Lassejunker — CS2 Stats

76561198039240071[U:1:78974343]

4,416Tracked matches50%Win rate2020Tracked since

CSDB Rating6.4 SolidSupport

Ladder ranks via Leetify

Performance scores

Aim74

Positioning53

Utility75

0–100 skill scores via Leetify.

Recent form

STEADY46–54Last 10046%Win rateLWLLWWLLLW

Last 10 vs previous 10: -10pp win rate · +0.02 avg rating

Player DNA

Primary style: Support — Utility contribution leads the profile while opening activity stays low.

Aim7.4

Aggression4.7

Utility7.5

Positioning5.3

Opening Duels1.8

Clutch3.2

Strong CT-side openerHigh utility contribution

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 92% playstyle similarity

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

Where you differ: 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

T-side openings. Opening success drops from 46% on CT to 29% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 613ms 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

Aim7.4

Positioning5.3

Utility7.5

Mechanics6.9

Opening Duels2.0

Win Impact5.0

Composite 6.4/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00+0.01

first ⅓ avg -0.00 → last ⅓ avg 0.00

Reaction time621ms−13ms

first ⅓ avg 634ms → last ⅓ avg 621ms

Headshot accuracy28.2%+0.9%

first ⅓ avg 27.4% → last ⅓ avg 28.2%

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

0.13Best rating — nuke 13–3

13–1Biggest win — overpass

6Longest win streak

6–6In matches decided by ≤2 rounds

10Overtime games

Map breakdown

ancientBest map · 60% over 5anubisWeakest map · 27% over 11

Map	Grade	Played	Record	Win rate	Avg rating
nuke	A	29	16–13	55%	0.01
inferno	B	29	14–15	48%	-0.00
overpass	C	15	6–9	40%	0.00
anubis	D	11	3–8	27%	-0.02
cache	C	7	3–4	43%	-0.00
ancient	A	5	3–2	60%	0.03
dust2	—	4	1–3	25%	-0.01

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (27% over 11). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

3,091Matches

51%Win rate

1.11Avg K/D

81.3ADR

56%Headshot %

Clutches & streaks

36%1v1 clutch win

21%1v2 clutch win

10Longest win streak

Recent Faceit resultsLWLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	516	55%	1.05	15.9
Nuke	375	52%	1.10	16.1
Ancient	332	53%	1.13	17.8
Anubis	293	46%	1.00	16.6
Overpass	153	50%	1.15	17.1
Train	144	49%	1.12	18.2
Vertigo	27	22%	1.10	16.0
Dust2	19	26%	0.82	14.1

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.

27.6%Headshot accuracy

34.4%Accuracy (enemy spotted)

38.1%Spray accuracy

80.9%Counter-strafing

11.8°Preaim

613msReaction time

28.5%T opening success

46.3%CT opening success

0.66Enemies flashed / flash

11.1%Flash assists

12.01HE damage / grenade

7.73Flashes / 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 28.5204% — below the 40% mark we flag

Spend your practice time on Anubis

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

27% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
anubis	10–13	-0.02	28%	14 Aug →
nuke	13–5	0.02	23%	14 Aug →
inferno	7–13	-0.01	26%	25 Jul →
dust2	8–13	-0.02	20%	25 Jul →
nuke	13–9	0.07	23%	19 Jul →
nuke	13–10	0.03	27%	19 Jul →
inferno	4–13	-0.07	33%	18 Jul →
nuke	14–16	0.00	25%	18 Jul →
inferno	11–13	0.01	25%	18 Jul →
nuke	13–8	0.01	22%	15 Jul →
cache	22–18	-0.02	23%	12 Jul →
cache	10–13	-0.03	28%	10 Jul →
inferno	8–13	0.00	25%	10 Jul →
inferno	16–14	-0.04	30%	5 Jul →
ancient	13–8	0.01	32%	5 Jul →
cache	7–13	-0.02	23%	28 Jun →
inferno	8–13	-0.04	21%	28 Jun →
ancient	16–13	0.08	29%	28 Jun →
nuke	16–12	-0.01	18%	28 Jun →
ancient	0–13	-0.06	18%	28 Jun →
nuke	6–13	-0.03	37%	23 Jun →
inferno	1–13	0.00	42%	23 Jun →
dust2	13–10	0.08	30%	23 Jun →
nuke	13–11	0.10	44%	23 Jun →
inferno	5–13	-0.06	24%	21 Jun →
dust2	10–13	-0.05	29%	21 Jun →
inferno	13–8	-0.01	35%	14 Jun →
cache	13–7	0.00	42%	12 Jun →
cache	13–7	0.07	31%	12 Jun →
inferno	13–8	0.01	23%	12 Jun →
overpass	13–4	0.08	35%	12 Jun →
ancient	13–2	0.11	38%	12 Jun →
dust2	5–13	-0.04	24%	12 Jun →
inferno	19–16	0.02	23%	30 May →
cache	5–13	0.01	33%	30 May →
overpass	13–1	0.09	28%	29 May →
cache	5–13	-0.04	28%	29 May →
nuke	6–13	-0.04	36%	29 May →
nuke	4–13	-0.02	28%	22 May →
inferno	13–9	0.02	30%	22 May →
nuke	13–6	0.04	27%	8 May →
nuke	13–9	-0.01	22%	1 May →
nuke	5–13	-0.03	19%	1 May →
overpass	5–13	-0.00	13%	28 Apr →
inferno	13–9	0.00	18%	28 Apr →
nuke	13–3	0.13	28%	28 Apr →
nuke	8–13	-0.03	26%	26 Apr →
anubis	7–13	-0.04	26%	26 Apr →
inferno	10–13	-0.01	23%	26 Apr →
nuke	13–16	0.02	34%	25 Apr →
inferno	13–8	0.03	14%	25 Apr →
overpass	3–13	-0.02	38%	25 Apr →
overpass	16–13	0.03	20%	25 Apr →
anubis	10–13	0.06	17%	25 Apr →
nuke	7–13	-0.05	26%	25 Apr →
nuke	13–10	0.04	35%	17 Apr →
nuke	13–9	0.09	28%	17 Apr →
nuke	13–9	0.01	33%	17 Apr →
nuke	11–13	-0.04	15%	13 Apr →
inferno	13–6	0.01	30%	11 Apr →
overpass	10–13	-0.03	23%	10 Apr →
overpass	13–9	-0.00	28%	10 Apr →
inferno	11–13	-0.01	16%	6 Apr →
inferno	11–13	-0.05	56%	6 Apr →
anubis	5–13	-0.04	22%	2 Apr →
overpass	4–13	-0.04	23%	2 Apr →
inferno	8–13	-0.01	27%	2 Apr →
nuke	13–8	0.04	44%	15 Mar →
anubis	7–13	-0.07	33%	15 Mar →
overpass	13–11	0.03	19%	15 Mar →
anubis	9–13	-0.03	24%	15 Mar →
inferno	6–13	-0.04	28%	14 Mar →
anubis	10–13	-0.02	26%	14 Mar →
anubis	13–9	-0.01	21%	14 Mar →
overpass	10–13	-0.01	30%	14 Mar →
nuke	4–13	-0.02	15%	13 Mar →
inferno	13–5	0.04	35%	13 Mar →
nuke	13–7	0.00	29%	8 Mar →
inferno	13–8	0.05	29%	7 Mar →
overpass	10–13	-0.05	27%	7 Mar →
inferno	8–13	0.07	29%	1 Mar →
overpass	12–16	-0.04	25%	1 Mar →
nuke	13–10	-0.04	26%	1 Mar →
overpass	8–13	-0.01	44%	1 Mar →
overpass	13–11	-0.02	29%	28 Feb →
overpass	11–13	0.01	20%	28 Feb →
inferno	13–11	-0.00	25%	28 Feb →
inferno	8–13	0.02	46%	26 Feb →
nuke	4–13	-0.07	19%	26 Feb →
nuke	1–13	-0.06	30%	26 Feb →
inferno	8–13	-0.10	23%	20 Feb →
inferno	13–4	0.05	27%	20 Feb →
nuke	13–7	0.03	20%	20 Feb →
nuke	15–19	-0.00	26%	15 Feb →
anubis	13–9	0.02	29%	15 Feb →
inferno	13–5	0.10	20%	14 Feb →
inferno	13–11	-0.04	19%	14 Feb →
anubis	13–10	0.04	23%	14 Feb →
anubis	5–13	-0.04	43%	14 Feb →
ancient	10–13	0.01	21%	14 Feb →