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Frikadellen

Frikadellen — CS2 Stats

DK76561199006568945[U:1:1046303217]Steam profile ↗✓ No bans

1,485Tracked matches52%Win rate2020Tracked since
1,316Hours in CS
CSDB Rating6.2 SolidSupport
CSDB Leaderboard#180988 of 258177 tracked
FaceitLevel 9 · 1,782 ELOTop 20.7% of ranked FACEIT players
WingmanLegendary Eagle
Ladder ranks via Leetify

Rating over time

10,661Peak Premier in tracked matches
1,782Highest Faceit ELO seen on CSDB
73Days played since 2025-02-15

Faceit ELO

  • At peak — 1,782
  • Next: Level 10 at 2,001 — 219 to go
  • Reached: Level 9 · Level 8 · Level 7 · Level 6

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 9 among CSDB-tracked players (n=15,132), 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 9 medianLevel 10 medianvs Level 10
Headshot rate47.4%48.2%50.9%3.5% short
Shot accuracy15.9%13.2%13.7%above
Kill/death ratio0.991.071.090.10 short
Match win rate46.5%46.9%48.4%1.9% short

This profile matches the typical Level 10 player on 1 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Level 10 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGFrikadellenFACEITLevel 9 · 1,782 ELOSTANDINGTop 20.7% of rankedPEAK ELO1,782csdb.gg/stats

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Performance scores

Aim81
Positioning55
Utility58

0–100 skill scores via Leetify.

Recent form

STEADY51–46–3Last 10051%Win rateLLWWLLWWWW

Last 10 vs previous 10: +20pp win rate · +0.00 avg rating · −0.3pp headshot accuracy · −48ms reaction

Win rate up 20pp 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

  • 2–3 · 40% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 14%
  • Avg reaction 580ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 20%
  • Avg reaction 554ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 20%
  • Avg reaction 578ms

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: Support — Utility contribution stands above the rest of this profile (+1.1 against its own average).

Aim8.1
Utility5.8
Positioning5.5
Opening Duels4.1
Clutch3.2

Strong CT-side opener

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

ZywOo

Plays most like ZywOo 96% playstyle similarity

Most alike: opening-duel success, aim profile.

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

Strengths

CT openings. 61% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 61% on CT to 25% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 626ms 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

Aim8.1
Positioning5.5
Utility5.8
Mechanics7.6
Opening Duels3.9
Win Impact5.6

Composite 6.2/10 (Solid), 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-0.00−0.01
first ⅓ avg 0.01 → last ⅓ avg -0.00
Reaction time624ms−81ms
first ⅓ avg 705ms → last ⅓ avg 624ms
Headshot accuracy21.4%−2.6%
first ⅓ avg 23.9% → last ⅓ avg 21.4%

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

0.14Best match rating · 13–5 · anubis, 8 Oct →
50%Best headshot accuracy · 5–13 · mirage, 28 Sept →
453msFastest reaction time · 11–13 · anubis, 10 Oct →
13–1Biggest win · grail, 13 May →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L2Current streak
12–7In matches decided by ≤2 rounds
12Overtime games

Map breakdown

anubisBest map · 64% over 14infernoWeakest map · 25% over 20
MapGradePlayedRecordWin rateAvg rating
ancientA2616–1062%0.01
infernoD205–1525%-0.01
mirageA148–657%-0.01
anubisA149–564%0.02
nukeD93–633%-0.00
overpassA74–357%-0.01
dust2—32–167%0.00
train—32–167%0.01
cache—20–20%0.01
vertigo—11–0100%0.05
grail—11–0100%0.09

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (25% over 20). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

63,774Lifetime kills
0.99K/D
2,727Matches
46.5%Match win rate
47.4%Headshot %
15.9%Shot accuracy · Top 50% of Level 9 players
7,450MVPs
1,316Hours (in match)
1,509Bombs planted
725Bombs defused

Most-used weapons

AK-4722,184
M4A4 / M4A1-S12,363
AWP7,482
Desert Eagle4,282
P2000 / USP-S2,608
Glock-182,582
Knife1,772
SG 5531,180
Galil AR1,110
MP91,045

Lifetime map wins

5,691inferno
4,413vertigo
2,555nuke
1,980dust2
1,375train
234cbble
70lake
40office

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

Faceit stats

Combat

2,027Matches
51%Win rate
0.96Avg K/D
79.5ADR
45%Headshot %

Clutches & streaks

36%1v1 clutch win
20%1v2 clutch win
11Longest win streak

Recent Faceit resultsWLLWW

MapMatchesWin rateAvg K/DAvg kills
Mirage15447%1.0215.1
Ancient15253%0.9915.9
Inferno12147%0.9515.6
Anubis11048%1.0116.3
Nuke7436%0.8714.5
Dust25841%0.9215.2
Overpass5744%0.9715.1
Vertigo2462%0.8614.1

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.

20.3%Headshot accuracy
38.2%Accuracy (enemy spotted)
39.9%Spray accuracy
84.1%Counter-strafing
9.0°Preaim
626msReaction time
25.4%T opening success
61.5%CT opening success
0.57Enemies flashed / flash
7.8%Flash assists
8.56HE damage / grenade
9.47Flashes / 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 25.3759% — 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 20 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno12–16-0.0717%21 Oct →
inferno8–13-0.0511%21 Oct →
ancient13–11-0.0210%16 Oct →
mirage13–50.0013%16 Oct →
cache9–13-0.0421%16 Oct →
anubis11–13-0.0215%10 Oct →
anubis13–50.1424%8 Oct →
nuke13–5-0.0635%5 Oct →
ancient16–140.0226%2 Oct →
ancient13–90.0724%2 Oct →
inferno13–50.0915%28 Sept →
mirage5–130.0150%28 Sept →
mirage6–13-0.0915%28 Sept →
anubis13–40.0124%25 Aug →
ancient13–20.0119%8 Jul →
nuke10–13-0.0415%8 Jul →
nuke13–16-0.0217%5 Jul →
mirage9–13-0.0324%2 Jul →
mirage13–30.019%23 May →
mirage7–13-0.0212%15 May →
cache12–120.0613%29 Apr →
nuke16–14-0.0426%19 Jan →
inferno6–13-0.0527%16 Jan →
ancient11–130.0222%9 Dec →
overpass13–100.0219%4 Dec →
inferno13–11-0.0225%4 Dec →
mirage13–90.0321%1 Dec →
inferno13–80.0229%24 Nov →
overpass8–130.0120%21 Nov →
overpass9–13-0.0615%21 Nov →
ancient13–100.0932%18 Nov →
dust213–30.0632%14 Nov →
overpass11–13-0.0628%14 Nov →
dust213–2-0.0119%13 Nov →
inferno10–13-0.0815%11 Nov →
ancient0–13-0.109%11 Nov →
ancient13–110.0439%6 Nov →
ancient7–13-0.0429%4 Nov →
train19–16-0.0327%2 Nov →
inferno9–13-0.0230%27 Oct →
ancient13–100.0422%23 Oct →
ancient13–100.0418%21 Oct →
inferno8–13-0.0134%20 Oct →
ancient13–60.0947%19 Oct →
overpass13–60.0426%16 Oct →
ancient11–13-0.0512%1 Oct →
mirage13–10-0.0411%27 Sept →
nuke7–130.0425%22 Sept →
inferno11–130.0320%19 Sept →
ancient1–13-0.0626%2 Sept →
ancient13–5-0.0020%30 Aug →
nuke9–130.0648%28 Aug →
overpass13–11-0.0333%22 Aug →
mirage13–11-0.0428%22 Aug →
inferno11–130.0432%20 Aug →
overpass13–70.0011%15 Aug →
ancient16–120.0421%15 Aug →
inferno14–16-0.0529%5 Aug →
mirage4–13-0.0029%5 Aug →
inferno13–90.0129%28 Jul →
inferno6–13-0.0324%21 Jul →
ancient13–60.0925%9 Jul →
ancient3–13-0.1033%5 Jul →
anubis13–8-0.0128%4 Jul →
vertigo13–50.0546%4 Jul →
inferno13–4-0.0022%3 Jul →
anubis16–140.0722%2 Jul →
mirage13–80.0720%1 Jul →
inferno6–13-0.0232%19 Jun →
ancient13–110.0231%5 Jun →
inferno15–150.0230%3 Jun →
anubis6–13-0.0422%27 May →
anubis13–110.0624%15 May →
grail13–10.0942%13 May →
nuke13–30.0936%4 May →
inferno13–16-0.0119%24 Apr →
train13–80.0033%24 Apr →
mirage13–30.0114%22 Apr →
anubis7–13-0.0236%18 Apr →
anubis5–13-0.0223%11 Apr →
anubis13–20.0919%10 Apr →
ancient13–40.0832%10 Apr →
ancient7–130.0129%1 Apr →
inferno15–15-0.0126%27 Mar →
nuke10–13-0.0223%22 Mar →
anubis13–90.0215%22 Mar →
mirage13–6-0.0216%25 Feb →
mirage8–13-0.0328%25 Feb →
train12–160.0516%21 Feb →
anubis13–100.0028%21 Feb →
inferno9–13-0.0413%21 Feb →
ancient13–10-0.0125%21 Feb →
nuke9–13-0.0622%20 Feb →
ancient9–130.0326%20 Feb →
ancient13–110.0317%20 Feb →
dust27–13-0.0424%20 Feb →
ancient5–13-0.0519%18 Feb →
anubis13–110.0622%15 Feb →
anubis9–13-0.0316%15 Feb →
ancient4–13-0.0511%15 Feb →

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 →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.

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