Mischgemuese — CS2 Stats

DE76561198080512771[U:1:120247043]Steam profile ↗✓ No bans

1,663Tracked matches41%Win rate2020Tracked since

5,758Hours in CS1Hrs last 2 wks

CSDB Rating6.0 SolidAll-Rounder

Premier CS Rating18,276Purple band · top ~15.4% of ranked players (population est.)

CSDB Leaderboard#110296 of 261589 tracked

FaceitLevel 5Top 67.6% of ranked FACEIT players

WingmanDistinguished Master Guardian

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 6 Oct 2026 (39 days ago). Ranks are recorded once per day this page is viewed.

0Premier CS Rating · 18,276 → 18,276

+1Tracked matches · now 1,663

0.0ppWin rate · 41.4% → 41.4%

Rating over time

Premier CS Rating: 18,276 -2,323 7 Jun – 6 Oct · 24 days played

22,065Peak Premier in tracked matches

35Days played since 2026-06-07

Premier CS Rating

3,419 below peak (21,695)
0 over 30 days · steady
-2,443 over 90 days
Next: Pink band at 20,000 — 1,724 to go
Reached: Pink band · Purple band · Blue band · Light Blue band
Purple band first seen 2026-09-01
Blue band first seen 2026-09-01

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 5 among CSDB-tracked players (n=14,283), 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.

Metric	This player	Level 5 median	Level 6 median	vs Level 6
Headshot rate	39.0%	43.8%	44.8%	5.8% short
Shot accuracy	19.3%	12.0%	12.4%	above
Kill/death ratio	1.04	1.02	1.03	meets
Match win rate	42.5%	44.7%	45.2%	2.8% short

This profile matches the typical Level 6 player on 2 of 4 comparable metrics.

Widest gap: Headshot rate. That is the metric furthest from the Level 6 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim82

Positioning53

Utility58

0–100 skill scores via Leetify.

Recent form

COLD41–54–5Last 10041%Win rateLLLLWLWLLW

Last 10 vs previous 10: −20pp win rate · −0.05 avg rating · +1.9pp headshot accuracy · −9ms reaction

Win rate down 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

1–4 · 20% win rate
Avg rating 0.01
Avg headshot accuracy 20%
Avg reaction 557ms

Last 10

3–7 · 30% win rate
Avg rating -0.01
Avg headshot accuracy 19%
Avg reaction 548ms

Last 20

8–12 · 40% win rate
Avg rating 0.01
Avg headshot accuracy 19%
Avg reaction 552ms

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.

Aim8.2

Utility5.8

Positioning5.3

Opening Duels4.2

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

Plays most like ZywOo 96% playstyle similarity

Most alike: aim profile, positioning profile.

Where you differ: lower utility contribution; lower opening-duel success.

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. 561ms 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

Positioning5.3

Utility5.8

Mechanics7.6

Opening Duels2.8

Win Impact2.1

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 rating0.01−0.00

first ⅓ avg 0.01 → last ⅓ avg 0.01

Reaction time574ms−98ms

first ⅓ avg 672ms → last ⅓ avg 574ms

Headshot accuracy19.1%+2.0%

first ⅓ avg 17.1% → last ⅓ avg 19.1%

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

0.21Best match rating · 3–0 · dust2, 12 Jul →

55%Best headshot accuracy · 3–0 · dust2, 12 Jul →

375msFastest reaction time · 13–5 · inferno, 8 Sept →

13–2Biggest win · train, 16 Aug →

Across the last 100 tracked matches.

Highlights

4Longest win streak

L4Current streak

5–13In matches decided by ≤2 rounds

11Overtime games

Map breakdown

dust2Best map · 78% over 9nukeWeakest map · 15% over 13

Map	Grade	Played	Record	Win rate	Avg rating
cache	D	16	5–11	31%	0.02
inferno	C	16	7–9	44%	-0.02
anubis	B	15	8–7	53%	-0.02
nuke	D	13	2–11	15%	-0.03
dust2	S	9	7–2	78%	0.02
mirage	C	9	4–5	44%	0.03
ancient	A	7	4–3	57%	0.00
train	D	7	2–5	29%	0.08
vertigo	—	3	1–2	33%	0.06
overpass	—	3	0–3	0%	0.05
office	—	2	1–1	50%	0.03

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (15% over 13). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

159,706Lifetime kills

1.04K/D · Top 50% of Level 5 players

7,922Matches

42.5%Match win rate

39.0%Headshot %

19.3%Shot accuracy · Top 5% of Level 5 players

18,957MVPs

3,193Hours (in match)

10,217Bombs planted

1,768Bombs defused

Most-used weapons

AK-4741,282

M4A4 / M4A1-S24,061

AWP20,066

Desert Eagle12,522

P2000 / USP-S9,128

Glock-185,594

MAC-104,161

P2504,033

SSG 083,989

MP93,426

Lifetime map wins

11,931inferno

9,377dust2

5,454cbble

3,406nuke

1,700vertigo

1,695train

373lake

218safehouse

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

Faceit stats

Combat

279Matches

51%Win rate

1.06Avg K/D

—ADR

40%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

10Longest win streak

Recent Faceit resultsWLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	15	53%	1.04	15.1
Inferno	12	50%	0.90	14.6
Anubis	7	71%	0.90	13.7
Overpass	7	57%	0.93	15.3
Nuke	6	33%	0.59	11.8
Dust2	6	67%	1.16	18.7
Vertigo	2	0%	0.98	17.0

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.

18.8%Headshot accuracy

38.2%Accuracy (enemy spotted)

40.3%Spray accuracy

84.1%Counter-strafing

9.7°Preaim

561msReaction time

33.8%T opening success

48.7%CT opening success

0.59Enemies flashed / flash

6.9%Flash assists

7.40HE damage / grenade

9.24Flashes / 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.

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 33.8009% — below the 40% mark we flag

Spend your practice time on Nuke

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

15% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
cache	5–13	0.06	26%	11 Oct →
vertigo	6–13	0.08	12%	27 Sept →
inferno	14–16	-0.02	15%	8 Sept →
cache	10–13	-0.03	25%	8 Sept →
inferno	13–5	-0.06	22%	8 Sept →
anubis	6–13	-0.03	15%	31 Aug →
cache	13–4	0.03	25%	31 Aug →
nuke	10–13	-0.02	16%	31 Aug →
nuke	3–13	-0.06	15%	24 Aug →
anubis	13–7	-0.09	24%	24 Aug →
cache	13–9	-0.02	12%	24 Aug →
nuke	9–13	-0.02	19%	18 Aug →
cache	10–13	0.03	23%	18 Aug →
nuke	13–4	0.01	25%	18 Aug →
anubis	13–6	0.03	15%	18 Aug →
inferno	12–16	-0.04	12%	16 Aug →
ancient	16–14	0.00	17%	16 Aug →
train	13–2	0.21	9%	16 Aug →
train	3–13	0.02	26%	16 Aug →
train	7–13	0.08	18%	16 Aug →
train	3–13	-0.01	19%	16 Aug →
dust2	9–13	-0.04	20%	12 Aug →
anubis	7–13	-0.05	8%	12 Aug →
inferno	13–3	-0.02	21%	12 Aug →
nuke	2–5	0.04	31%	10 Aug →
nuke	15–15	-0.01	18%	5 Aug →
cache	7–13	-0.00	24%	3 Aug →
ancient	13–11	0.02	32%	3 Aug →
dust2	13–6	0.03	16%	31 Jul →
vertigo	13–9	0.14	16%	31 Jul →
vertigo	10–13	-0.05	14%	31 Jul →
anubis	13–8	0.00	13%	29 Jul →
cache	9–13	0.05	27%	29 Jul →
inferno	4–1	-0.10	11%	29 Jul →
cache	3–13	-0.01	14%	28 Jul →
anubis	16–13	0.01	5%	28 Jul →
cache	15–15	-0.02	14%	28 Jul →
dust2	4–13	-0.06	20%	27 Jul →
mirage	15–15	0.02	23%	27 Jul →
inferno	9–13	-0.04	9%	27 Jul →
inferno	11–13	0.01	15%	26 Jul →
mirage	5–13	0.04	19%	24 Jul →
train	10–13	0.08	8%	24 Jul →
cache	5–13	0.16	23%	24 Jul →
anubis	8–13	-0.06	15%	24 Jul →
overpass	11–13	0.09	10%	24 Jul →
anubis	13–5	0.07	15%	23 Jul →
anubis	10–13	-0.05	5%	23 Jul →
ancient	15–15	0.01	13%	19 Jul →
dust2	13–10	0.05	13%	19 Jul →
cache	13–11	0.00	4%	19 Jul →
inferno	5–13	-0.01	8%	19 Jul →
anubis	11–13	0.00	16%	19 Jul →
inferno	13–9	-0.01	19%	19 Jul →
dust2	13–3	-0.00	15%	17 Jul →
dust2	13–3	-0.05	10%	17 Jul →
cache	5–13	-0.01	16%	17 Jul →
mirage	13–8	-0.05	15%	17 Jul →
cache	13–6	-0.05	14%	17 Jul →
cache	9–0	-0.01	14%	17 Jul →
mirage	11–13	-0.02	12%	17 Jul →
anubis	13–11	-0.06	6%	17 Jul →
anubis	5–13	-0.03	29%	16 Jul →
inferno	10–13	-0.03	24%	16 Jul →
inferno	15–15	0.02	14%	16 Jul →
nuke	8–13	-0.03	21%	16 Jul →
inferno	11–13	-0.00	11%	15 Jul →
inferno	13–7	-0.02	15%	15 Jul →
nuke	7–13	-0.10	18%	14 Jul →
mirage	13–10	0.05	9%	14 Jul →
ancient	8–13	-0.04	26%	13 Jul →
ancient	13–9	0.04	7%	13 Jul →
inferno	6–13	0.01	11%	13 Jul →
nuke	11–13	-0.05	22%	13 Jul →
office	13–10	0.03	16%	12 Jul →
office	3–13	0.03	19%	12 Jul →
mirage	13–8	0.17	19%	12 Jul →
dust2	3–0	0.21	55%	12 Jul →
mirage	8–13	0.04	28%	12 Jul →
dust2	13–9	-0.03	11%	11 Jul →
nuke	13–10	-0.05	33%	5 Jul →
ancient	11–13	-0.02	19%	5 Jul →
nuke	11–13	-0.04	25%	5 Jul →
cache	6–13	0.03	7%	4 Jul →
cache	6–13	0.07	16%	4 Jul →
overpass	11–13	0.09	11%	29 Jun →
mirage	9–13	0.04	16%	29 Jun →
nuke	14–16	-0.04	13%	24 Jun →
anubis	13–7	0.03	22%	24 Jun →
mirage	13–9	0.01	11%	23 Jun →
train	13–2	0.07	6%	19 Jun →
train	7–13	0.08	20%	19 Jun →
nuke	11–13	-0.04	11%	9 Jun →
overpass	8–13	-0.04	19%	9 Jun →
dust2	13–9	0.02	28%	9 Jun →
ancient	13–9	-0.00	15%	8 Jun →
inferno	13–5	0.01	14%	8 Jun →
anubis	13–6	-0.10	10%	8 Jun →
anubis	11–13	-0.05	8%	7 Jun →
inferno	16–14	-0.06	4%	7 Jun →