Mullink — CS2 Stats

76561198136081236[U:1:175815508]

584Tracked matches62%Win rate2023Tracked since

CSDB Rating5.0 DevelopingClutch Specialist

Ladder ranks via Leetify

Performance scores

Aim52

Positioning45

Utility28

0–100 skill scores via Leetify.

Recent form

STEADY47–46–7Last 10047%Win rateLWLLLWWWLW

Last 10 vs previous 10: -30pp win rate · -0.01 avg rating

Player DNA

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

Aim5.2

Aggression3.3

Utility2.8

Positioning4.5

Opening Duels0.5

Clutch10.0

Limited utility dependenceReliable 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 76% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

Where you differ: lower utility contribution; 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. 625ms 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

Positioning4.5

Utility2.8

Mechanics7.3

Opening Duels0.8

Win Impact9.0

Composite 5.0/10 (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+0.02

first ⅓ avg -0.02 → last ⅓ avg -0.00

Reaction time628ms+25ms

first ⅓ avg 603ms → last ⅓ avg 628ms

Headshot accuracy8.3%−1.3%

first ⅓ avg 9.6% → last ⅓ avg 8.3%

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

0.09Best rating — dust2 13–6

13–1Biggest win — anubis

5Longest win streak

12–8In matches decided by ≤2 rounds

14Overtime games

Map breakdown

nukeBest map · 63% over 8dust2Weakest map · 32% over 25

Map	Grade	Played	Record	Win rate	Avg rating
dust2	D	25	8–17	32%	-0.01
ancient	A	14	8–6	57%	0.00
anubis	A	11	6–5	55%	0.01
nuke	A	8	5–3	63%	-0.00
inferno	B	8	4–4	50%	-0.02
train	C	7	3–4	43%	-0.03
mirage	B	6	3–3	50%	-0.02
vertigo	C	5	2–3	40%	-0.03
office	—	4	2–2	50%	-0.06
jura	—	3	1–2	33%	-0.03
grail	—	3	1–2	33%	0.03
thera	—	3	2–1	67%	-0.02
overpass	—	2	1–1	50%	0.05
agency	—	1	1–0	100%	-0.02

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (32% over 25). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

2Matches

50%Win rate

0.64Avg K/D

72.3ADR

26%Headshot %

Clutches & streaks

100%1v1 clutch win

0%1v2 clutch win

1Longest win streak

Recent Faceit resultsLLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Anubis	1	100%	0.50	9.0
Train	1	0%	0.78	14.0

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.

8.2%Headshot accuracy

35.8%Accuracy (enemy spotted)

38.2%Spray accuracy

82.7%Counter-strafing

11.9°Preaim

625msReaction time

27.1%T opening success

36.6%CT opening success

0.46Enemies flashed / flash

3.3%Flash assists

2.34HE damage / grenade

3.94Flashes / 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 8.2431% — below the 15% mark we flag
Aim Training →
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 0.4555 — below the 0.5 mark we flag
Grenade Lineups →
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 27.1087% — below the 40% mark we flag

Spend your practice time on Dust 2

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

32% win rate across 25 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
overpass	11–13	0.05	6%	30 Oct →
nuke	13–5	0.04	5%	24 Oct →
train	6–13	-0.04	0%	22 Oct →
train	4–13	-0.06	4%	22 Oct →
dust2	11–13	0.03	15%	19 Oct →
mirage	16–13	0.00	12%	12 Jul →
ancient	13–10	0.00	10%	12 Jul →
ancient	13–10	0.05	6%	11 Jul →
dust2	5–13	0.01	11%	11 Jul →
dust2	13–10	-0.04	9%	11 Jul →
train	13–9	-0.03	5%	11 Jul →
dust2	13–6	0.09	8%	10 Jul →
vertigo	5–13	-0.06	9%	10 Jul →
overpass	13–10	0.04	9%	10 Jul →
inferno	13–11	0.03	11%	9 Jul →
ancient	15–15	0.01	6%	9 Jul →
anubis	13–9	0.06	9%	9 Jul →
dust2	13–7	-0.05	9%	8 Jul →
office	13–11	0.01	4%	8 Jul →
nuke	16–14	0.02	6%	5 Jul →
ancient	13–11	0.03	11%	5 Jul →
dust2	5–13	-0.05	4%	5 Jul →
vertigo	13–7	-0.01	22%	5 Jul →
mirage	4–13	-0.03	5%	1 Jul →
dust2	6–13	0.02	9%	1 Jul →
dust2	6–13	-0.08	14%	1 Jul →
anubis	13–5	0.02	7%	1 Jul →
dust2	16–13	-0.03	4%	29 Jun →
ancient	3–13	-0.04	11%	29 Jun →
anubis	16–14	-0.04	10%	29 Jun →
train	9–13	-0.04	11%	28 Jun →
jura	9–13	0.03	8%	27 Jun →
office	13–10	-0.07	8%	27 Jun →
train	13–7	-0.05	7%	27 Jun →
ancient	8–0	0.05	8%	26 Jun →
dust2	13–3	0.09	14%	26 Jun →
nuke	15–15	-0.02	5%	26 Jun →
mirage	13–5	-0.03	13%	25 Jun →
inferno	11–13	-0.02	9%	25 Jun →
ancient	16–14	0.05	8%	22 Jun →
dust2	9–13	-0.02	7%	22 Jun →
train	16–14	0.06	8%	22 Jun →
anubis	13–1	0.07	2%	22 Jun →
inferno	13–8	-0.08	5%	21 Jun →
grail	13–8	0.06	14%	19 Jun →
dust2	5–13	-0.05	16%	18 Jun →
mirage	7–13	-0.02	7%	18 Jun →
anubis	11–13	-0.01	8%	18 Jun →
nuke	13–6	0.00	19%	18 Jun →
agency	13–3	-0.02	13%	12 Jun →
vertigo	13–8	0.00	12%	12 Jun →
vertigo	1–13	-0.06	6%	10 Jun →
inferno	15–15	-0.06	5%	5 Jun →
ancient	14–16	-0.03	9%	4 Jun →
nuke	13–10	0.01	8%	4 Jun →
dust2	7–13	-0.01	11%	4 Jun →
grail	5–13	0.02	8%	3 Jun →
anubis	13–10	-0.01	9%	3 Jun →
dust2	13–8	0.03	10%	2 Jun →
dust2	4–13	-0.02	9%	2 Jun →
dust2	5–13	-0.01	14%	30 May →
dust2	4–13	-0.04	24%	30 May →
mirage	13–11	-0.02	13%	27 May →
inferno	11–13	-0.02	8%	27 May →
anubis	10–13	-0.00	9%	27 May →
dust2	9–13	-0.03	6%	27 May →
mirage	10–13	-0.03	13%	27 May →
dust2	15–15	-0.00	13%	26 May →
nuke	11–13	-0.07	6%	26 May →
jura	13–11	-0.06	5%	26 May →
ancient	1–13	-0.05	3%	25 May →
ancient	13–11	-0.02	8%	25 May →
nuke	13–11	0.02	8%	25 May →
train	15–15	-0.03	12%	25 May →
anubis	8–13	-0.02	9%	25 May →
ancient	5–13	-0.01	8%	24 May →
dust2	13–4	0.01	15%	24 May →
grail	7–13	0.01	20%	23 May →
jura	8–13	-0.06	7%	23 May →
dust2	9–13	-0.01	6%	24 Apr →
dust2	13–11	-0.05	8%	24 Apr →
inferno	13–9	-0.04	5%	23 Apr →
inferno	13–9	-0.01	12%	17 Apr →
ancient	16–13	-0.00	6%	16 Apr →
ancient	13–4	0.01	11%	13 Apr →
dust2	8–13	0.03	9%	13 Apr →
anubis	9–13	-0.03	14%	13 Apr →
vertigo	11–13	0.00	8%	11 Apr →
nuke	7–13	-0.01	10%	11 Apr →
ancient	15–15	0.00	21%	9 Mar →
dust2	6–13	-0.01	15%	9 Mar →
office	4–13	-0.04	10%	2 Feb →
dust2	9–13	-0.08	8%	18 Sept →
anubis	12–12	0.03	9%	10 Sept →
thera	13–8	0.02	7%	10 Sept →
inferno	8–13	0.00	9%	10 Sept →
thera	13–6	-0.01	8%	8 Sept →
anubis	13–8	0.04	7%	8 Sept →
office	2–13	-0.16	8%	7 Aug →
thera	6–13	-0.08	10%	7 Aug →