Chatounnet

Chatounnet — CS2 Stats

FR76561198378759355[U:1:418493627]Steam profile ↗✓ No bans

133Tracked matches62%Win rate2024Tracked since
CSDB Rating6.0 SolidPositional Player
WingmanGold Nova III
Ladder ranks via Leetify

Performance scores

Aim82
Positioning48
Utility13

0–100 skill scores via Leetify.

Recent form

STEADY55–32–13Last 10055%Win rateTLWLTLWWLW

Last 10 vs previous 10: 0pp win rate · +0.02 avg rating · −3.1pp headshot accuracy · +32ms reaction

Win rate 0pp 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

  • 1–2–2 · 20% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 23%
  • Avg reaction 625ms

Last 10

  • 4–4–2 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 23%
  • Avg reaction 652ms

Last 20

  • 8–8–4 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 25%
  • Avg reaction 636ms

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 (+1.6 against its own average).

Aim8.2
Utility1.3
Positioning4.8
Opening Duels3.6

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

donk

Plays most like donk 81% playstyle similarity

Most alike: aim profile, opening-duel success.

Where you differ: lower positioning profile; lower utility contribution.

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

Positioning. Positioning trails aim by 34 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 48% on CT to 33% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 657ms 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

Aim8.2
Positioning4.8
Utility1.3
Mechanics8.4
Opening Duels2.6
Win Impact8.8

Composite 6.0/10 (Solid), 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 rating0.03+0.00
first ⅓ avg 0.03 → last ⅓ avg 0.03
Reaction time666ms−35ms
first ⅓ avg 702ms → last ⅓ avg 666ms
Headshot accuracy26.5%+1.2%
first ⅓ avg 25.3% → last ⅓ avg 26.5%

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

0.19Best match rating · 13–1 · vertigo, 16 Apr →
53%Best headshot accuracy · 8–1 · dust2, 22 Nov →
453msFastest reaction time · 7–13 · vertigo, 21 May →
13–0Biggest win · nuke, 22 Nov →

Across the last 100 tracked matches.

Highlights

8Longest win streak
7–6In matches decided by ≤2 rounds

Map breakdown

ancientBest map · 71% over 7mirageWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
infernoB168–850%-0.01
vertigoA159–660%0.04
dust2A127–558%0.03
anubisA127–558%0.02
nukeB126–650%0.03
mirageD72–529%0.01
overpassC73–443%0.03
cacheA74–357%0.03
ancientS75–271%0.01
warden—21–150%0.04
office—22–0100%0.04
train—11–0100%0.00

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (29% over 7). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

26.6%Headshot accuracy
33.4%Accuracy (enemy spotted)
39.7%Spray accuracy
87.7%Counter-strafing
8.6°Preaim
657msReaction time
32.6%T opening success
48.0%CT opening success
0.16Enemies flashed / flash
0.0%Flash assists
3.60HE damage / grenade
1.57Flashes / 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. 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 0.1566 — below the 0.5 mark we flag

    Grenade Lineups →
  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 32.5567% — below the 40% mark we flag

Spend your practice time on Mirage

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

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno12–120.0825%24 Sept →
mirage3–130.0313%24 Sept →
vertigo13–4-0.0017%21 Sept →
dust211–130.0424%9 Sept →
vertigo12–120.0137%3 Jun →
inferno10–13-0.0233%29 May →
anubis13–110.0321%27 May →
vertigo13–70.0620%27 May →
anubis4–13-0.0420%25 May →
overpass13–30.1121%25 May →
mirage4–13-0.0324%23 May →
vertigo13–80.0220%23 May →
cache13–10-0.0023%23 May →
cache12–12-0.0126%22 May →
inferno6–13-0.0722%21 May →
cache13–70.1837%21 May →
vertigo7–130.0121%21 May →
vertigo9–60.0935%20 May →
inferno11–13-0.0328%20 May →
cache12–12-0.0224%16 May →
cache13–60.0531%13 May →
overpass13–50.0319%13 May →
inferno13–5-0.0016%10 May →
cache13–60.0137%8 May →
cache11–130.0336%8 May →
ancient13–8-0.0131%8 May →
ancient13–60.0623%30 Apr →
vertigo6–130.0128%30 Apr →
inferno13–110.0426%20 Apr →
vertigo13–10.1944%16 Apr →
nuke13–90.0742%16 Apr →
dust26–130.0422%15 Apr →
warden13–60.1128%15 Apr →
warden1–13-0.0423%15 Apr →
overpass2–13-0.0724%1 Feb →
mirage3–13-0.0529%3 Jan →
inferno10–130.0017%1 Jan →
ancient13–11-0.0316%29 Dec →
anubis12–120.0123%26 Dec →
inferno13–80.0226%26 Dec →
mirage13–30.0126%26 Dec →
nuke7–130.0532%24 Dec →
vertigo13–30.0628%23 Dec →
overpass12–120.0224%23 Dec →
inferno6–13-0.0528%22 Dec →
nuke13–110.0625%22 Dec →
mirage12–120.0120%21 Dec →
dust211–13-0.0211%21 Dec →
nuke8–8-0.0525%21 Dec →
dust213–50.0725%20 Dec →
anubis10–130.0317%20 Dec →
inferno13–11-0.0323%19 Dec →
overpass5–2-0.0517%19 Dec →
inferno11–13-0.0332%18 Dec →
dust26–130.0224%18 Dec →
dust213–90.0428%18 Dec →
overpass10–130.1318%17 Dec →
overpass7–130.0323%17 Dec →
dust212–12-0.0120%16 Dec →
train13–100.0018%15 Dec →
ancient11–13-0.0423%11 Dec →
anubis13–3-0.029%11 Dec →
inferno13–10-0.0329%10 Dec →
mirage12–120.0631%9 Dec →
inferno3–13-0.0713%9 Dec →
nuke9–130.0123%6 Dec →
anubis6–13-0.0129%3 Dec →
dust213–110.0420%1 Dec →
anubis13–20.0633%29 Nov →
vertigo12–120.0130%29 Nov →
office13–60.0422%26 Nov →
office13–90.0436%26 Nov →
anubis13–80.0421%23 Nov →
vertigo13–70.0129%22 Nov →
anubis13–60.1018%22 Nov →
dust28–10.1053%22 Nov →
nuke13–00.1134%22 Nov →
dust213–50.0021%20 Nov →
vertigo10–13-0.0021%19 Nov →
vertigo13–70.0717%19 Nov →
nuke13–90.0532%19 Nov →
nuke13–110.0223%17 Nov →
nuke10–13-0.0124%15 Nov →
anubis6–13-0.0133%11 Nov →
ancient13–40.0415%10 Nov →
nuke13–60.0227%8 Nov →
ancient13–90.0319%8 Nov →
nuke12–120.0123%7 Nov →
dust213–20.0423%7 Nov →
mirage13–40.0327%6 Nov →
inferno13–10-0.0226%5 Nov →
vertigo13–10-0.0140%2 Nov →
anubis13–7-0.0215%1 Nov →
vertigo7–130.0423%29 Oct →
nuke8–13-0.0320%27 Oct →
ancient12–12-0.0015%24 Oct →
inferno13–60.0216%24 Oct →
dust213–20.0535%23 Oct →
anubis13–50.0522%23 Oct →
inferno13–80.0524%23 Oct →

Match data via Leetify.

Recent teammates

Milestones

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

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