в аквапааааркеее

в аквапааааркеее — CS2 Stats

76561198832317290[U:1:872051562]Steam profile ↗✓ No bans

3,041Tracked matches53%Win rate2020Tracked since
CSDB Rating7.0 StrongAll-Rounder
FaceitLevel 10 · 3,781 ELOTop 12.4% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGв аквапааааркеееFACEITLevel 10 · 3,781 ELOSTANDINGTop 12.4% of rankedcsdb.gg/stats

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Performance scores

Aim91
Positioning53
Utility55

0–100 skill scores via Leetify.

Recent form

STEADY48–52Last 10048%Win rateWLLWWLLWLL

Last 10 vs previous 10: −30pp win rate · −0.03 avg rating · +1.2pp headshot accuracy · −60ms reaction

Win rate down 30pp 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 0.02
  • Avg headshot accuracy 29%
  • Avg reaction 544ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 29%
  • Avg reaction 560ms

Last 20

  • 11–9 · 55% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 28%
  • Avg reaction 590ms

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.

Aim9.1
Utility5.5
Positioning5.3
Opening Duels5.4
Clutch4.2

Sharp aimerEffective flashes

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

m0NESY

Plays most like m0NESY 91% playstyle similarity

Most alike: aim profile, opening-duel success.

Where you differ: lower positioning 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

Strengths

Aim. Aim score of 91 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 38 points — deaths here waste a strong aim profile.

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 52% on CT to 34% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 577ms 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

Aim9.1
Positioning5.3
Utility5.5
Mechanics7.2
Opening Duels3.3
Win Impact6.1

Composite 7.0/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01−0.00
first ⅓ avg 0.01 → last ⅓ avg 0.01
Reaction time584ms+19ms
first ⅓ avg 565ms → last ⅓ avg 584ms
Headshot accuracy30.4%−5.6%
first ⅓ avg 36.0% → last ⅓ avg 30.4%

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

0.24Best match rating · 13–1 · inferno, 11 Aug →
79%Best headshot accuracy · 5–13 · dust2, 11 Feb →
375msFastest reaction time · 11–13 · ancient, 8 Aug →
13–0Biggest win · inferno, 29 Jul →

Across the last 100 tracked matches.

Highlights

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

Map breakdown

overpassBest map · 86% over 7infernoWeakest map · 33% over 9
MapGradePlayedRecordWin rateAvg rating
mirageB3116–1552%0.02
dust2B2914–1548%0.00
ancientC156–940%0.01
infernoD93–633%0.02
overpassS76–186%0.02
anubisC52–340%0.03
train—31–233%0.01
nuke—10–10%-0.02

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

4,352Matches
57%Win rate
1.28Avg K/D
90.7ADR
63%Headshot %

Clutches & streaks

41%1v1 clutch win
31%1v2 clutch win
36Longest win streak

Recent Faceit resultsLWLLW

MapMatchesWin rateAvg K/DAvg kills
Mirage62162%1.4319.3
Anubis31068%1.4718.6
Dust226661%1.4418.9
Ancient24958%1.3518.1
Inferno6072%1.5118.1
Overpass4856%1.2416.9
Vertigo4052%1.3419.9
Nuke3050%1.1418.6

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.

30.2%Headshot accuracy
40.1%Accuracy (enemy spotted)
40.9%Spray accuracy
82.2%Counter-strafing
9.4°Preaim
577msReaction time
34.3%T opening success
52.2%CT opening success
0.74Enemies flashed / flash
10.3%Flash assists
5.35HE damage / grenade
5.87Flashes / 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

    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 34.3312% — 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.

33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis13–90.1325%10 Jul →
dust20–8-0.0421%10 Jul →
inferno3–13-0.0728%26 Apr →
ancient13–10-0.0229%26 Apr →
mirage13–40.1043%26 Apr →
anubis9–13-0.0132%20 Apr →
ancient10–13-0.0145%20 Apr →
dust213–10-0.0227%16 Apr →
dust29–13-0.0816%28 Mar →
inferno7–13-0.0124%28 Mar →
overpass13–70.1431%12 Mar →
overpass13–60.1031%12 Mar →
overpass13–10-0.0222%18 Feb →
dust26–130.0726%16 Feb →
overpass6–13-0.047%16 Feb →
mirage13–70.0725%15 Feb →
mirage6–13-0.0429%14 Feb →
dust213–9-0.0429%14 Feb →
mirage13–10.0250%13 Feb →
mirage13–70.0227%13 Feb →
dust25–130.0279%11 Feb →
ancient13–70.0734%10 Feb →
ancient8–130.0427%9 Feb →
mirage11–13-0.0320%9 Feb →
anubis6–13-0.0444%9 Feb →
dust213–4-0.0212%3 Feb →
mirage13–80.0246%28 Jan →
anubis9–130.0628%20 Jan →
anubis13–110.0229%17 Jan →
mirage13–8-0.0131%17 Jan →
dust213–8-0.0034%15 Jan →
mirage7–130.0222%15 Jan →
mirage8–13-0.0030%12 Jan →
mirage8–130.0633%11 Jan →
dust28–130.0525%7 Jan →
mirage14–160.0948%3 Jan →
dust213–90.1236%24 Dec →
nuke11–13-0.0235%17 Dec →
dust210–13-0.0247%17 Dec →
dust27–13-0.0633%17 Dec →
mirage13–10-0.0024%15 Dec →
mirage13–40.0333%15 Dec →
ancient7–130.0350%14 Dec →
inferno13–100.0736%13 Dec →
dust213–50.0420%11 Dec →
mirage13–60.0630%9 Dec →
mirage9–130.0622%9 Dec →
overpass13–90.0530%5 Dec →
overpass13–11-0.0938%5 Dec →
dust213–40.0740%4 Dec →
dust24–13-0.0929%1 Dec →
mirage22–200.0433%1 Dec →
dust213–110.0540%30 Nov →
ancient13–50.0544%26 Nov →
dust213–110.0331%18 Nov →
mirage4–13-0.0918%17 Nov →
dust23–13-0.0447%3 Oct →
mirage1–13-0.0758%3 Oct →
train14–160.0023%1 Oct →
dust213–20.0521%1 Oct →
mirage10–13-0.0223%1 Oct →
mirage7–13-0.0533%11 Sept →
dust29–130.0241%11 Sept →
ancient3–13-0.0250%16 Aug →
inferno2–13-0.0356%16 Aug →
mirage13–110.1149%15 Aug →
ancient13–100.0144%15 Aug →
ancient13–100.0144%15 Aug →
dust27–13-0.0233%14 Aug →
ancient13–60.0222%14 Aug →
ancient10–130.0345%13 Aug →
train14–60.0959%13 Aug →
inferno6–13-0.0935%13 Aug →
mirage13–50.0431%11 Aug →
mirage8–13-0.1123%11 Aug →
ancient11–13-0.0426%11 Aug →
inferno13–10.2447%11 Aug →
inferno12–160.0137%8 Aug →
ancient11–130.0531%8 Aug →
mirage13–50.0431%2 Aug →
mirage2–13-0.0616%2 Aug →
dust26–13-0.0137%2 Aug →
ancient5–130.0232%2 Aug →
mirage13–100.1236%1 Aug →
dust25–130.0028%1 Aug →
mirage13–70.0539%30 Jul →
dust213–5-0.0038%30 Jul →
overpass13–60.0141%30 Jul →
inferno13–00.0957%29 Jul →
dust213–50.0758%29 Jul →
dust21–13-0.0720%29 Jul →
inferno6–13-0.0531%29 Jul →
mirage9–130.0330%28 Jul →
dust213–60.0540%28 Jul →
dust213–80.0461%28 Jul →
mirage9–130.0139%28 Jul →
dust24–13-0.0541%25 Jul →
train2–13-0.0521%25 Jul →
mirage13–80.0831%23 Jul →
ancient9–13-0.0826%15 Jul →

Match data via Leetify.

Recent teammates

Milestones

Faceit Level 103K ELO Club1,000 MatchesAim 90+
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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