samsung smart fridg 111

samsung smart fridg 111 — CS2 Stats

76561198995697134[U:1:1035431406]Steam profile ↗✓ No bans

821Tracked matches45%Win rate2023Tracked since
752Hours in CS
CSDB Rating4.1 DevelopingPositional Player
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 11 Sep 2026 (65 days ago). Ranks are recorded once per day this page is viewed.

+4Tracked matches · now 821
0.0ppWin rate · 44.8% → 44.8%

Rating over time

Premier CS Rating: 19,733 -2,673 14 Jan – 28 May · 3 days played
18,61722,406peak 22,40614 Jan28 May
Faceit ELO: 1,343 +0 31 Aug – 11 Sept · 2 observations
1,3431,343peak 1,34331 Aug11 Sept
22,406Peak Premier in tracked matches
1,343Highest Faceit ELO seen on CSDB
56Days played since 2026-01-08

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.

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CSDB.GGsamsung smart fridg 111PEAK ELO1,343csdb.gg/stats

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Performance scores

Aim50
Positioning49
Utility21

0–100 skill scores via Leetify.

Recent form

STEADY37–55–8Last 10037%Win rateLLLLWWWWLL

Last 10 vs previous 10: +10pp win rate · +0.04 avg rating · −4.7pp headshot accuracy · +20ms 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

  • 1–4 · 20% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 17%
  • Avg reaction 544ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 18%
  • Avg reaction 620ms

Last 20

  • 7–12–1 · 35% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 20%
  • Avg reaction 610ms

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 (+1.7 against its own average).

Aim5.0
Utility2.1
Positioning4.9
Opening Duels2.0
Clutch4.0

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 84% 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. 627ms 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

Aim5.0
Positioning4.9
Utility2.1
Mechanics5.6
Opening Duels1.5
Win Impact3.3

Composite 4.1/10 (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-0.00−0.00
first ⅓ avg -0.00 → last ⅓ avg -0.00
Reaction time622ms−4ms
first ⅓ avg 626ms → last ⅓ avg 622ms
Headshot accuracy22.7%+5.3%
first ⅓ avg 17.4% → last ⅓ avg 22.7%

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

0.19Best match rating · 13–5 · ancient, 16 Apr →
48%Best headshot accuracy · 13–5 · ancient, 16 Apr →
469msFastest reaction time · 5–13 · mirage, 25 Sept →
13–2Biggest win · inferno, 5 Feb →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L4Current streak
3–11In matches decided by ≤2 rounds
4Overtime games

Map breakdown

dust2Best map · 47% over 15mirageWeakest map · 22% over 18
MapGradePlayedRecordWin rateAvg rating
nukeB209–1145%-0.00
mirageD184–1422%-0.01
dust2B157–847%-0.01
infernoD155–1033%-0.01
ancientC145–936%0.00
anubisD103–730%0.01
cache—43–175%-0.05
overpass—21–150%-0.03
warden—10–10%-0.03
train—10–10%0.05

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (22% over 18). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Lifetime stats

41,114Lifetime kills
1.08K/D · Top 50% of tracked players
2,429Matches
43.3%Match win rate
41.1%Headshot %
2.7%Shot accuracy
4,437MVPs
752Hours (in match)
3,075Bombs planted
534Bombs defused

Most-used weapons

Lifetime map wins

2,893nuke
2,345dust2
2,257inferno
1,200vertigo
687train
289assault
234office
168italy

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

Faceit stats

Combat

97Matches
58%Win rate
1.08Avg K/D
75.6ADR
49%Headshot %

Clutches & streaks

40%1v1 clutch win
24%1v2 clutch win
7Longest win streak

Recent Faceit resultsWLLWL

MapMatchesWin rateAvg K/DAvg kills
Mirage2748%0.9312.4
Ancient1747%1.0017.5
Dust21362%1.0714.8
Inferno1369%1.0415.3
Nuke1173%1.2818.6
Anubis786%1.4518.6
Overpass450%1.3116.0
Train367%1.1921.7

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.

22.4%Headshot accuracy
28.9%Accuracy (enemy spotted)
31.9%Spray accuracy
75.1%Counter-strafing
11.5°Preaim
627msReaction time
35.6%T opening success
36.6%CT opening success
0.38Enemies flashed / flash
3.4%Flash assists
8.47HE damage / grenade
0.99Flashes / 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 0.3797 — 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 35.6206% — 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.

22% win rate across 18 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke4–11-0.0422%27 Oct →
mirage11–130.0320%27 Oct →
ancient9–130.0118%24 Oct →
mirage5–13-0.049%25 Sept →
nuke13–60.0317%3 Aug →
ancient13–30.0910%3 Aug →
nuke13–60.0715%3 Aug →
mirage13–50.0411%3 Aug →
ancient10–130.0032%15 Jul →
dust210–130.0323%14 Jul →
nuke11–130.0137%7 Jul →
mirage2–13-0.0417%25 Jun →
inferno10–13-0.0328%21 Jun →
nuke10–13-0.0420%16 Jun →
ancient13–6-0.0415%30 May →
inferno13–7-0.0324%28 May →
cache13–8-0.0220%28 May →
ancient11–130.0126%25 May →
anubis12–12-0.0126%25 May →
mirage6–13-0.0011%16 May →
nuke0–13-0.0715%15 May →
cache0–12-0.1817%1 May →
cache13–90.0024%29 Apr →
cache4–0-0.0129%29 Apr →
dust213–9-0.0824%21 Apr →
mirage11–130.0330%17 Apr →
inferno7–13-0.0417%16 Apr →
nuke13–50.0218%16 Apr →
nuke13–70.0533%16 Apr →
ancient13–50.1948%16 Apr →
inferno13–16-0.0338%14 Apr →
mirage11–130.0228%14 Apr →
mirage10–13-0.0126%14 Apr →
inferno0–5-0.0033%10 Apr →
dust214–16-0.0622%6 Apr →
mirage13–110.0123%6 Apr →
anubis7–13-0.0927%6 Apr →
ancient4–13-0.0819%6 Apr →
nuke11–130.0125%4 Apr →
inferno13–90.0016%4 Apr →
mirage7–13-0.0236%4 Apr →
nuke13–50.0329%4 Apr →
overpass4–13-0.0824%4 Apr →
nuke15–15-0.0720%28 Mar →
ancient13–110.0020%28 Mar →
anubis6–13-0.0117%28 Mar →
mirage3–13-0.0321%26 Mar →
dust213–7-0.0517%20 Mar →
anubis12–120.0125%20 Mar →
inferno13–40.0723%18 Mar →
dust210–13-0.016%16 Mar →
nuke13–9-0.0021%15 Mar →
ancient2–130.0023%15 Mar →
inferno2–13-0.0919%10 Mar →
inferno0–13-0.0336%10 Mar →
anubis13–90.0214%9 Mar →
dust213–8-0.0913%7 Mar →
inferno8–13-0.039%7 Mar →
mirage11–13-0.0210%6 Mar →
inferno6–13-0.0313%6 Mar →
ancient5–13-0.0610%6 Mar →
nuke13–10-0.0213%6 Mar →
mirage12–12-0.039%2 Mar →
nuke6–13-0.0221%2 Mar →
overpass13–80.0119%26 Feb →
mirage7–13-0.0614%22 Feb →
mirage12–120.0417%22 Feb →
ancient11–13-0.0215%13 Feb →
dust27–13-0.0229%13 Feb →
dust213–50.0320%13 Feb →
inferno9–13-0.0122%8 Feb →
dust213–3-0.0117%7 Feb →
anubis12–120.0516%7 Feb →
dust216–140.0113%5 Feb →
ancient13–80.0225%5 Feb →
inferno13–20.0318%5 Feb →
mirage13–9-0.0221%1 Feb →
anubis5–130.0221%1 Feb →
nuke13–90.0418%28 Jan →
nuke13–80.0926%27 Jan →
dust212–12-0.0226%27 Jan →
dust213–50.0010%24 Jan →
dust25–130.0015%24 Jan →
nuke7–13-0.0622%24 Jan →
nuke6–13-0.0614%23 Jan →
warden9–13-0.0314%22 Jan →
mirage5–13-0.0913%19 Jan →
nuke11–130.0213%18 Jan →
ancient6–13-0.0117%15 Jan →
inferno13–40.0615%14 Jan →
dust212–120.0523%14 Jan →
anubis13–30.0316%14 Jan →
anubis11–130.0114%14 Jan →
mirage13–6-0.059%13 Jan →
nuke5–13-0.0814%13 Jan →
anubis13–30.0417%11 Jan →
train6–130.0516%10 Jan →
dust29–13-0.0119%9 Jan →
inferno6–13-0.0514%8 Jan →
ancient5–13-0.1014%8 Jan →

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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