Aquarellah

Aquarellah — CS2 Stats

76561199204944806[U:1:1244679078]Steam profile ↗✓ No bans

784Tracked matches41%Win rate2025Tracked since
455Hours in CS
CSDB Rating4.4 DevelopingPositional Player
Premier CS Rating13,910Blue band · top ~34.2% of ranked players (population est.)
FaceitLevel 3 · 887 ELOTop 90.6% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 8 Apr 2026 (220 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: 13,910 -666 11 Feb – 8 Apr · 21 days played
13,91016,700peak 16,70011 Feb8 Apr
16,732Peak Premier in tracked matches
887Highest Faceit ELO seen on CSDB
36Days played since 2026-02-02

Faceit ELO

  • At peak — 887
  • Next: Level 4 at 901 — 14 to go
  • Reached: Level 3 · Level 2

Premier CS Rating

  • 2,790 below peak (16,700)
  • -2,493 over 30 days · declining
  • Next: Purple band at 15,000 — 1,090 to go
  • Reached: 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.

How this compares with the same rank

Median values for Level 3 among CSDB-tracked players (n=10,505), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerLevel 3 medianLevel 4 medianvs Level 4
Headshot rate47.6%41.8%42.7%above
Shot accuracy0.0%12.2%11.2%11.2% short
Kill/death ratio0.700.980.990.29 short
Match win rate45.0%43.3%43.9%above

This profile matches the typical Level 4 player on 2 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 4 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGAquarellahFACEITLevel 3 · 887 ELOSTANDINGTop 90.6% of rankedPREMIER13,910 · Blue bandPEAK ELO887csdb.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

Aim43
Positioning61
Utility42

0–100 skill scores via Leetify.

Recent form

COLD39–56–5Last 10039%Win rateWLWWLLLLLL

Last 10 vs previous 10: −10pp win rate · +0.01 avg rating · +4.7pp headshot accuracy · +51ms 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

  • 3–2 · 60% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 21%
  • Avg reaction 748ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 22%
  • Avg reaction 770ms

Last 20

  • 7–13 · 35% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 20%
  • Avg reaction 745ms

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).

Aim4.3
Utility4.2
Positioning6.1
Opening Duels4.3
Clutch4.4

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 80% 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. 741ms 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

Aim4.3
Positioning6.1
Utility4.2
Mechanics6.2
Opening Duels3.2
Win Impact2.1

Composite 4.4/10 (Developing), 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-0.02+0.01
first ⅓ avg -0.03 → last ⅓ avg -0.02
Reaction time749ms+69ms
first ⅓ avg 679ms → last ⅓ avg 749ms
Headshot accuracy18.0%+0.5%
first ⅓ avg 17.4% → last ⅓ avg 18.0%

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

0.09Best match rating · 13–4 · mirage, 26 Mar →
43%Best headshot accuracy · 13–9 · inferno, 12 Mar →
438msFastest reaction time · 13–11 · anubis, 28 Feb →
13–2Biggest win · overpass, 14 Mar →

Across the last 100 tracked matches.

Highlights

6Longest win streak
5–8In matches decided by ≤2 rounds
6Overtime games

Map breakdown

anubisBest map · 75% over 8dust2Weakest map · 21% over 14
MapGradePlayedRecordWin rateAvg rating
nukeC207–1335%-0.03
ancientC197–1237%-0.04
infernoC167–944%-0.03
dust2D143–1121%-0.03
mirageC125–742%-0.03
overpassC94–544%-0.05
anubisS86–275%-0.03
cache—10–10%-0.04
stronghold—10–10%-0.06

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (21% over 14). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

13,401Lifetime kills
0.70K/D
1,027Matches
45.0%Match win rate · Top 50% of Level 3 players
47.6%Headshot % · Top 25% of Level 3 players
0.0%Shot accuracy
1,474MVPs
455Hours (in match)
913Bombs planted
224Bombs defused

Most-used weapons

Lifetime map wins

1,817inferno
1,797dust2
1,544nuke
366train
81vertigo
13italy
9lake
1office

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

296Matches
49%Win rate
0.80Avg K/D
65.5ADR
45%Headshot %

Clutches & streaks

42%1v1 clutch win
16%1v2 clutch win
8Longest win streak

Recent Faceit resultsLLLLW

MapMatchesWin rateAvg K/DAvg kills
Ancient7051%0.9214.1
Inferno6349%0.7512.3
Dust25145%0.7911.9
Nuke4951%0.7512.7
Overpass2556%0.7513.8
Mirage2241%0.6911.8
Train1040%0.8214.1
Anubis650%1.0013.7

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.

18.0%Headshot accuracy
30.7%Accuracy (enemy spotted)
34.6%Spray accuracy
78.0%Counter-strafing
10.7°Preaim
741msReaction time
44.0%T opening success
41.5%CT opening success
0.63Enemies flashed / flash
4.2%Flash assists
12.31HE damage / grenade
4.94Flashes / 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 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 741.2776ms — above the 700ms mark we flag

    Aim Training →
Spend your practice time on Dust 2

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

21% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis13–50.0318%20 Jul →
cache3–13-0.0422%20 Jul →
anubis13–7-0.0113%11 Apr →
ancient13–6-0.0324%11 Apr →
mirage10–130.0325%8 Apr →
mirage4–13-0.0319%8 Apr →
ancient4–13-0.0936%6 Apr →
mirage4–13-0.0829%6 Apr →
dust21–13-0.108%4 Apr →
nuke7–130.0124%4 Apr →
dust211–13-0.0114%31 Mar →
dust23–130.0115%29 Mar →
ancient13–16-0.0012%28 Mar →
dust213–6-0.1013%28 Mar →
ancient13–11-0.0513%28 Mar →
mirage0–13-0.0740%28 Mar →
ancient3–13-0.0811%28 Mar →
nuke3–13-0.0624%28 Mar →
ancient13–8-0.0310%26 Mar →
nuke13–7-0.0220%26 Mar →
dust212–120.0122%26 Mar →
mirage13–4-0.0116%26 Mar →
mirage13–40.099%26 Mar →
mirage7–13-0.0726%24 Mar →
overpass9–13-0.0222%24 Mar →
dust213–40.078%23 Mar →
inferno10–130.0220%23 Mar →
dust28–130.0110%23 Mar →
mirage13–4-0.0514%23 Mar →
ancient13–10-0.0413%22 Mar →
anubis6–130.0123%22 Mar →
inferno5–13-0.0114%22 Mar →
dust29–13-0.066%20 Mar →
mirage13–11-0.1317%20 Mar →
dust213–30.0116%19 Mar →
anubis1–13-0.0621%19 Mar →
mirage13–50.0235%19 Mar →
nuke11–130.0118%19 Mar →
dust210–13-0.0420%18 Mar →
dust211–13-0.0422%18 Mar →
ancient5–13-0.0318%16 Mar →
nuke5–13-0.0419%16 Mar →
inferno7–13-0.0620%16 Mar →
overpass13–2-0.068%14 Mar →
dust26–13-0.0814%14 Mar →
overpass3–13-0.0535%13 Mar →
overpass8–13-0.0814%13 Mar →
nuke15–15-0.0113%12 Mar →
inferno13–9-0.0243%12 Mar →
nuke5–13-0.0810%12 Mar →
ancient8–13-0.0537%8 Mar →
nuke10–13-0.0720%7 Mar →
nuke10–13-0.0425%7 Mar →
anubis13–8-0.0727%7 Mar →
ancient3–13-0.0614%7 Mar →
nuke10–13-0.0719%7 Mar →
anubis13–10-0.0018%1 Mar →
stronghold4–13-0.0616%1 Mar →
dust27–13-0.0317%1 Mar →
ancient7–13-0.0519%28 Feb →
nuke3–13-0.0318%28 Feb →
overpass13–9-0.0113%28 Feb →
mirage15–15-0.0320%28 Feb →
inferno16–12-0.0715%28 Feb →
anubis13–11-0.0427%28 Feb →
ancient13–5-0.0523%28 Feb →
ancient13–110.0126%28 Feb →
nuke13–4-0.0124%28 Feb →
ancient13–8-0.0922%27 Feb →
overpass14–16-0.0718%27 Feb →
dust212–12-0.0219%26 Feb →
nuke13–8-0.0219%25 Feb →
overpass2–13-0.0325%25 Feb →
ancient11–13-0.0213%21 Feb →
ancient2–13-0.037%21 Feb →
ancient9–13-0.0113%18 Feb →
inferno12–120.0322%18 Feb →
ancient11–13-0.0615%13 Feb →
inferno13–7-0.0811%13 Feb →
inferno13–10-0.0513%13 Feb →
inferno13–11-0.0018%12 Feb →
nuke5–13-0.0529%11 Feb →
inferno16–13-0.0731%11 Feb →
nuke13–10-0.0317%11 Feb →
nuke13–6-0.0419%11 Feb →
inferno8–13-0.0818%11 Feb →
overpass13–3-0.0518%11 Feb →
nuke13–9-0.0710%11 Feb →
overpass13–3-0.0626%11 Feb →
anubis13–7-0.0710%11 Feb →
mirage10–13-0.0311%11 Feb →
inferno4–13-0.0119%9 Feb →
ancient11–13-0.0216%6 Feb →
inferno11–130.0221%6 Feb →
nuke13–9-0.0720%6 Feb →
nuke10–130.0110%5 Feb →
inferno13–7-0.0213%3 Feb →
inferno3–13-0.0213%3 Feb →
inferno4–130.0123%2 Feb →
nuke6–13-0.0513%2 Feb →

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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