Silux — CS2 Stats

LT76561198096206534[U:1:135940806]Steam profile ↗

1,815Tracked matches45%Win rate2023Tracked since

1,690Hours in CS15Hrs last 2 wks

CSDB Rating5.4 DevelopingSupport

Premier CS Rating18,614Purple band · top ~14% of ranked players (population est.)

CSDB Leaderboard#10555 of 20897 tracked

WingmanSilver Elite Master

Ladder ranks via Leetify

How this compares with the same rank

Median values for Pink band among CSDB-tracked players (n=201), 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	Pink band median	vs Pink band
Headshot rate	53.6%	48.1%	above
Shot accuracy	2.4%	12.9%	10.4% short
Kill/death ratio	0.89	1.08	0.20 short
Match win rate	41.6%	46.5%	4.9% short

This profile matches the typical Pink band player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Pink band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim65

Positioning42

Utility72

0–100 skill scores via Leetify.

Recent form

STEADY52–45–3Last 10052%Win rateLWLWWWWWLL

Last 10 vs previous 10: +30pp win rate · +0.02 avg rating

Player DNA

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

Aim6.5

Aggression3.3

Utility7.2

Positioning4.2

Opening Duels0.1

Clutch2.4

Effective flashes

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 82% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

Where you differ: lower positioning profile; 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. 649ms 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

Aim6.5

Positioning4.2

Utility7.2

Mechanics7.7

Opening Duels0.5

Win Impact3.3

Composite 5.4/10 (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-0.00−0.01

first ⅓ avg 0.01 → last ⅓ avg -0.00

Reaction time660ms−27ms

first ⅓ avg 687ms → last ⅓ avg 660ms

Headshot accuracy20.0%+0.2%

first ⅓ avg 19.8% → last ⅓ avg 20.0%

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

0.14Best rating — overpass 13–7

13–1Biggest win — anubis

5Longest win streak

9–3In matches decided by ≤2 rounds

11Overtime games

Map breakdown

dust2Best map · 67% over 15infernoWeakest map · 33% over 15

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	18	9–9	50%	0.01
anubis	B	15	8–7	53%	0.01
dust2	S	15	10–5	67%	0.01
inferno	D	15	5–10	33%	-0.01
nuke	S	12	8–4	67%	-0.01
mirage	B	11	5–6	45%	0.00
cache	C	5	2–3	40%	0.02
overpass	A	5	3–2	60%	0.04
train	—	1	0–1	0%	-0.09
alpine	—	1	0–1	0%	-0.06
vertigo	—	1	1–0	100%	0.03
office	—	1	1–0	100%	-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 15). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

40,535Lifetime kills

0.89K/D

2,350Matches

41.6%Match win rate

53.6%Headshot % · Top 25% of tracked players

2.4%Shot accuracy

4,591MVPs

902Hours (in match)

4,012Bombs planted

729Bombs defused

Most-used weapons

AK-4716,887

M4A4 / M4A1-S8,227

Desert Eagle3,707

P2000 / USP-S2,064

Glock-181,653

Galil AR1,581

FAMAS1,476

AWP718

MP7606

MAC-10448

Lifetime map wins

2,825inferno

2,803dust2

2,315nuke

1,411vertigo

437train

325office

29italy

6ar_shoots

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

Faceit stats

Combat

269Matches

53%Win rate

1.15Avg K/D

77.2ADR

48%Headshot %

Clutches & streaks

32%1v1 clutch win

22%1v2 clutch win

10Longest win streak

Recent Faceit resultsLWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	46	52%	1.15	15.4
Inferno	44	57%	1.19	14.4
Nuke	26	54%	1.07	14.7
Mirage	26	50%	1.22	14.5
Dust2	26	65%	1.18	17.1
Anubis	23	57%	1.38	16.8
Train	14	50%	1.10	16.4
Overpass	10	50%	1.06	14.7

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.

20.1%Headshot accuracy

32.1%Accuracy (enemy spotted)

32.8%Spray accuracy

84.7%Counter-strafing

9.3°Preaim

649msReaction time

26.2%T opening success

34.3%CT opening success

0.70Enemies flashed / flash

8.0%Flash assists

10.72HE damage / grenade

15.95Flashes / 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 26.2318% — 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.

33% win rate across 15 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
anubis	6–13	0.02	18%	24 Aug →
dust2	13–10	-0.03	27%	16 Aug →
mirage	6–13	-0.01	14%	16 Aug →
inferno	13–7	0.02	21%	12 Aug →
inferno	13–8	-0.00	16%	12 Aug →
nuke	16–13	0.02	7%	12 Aug →
ancient	13–2	0.04	22%	5 Aug →
ancient	13–9	0.01	25%	5 Aug →
cache	4–13	-0.02	19%	4 Aug →
anubis	3–13	-0.02	15%	4 Aug →
ancient	12–16	-0.02	21%	4 Aug →
dust2	13–7	0.04	19%	2 Aug →
ancient	10–13	-0.03	19%	2 Aug →
ancient	5–13	-0.05	18%	30 Jul →
cache	13–6	0.07	35%	30 Jul →
ancient	16–13	0.00	17%	30 Jul →
anubis	1–13	-0.06	21%	28 Jul →
inferno	8–13	-0.08	7%	26 Jul →
inferno	5–13	-0.03	23%	26 Jul →
dust2	15–15	-0.04	19%	26 Jul →
anubis	13–7	0.01	21%	24 Jul →
anubis	13–4	0.10	24%	24 Jul →
mirage	9–13	0.01	25%	24 Jul →
ancient	9–13	-0.03	18%	24 Jul →
inferno	8–13	-0.03	37%	23 Jul →
anubis	13–11	0.05	20%	23 Jul →
cache	13–6	0.08	24%	22 Jul →
anubis	13–16	-0.04	25%	22 Jul →
ancient	5–13	0.03	13%	21 Jul →
nuke	3–13	-0.05	18%	21 Jul →
inferno	6–13	-0.04	21%	21 Jul →
dust2	13–6	0.02	16%	20 Jul →
nuke	13–8	-0.03	16%	20 Jul →
nuke	13–3	0.06	17%	20 Jul →
anubis	13–11	0.04	26%	19 Jul →
ancient	11–13	0.01	30%	19 Jul →
mirage	15–15	0.05	16%	18 Jul →
nuke	13–7	-0.01	24%	17 Jul →
mirage	9–13	-0.06	11%	17 Jul →
cache	9–13	-0.03	16%	9 Jul →
mirage	13–10	0.04	14%	9 Jul →
train	7–13	-0.09	34%	8 Jul →
alpine	4–13	-0.06	56%	8 Jul →
vertigo	13–6	0.03	33%	8 Jul →
nuke	8–13	0.01	30%	8 Jul →
office	13–2	-0.04	30%	8 Jul →
nuke	13–11	-0.04	17%	6 Jul →
dust2	13–9	0.04	26%	6 Jul →
overpass	9–13	-0.03	27%	6 Jul →
inferno	10–13	0.01	30%	6 Jul →
inferno	11–13	-0.04	16%	5 Jul →
ancient	13–11	0.05	22%	5 Jul →
inferno	8–8	0.04	50%	5 Jul →
mirage	2–13	-0.01	14%	5 Jul →
inferno	16–14	0.01	21%	5 Jul →
mirage	16–13	0.07	26%	5 Jul →
dust2	8–13	-0.03	21%	5 Jul →
nuke	13–16	-0.03	14%	4 Jul →
dust2	13–6	0.02	17%	4 Jul →
inferno	2–13	-0.09	15%	4 Jul →
overpass	13–7	0.14	27%	4 Jul →
ancient	13–5	-0.01	27%	4 Jul →
dust2	4–13	-0.01	19%	3 Jul →
anubis	9–13	0.05	21%	3 Jul →
anubis	13–5	0.02	29%	27 Jun →
mirage	13–4	0.03	10%	27 Jun →
mirage	16–13	0.00	20%	27 Jun →
overpass	13–9	0.06	16%	27 Jun →
nuke	13–6	-0.03	28%	27 Jun →
anubis	4–13	-0.05	15%	27 Jun →
inferno	16–14	0.01	25%	27 Jun →
mirage	13–8	-0.04	14%	27 Jun →
ancient	13–4	-0.02	23%	26 Jun →
nuke	13–8	0.05	19%	26 Jun →
ancient	8–13	0.00	13%	26 Jun →
anubis	13–9	0.01	15%	24 Jun →
dust2	13–6	-0.02	21%	24 Jun →
dust2	13–9	-0.06	20%	24 Jun →
overpass	6–13	-0.05	13%	23 Jun →
anubis	8–13	-0.05	17%	23 Jun →
ancient	13–11	0.04	22%	23 Jun →
ancient	13–11	0.09	23%	21 Jun →
dust2	5–13	-0.01	24%	21 Jun →
ancient	4–13	-0.08	16%	21 Jun →
cache	4–13	0.01	14%	20 Jun →
inferno	8–13	-0.07	19%	20 Jun →
nuke	8–13	-0.02	13%	18 Jun →
dust2	13–11	0.01	24%	17 Jun →
inferno	13–2	0.06	25%	17 Jun →
anubis	13–10	0.08	19%	16 Jun →
dust2	13–2	0.09	16%	16 Jun →
dust2	11–13	0.04	25%	16 Jun →
dust2	13–5	0.04	28%	16 Jun →
inferno	8–13	0.03	21%	11 Jun →
ancient	13–10	0.14	19%	11 Jun →
overpass	13–10	0.06	23%	11 Jun →
anubis	13–1	0.02	19%	11 Jun →
nuke	13–5	-0.04	21%	11 Jun →
mirage	4–13	-0.05	17%	10 Jun →
ancient	10–13	0.04	25%	10 Jun →