highest Faceit ELO seen on CSDB
34Days played since 2026-08-29

Faceit ELO

  • At peak — 1,407
  • Next: Level 8 at 1,531 — 124 to go
  • Reached: Level 7 · Level 6 · Level 5 · Level 4
  • Level 7 first seen 2026-08-29
  • Level 6 first seen 2026-08-29

Premier CS Rating

  • 4,661 below peak (22,141)
  • -3,233 over 30 days · declining
  • Next: Pink band at 20,000 — 2,520 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band
  • Pink band first seen 2026-08-29
  • Purple band first seen 2026-08-29

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.GGemoney[HH]FACEITLevel 8 · 1,407 ELOSTANDINGTop 31.2% of rankedPREMIER17,480 · Purple bandPEAK ELO1,407csdb.gg/stats

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Performance scores

Aim59
Positioning62
Utility54

0–100 skill scores via Leetify.

Recent form

STEADY41–50–9Last 10041%Win rateLWWLWWLWLW

Last 10 vs previous 10: +40pp win rate · +0.03 avg rating · +3.4pp headshot accuracy · −35ms reaction

Win rate up 40pp 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

  • 3–2 · 60% win rate
  • Avg rating 0.06
  • Avg headshot accuracy 15%
  • Avg reaction 503ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 15%
  • Avg reaction 548ms

Last 20

  • 8–11–1 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 13%
  • Avg reaction 565ms

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 (+2.2 against its own average).

Aim5.9
Utility5.4
Positioning6.2
Opening Duels1.6
Clutch2.8

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

iM

Plays most like iM 79% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: 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. 578ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 68% 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

Aim5.9
Positioning6.2
Utility5.4
Mechanics4.1
Opening Duels2.8
Win Impact3.3

Composite 5.0/10 (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 rating0.00−0.03
first ⅓ avg 0.03 → last ⅓ avg 0.00
Reaction time572ms+76ms
first ⅓ avg 496ms → last ⅓ avg 572ms
Headshot accuracy12.7%−6.9%
first ⅓ avg 19.6% → last ⅓ avg 12.7%

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 · 3–13 · ancient, 24 Oct →
37%Best headshot accuracy · 6–13 · nuke, 2 Oct →
359msFastest reaction time · 1–13 · ancient, 11 Oct →
13–2Biggest win · dust2, 12 Oct →

Across the last 100 tracked matches.

Highlights

3Longest win streak
4–3In matches decided by ≤2 rounds
11Overtime games

Map breakdown

anubisBest map · 60% over 5infernoWeakest map · 25% over 8
MapGradePlayedRecordWin rateAvg rating
dust2C4419–2543%0.02
cacheD144–1029%0.00
mirageB115–645%-0.02
ancientC114–736%0.02
infernoD82–625%0.01
anubisA53–260%-0.00
nuke—43–175%0.06
train—20–20%-0.03
office—11–0100%-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (25% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

714Matches
49%Win rate
1.01Avg K/D
85.2ADR
45%Headshot %

Clutches & streaks

34%1v1 clutch win
20%1v2 clutch win
9Longest win streak

Recent Faceit resultsLLWWW

MapMatchesWin rateAvg K/DAvg kills
Dust220151%1.0415.8
Ancient13445%0.9715.4
Anubis8245%1.0816.7
Nuke7254%1.0214.6
Mirage6853%0.9814.3
Inferno6751%0.9915.2
Vertigo3549%0.9713.5
Cache1856%0.9617.9

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.

13.1%Headshot accuracy
33.8%Accuracy (enemy spotted)
37.3%Spray accuracy
68.5%Counter-strafing
8.3°Preaim
578msReaction time
48.1%T opening success
34.6%CT opening success
0.59Enemies flashed / flash
4.9%Flash assists
9.57HE damage / grenade
10.45Flashes / 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 13.068% — below the 15% mark we flag

    Aim Training →
  2. Advanced Mechanics

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 34.5763% — below the 40% mark we flag

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.

25% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage7–13-0.0516%6 Nov →
inferno13–30.1417%6 Nov →
dust213–40.097%6 Nov →
dust23–130.0621%6 Nov →
dust213–30.0615%5 Nov →
dust213–5-0.045%2 Nov →
train7–13-0.049%2 Nov →
office13–7-0.0414%2 Nov →
mirage5–13-0.0719%2 Nov →
dust213–8-0.0822%2 Nov →
ancient2–13-0.026%2 Nov →
dust212–120.0115%31 Oct →
inferno6–13-0.128%31 Oct →
ancient6–13-0.1015%30 Oct →
cache13–80.0515%30 Oct →
inferno10–13-0.048%30 Oct →
mirage13–50.038%30 Oct →
dust26–13-0.0013%30 Oct →
dust211–13-0.0318%29 Oct →
cache1–13-0.055%29 Oct →
inferno13–4-0.0711%29 Oct →
mirage6–13-0.065%29 Oct →
dust213–50.0316%29 Oct →
nuke13–40.1014%29 Oct →
dust27–130.0420%29 Oct →
ancient13–5-0.005%28 Oct →
cache13–160.0122%28 Oct →
cache13–4-0.048%28 Oct →
cache6–130.0812%27 Oct →
dust210–13-0.0212%24 Oct →
nuke13–70.0713%24 Oct →
ancient3–130.1410%24 Oct →
anubis8–13-0.0315%23 Oct →
dust26–130.0320%23 Oct →
dust212–120.0213%23 Oct →
dust28–13-0.0029%22 Oct →
anubis7–13-0.0510%20 Oct →
anubis16–14-0.069%20 Oct →
dust29–130.0328%16 Oct →
dust29–13-0.0510%15 Oct →
dust211–50.0728%15 Oct →
dust25–13-0.0122%15 Oct →
ancient12–160.0418%15 Oct →
anubis16–130.0615%15 Oct →
cache5–13-0.0115%15 Oct →
dust25–13-0.0410%12 Oct →
dust213–60.0022%12 Oct →
dust213–20.068%12 Oct →
mirage4–13-0.089%12 Oct →
mirage13–80.0326%12 Oct →
nuke13–10-0.0011%11 Oct →
inferno10–130.0924%11 Oct →
ancient1–13-0.0113%11 Oct →
ancient13–8-0.0312%11 Oct →
dust213–5-0.0417%11 Oct →
cache15–150.0221%10 Oct →
mirage2–13-0.0323%10 Oct →
dust213–6-0.0023%10 Oct →
mirage15–15-0.0018%8 Oct →
ancient12–160.1316%8 Oct →
ancient10–13-0.0113%8 Oct →
dust213–100.0717%7 Oct →
cache13–7-0.0012%7 Oct →
dust28–13-0.0318%7 Oct →
mirage13–110.0033%5 Oct →
cache4–13-0.0226%5 Oct →
dust23–13-0.0632%5 Oct →
ancient13–70.0624%4 Oct →
anubis13–110.078%4 Oct →
cache19–170.0311%3 Oct →
inferno11–130.0013%3 Oct →
nuke6–130.0837%2 Oct →
train12–12-0.0118%1 Oct →
dust28–130.0528%1 Oct →
mirage13–100.0324%1 Oct →
dust213–8-0.0130%29 Sept →
dust215–15-0.0020%28 Sept →
cache6–13-0.0317%28 Sept →
inferno11–130.0418%28 Sept →
dust213–60.0721%28 Sept →
dust213–30.0612%26 Sept →
cache7–130.0026%25 Sept →
dust213–40.1018%25 Sept →
dust212–120.0725%25 Sept →
dust26–130.0431%25 Sept →
cache9–130.0124%25 Sept →
dust213–160.0313%24 Sept →
cache6–13-0.0122%24 Sept →
inferno8–130.065%24 Sept →
dust23–130.0123%22 Sept →
dust213–100.0323%22 Sept →
dust213–50.0923%22 Sept →
ancient13–30.0016%22 Sept →
dust212–120.0916%21 Sept →
mirage13–3-0.0111%20 Sept →
dust212–120.0415%20 Sept →
dust27–130.0126%19 Sept →
dust27–130.029%19 Sept →
dust216–130.0321%19 Sept →
dust213–90.0622%17 Sept →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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