MösenMöger — CS2 Stats

76561198986894619[U:1:1026628891]Steam profile ↗✓ No bans

573Tracked matches45%Win rate2020Tracked since

CSDB Rating3.9 LearningClutch Specialist

Premier CS Rating12,737Blue band · top ~40.4% of ranked players (population est.)

Ladder ranks via Leetify

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Performance scores

Aim52

Positioning35

Utility54

0–100 skill scores via Leetify.

Recent form

STEADY40–59–1Last 10040%Win rateLWWWLWLLLL

Last 10 vs previous 10: -10pp win rate · -0.01 avg rating

Player DNA

Primary style: Clutch Specialist — Late-round 1vX conversion well above par.

Aim5.2

Aggression1.8

Utility5.4

Positioning3.5

Opening Duels0.0

Clutch10.0

Reliable in 1v1s

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

Plays most like NiKo 71% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-fight frequency; 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. 595ms 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

Aim5.2

Positioning3.5

Utility5.4

Mechanics4.7

Opening Duels0.0

Win Impact3.3

Composite 3.9/10 (Learning), 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-0.01+0.00

first ⅓ avg -0.02 → last ⅓ avg -0.01

Reaction time595ms−2ms

first ⅓ avg 598ms → last ⅓ avg 595ms

Headshot accuracy12.5%+0.5%

first ⅓ avg 12.0% → last ⅓ avg 12.5%

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.

Highlights

0.08Best rating — dust2 13–8

13–1Biggest win — mirage

6Longest win streak

9–3In matches decided by ≤2 rounds

10Overtime games

Map breakdown

nukeBest map · 57% over 7ancientWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
mirage	D	34	11–23	32%	-0.03
dust2	B	24	13–11	54%	-0.01
inferno	C	16	7–9	44%	-0.01
nuke	A	7	4–3	57%	-0.00
cache	D	7	2–5	29%	-0.04
ancient	D	6	1–5	17%	-0.02
overpass	—	2	0–2	0%	0.02
boulder	—	1	0–1	0%	-0.02
vertigo	—	1	0–1	0%	0.00
anubis	—	1	1–0	100%	0.00
train	—	1	1–0	100%	0.03

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

10Matches

60%Win rate

1.13Avg K/D

83.7ADR

36%Headshot %

Clutches & streaks

75%1v1 clutch win

20%1v2 clutch win

4Longest win streak

Recent Faceit resultsWWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	5	60%	1.28	13.8
Inferno	2	50%	0.58	12.0
Anubis	1	0%	1.11	20.0
Ancient	1	100%	1.19	19.0
Dust2	1	100%	1.43	20.0

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.

13.3%Headshot accuracy

33.2%Accuracy (enemy spotted)

37.2%Spray accuracy

71.1%Counter-strafing

10.4°Preaim

595msReaction time

27.2%T opening success

17.9%CT opening success

0.51Enemies flashed / flash

4.6%Flash assists

9.93HE damage / grenade

9.62Flashes / 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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 13.328% — below the 15% mark we flag
Aim Training →
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 27.2004% — below the 40% mark we flag

Spend your practice time on Ancient

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

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	2–13	-0.08	10%	25 Aug →
dust2	13–8	0.02	13%	25 Aug →
mirage	16–14	-0.05	15%	25 Aug →
mirage	13–7	-0.01	5%	25 Aug →
inferno	7–13	-0.13	5%	24 Aug →
dust2	13–5	0.02	8%	24 Aug →
ancient	3–13	-0.05	7%	17 Aug →
ancient	7–13	0.01	8%	13 Aug →
mirage	3–13	0.00	17%	13 Aug →
boulder	7–13	-0.02	17%	13 Aug →
mirage	2–13	-0.03	11%	13 Aug →
ancient	13–6	-0.02	12%	6 Aug →
inferno	13–5	-0.05	17%	6 Aug →
dust2	7–13	-0.02	14%	27 Jul →
inferno	13–10	-0.05	11%	27 Jul →
nuke	16–14	0.06	15%	27 Jul →
inferno	12–16	0.00	13%	27 Jul →
ancient	10–13	-0.03	8%	27 Jul →
mirage	9–13	-0.03	15%	23 Jul →
mirage	13–2	-0.02	23%	23 Jul →
dust2	13–8	0.08	18%	23 Jul →
dust2	13–7	-0.04	15%	23 Jul →
dust2	9–13	-0.03	20%	23 Jul →
mirage	13–3	0.04	13%	23 Jul →
mirage	7–13	-0.04	6%	22 Jul →
dust2	13–6	0.06	14%	22 Jul →
nuke	8–13	-0.02	4%	22 Jul →
mirage	3–13	-0.03	8%	22 Jul →
mirage	11–13	0.03	18%	21 Jul →
mirage	15–15	-0.06	29%	21 Jul →
inferno	2–13	-0.01	12%	13 Jul →
mirage	13–6	0.04	3%	13 Jul →
inferno	11–13	-0.02	7%	13 Jul →
dust2	16–14	-0.04	11%	8 Jul →
mirage	1–13	-0.03	7%	8 Jul →
dust2	13–11	-0.02	24%	8 Jul →
vertigo	7–13	0.00	10%	8 Jul →
cache	5–13	-0.01	10%	8 Jul →
overpass	10–13	0.03	16%	7 Jul →
mirage	8–13	0.03	10%	7 Jul →
cache	13–8	-0.04	6%	7 Jul →
mirage	4–13	-0.10	9%	24 Jun →
inferno	13–8	0.02	21%	22 Jun →
mirage	8–13	-0.02	17%	22 Jun →
inferno	10–13	0.01	20%	22 Jun →
cache	10–13	-0.05	10%	22 Jun →
cache	9–13	-0.08	11%	14 May →
cache	8–13	-0.05	13%	14 May →
cache	7–13	-0.05	10%	14 May →
dust2	10–13	-0.04	10%	13 May →
nuke	6–13	-0.05	2%	12 May →
mirage	2–13	-0.10	17%	4 May →
ancient	13–16	-0.03	5%	4 May →
mirage	13–9	-0.05	13%	4 May →
dust2	3–13	-0.08	14%	4 May →
dust2	13–9	0.05	18%	4 May →
inferno	13–10	0.04	6%	4 May →
cache	13–6	-0.01	11%	4 May →
anubis	13–9	0.00	8%	22 Apr →
mirage	3–13	-0.04	13%	22 Apr →
dust2	13–4	0.01	18%	22 Apr →
mirage	13–11	-0.03	15%	21 Apr →
mirage	13–10	-0.05	21%	21 Apr →
inferno	16–14	0.02	13%	21 Apr →
dust2	10–13	0.01	16%	9 Apr →
mirage	2–13	-0.12	14%	9 Apr →
mirage	10–13	-0.06	12%	9 Apr →
nuke	7–13	-0.04	9%	9 Apr →
ancient	9–13	0.00	10%	2 Apr →
dust2	13–8	-0.00	11%	2 Apr →
mirage	10–13	-0.03	10%	2 Apr →
mirage	10–13	-0.09	0%	2 Apr →
dust2	4–13	-0.07	23%	2 Apr →
dust2	7–13	-0.01	27%	2 Apr →
mirage	8–13	-0.05	13%	2 Apr →
dust2	4–13	-0.01	8%	2 Apr →
mirage	13–5	-0.06	13%	1 Apr →
dust2	16–14	-0.06	13%	31 Mar →
inferno	13–7	-0.07	5%	29 Mar →
dust2	13–11	-0.03	14%	26 Mar →
nuke	16–14	0.01	7%	26 Mar →
mirage	13–1	-0.01	14%	26 Mar →
mirage	10–13	-0.02	8%	25 Mar →
nuke	13–7	0.00	15%	25 Mar →
mirage	7–13	-0.05	3%	25 Mar →
mirage	13–5	0.06	16%	25 Mar →
inferno	10–13	0.03	5%	25 Mar →
dust2	4–13	0.04	12%	24 Mar →
mirage	9–13	-0.03	11%	23 Mar →
dust2	7–13	-0.06	8%	19 Mar →
inferno	6–13	0.01	2%	19 Mar →
mirage	3–13	-0.08	14%	19 Mar →
mirage	1–13	-0.07	30%	19 Mar →
inferno	13–5	0.08	19%	30 Oct →
dust2	13–6	0.04	20%	27 Sept →
overpass	8–13	0.00	15%	27 Sept →
inferno	9–13	-0.06	9%	27 Sept →
nuke	13–5	0.02	9%	25 Sept →
train	13–6	0.03	9%	25 Sept →
inferno	14–16	0.01	14%	25 Sept →