lekker slaapies — CS2 Stats

ZA76561199100057227[U:1:1139791499]Steam profile ↗✓ No bans

1,425Tracked matches73%Win rate2020Tracked since

1,231Hours in CS

CSDB Rating6.9 SolidAggressive Rifler

Premier CS Rating26,484Top 25% of 819 CSDB-tracked playersRed band · top ~2.3% of ranked players (population est.)

CSDB Leaderboard#1018 of 11954 tracked

Ladder ranks via Leetify

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Performance scores

Aim87

Positioning54

Utility41

0–100 skill scores via Leetify.

Recent form

STEADY68–31–1Last 10068%Win rateWWLWLLWWLW

Last 10 vs previous 10: -10pp win rate · -0.03 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim8.7

Aggression6.5

Utility4.1

Positioning5.4

Opening Duels3.5

Clutch1.2

Sharp aimerStrong CT-side openerLimited utility dependence

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 ropz 91% playstyle similarity

Most alike: positioning profile, opening-fight frequency.

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

Strengths

Aim. Aim score of 87 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 33 points — deaths here waste a strong aim profile.

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 53% on CT to 35% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim8.7

Positioning5.4

Utility4.1

Mechanics6.3

Opening Duels3.5

Win Impact10.0

Composite 6.9/10 (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 rating0.01−0.02

first ⅓ avg 0.03 → last ⅓ avg 0.01

Reaction time543ms−61ms

first ⅓ avg 603ms → last ⅓ avg 543ms

Headshot accuracy31.6%−2.2%

first ⅓ avg 33.8% → last ⅓ avg 31.6%

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 — cache 13–4

13–0Biggest win — mirage

11Longest win streak

W2Current streak

9Overtime games

Map breakdown

ancientBest map · 86% over 7anubisWeakest map · 50% over 10

Map	Grade	Played	Record	Win rate	Avg rating
mirage	A	34	20–14	59%	0.02
dust2	S	18	14–4	78%	0.02
inferno	S	17	12–5	71%	0.03
anubis	B	10	5–5	50%	0.01
cache	S	8	6–2	75%	0.05
ancient	S	7	6–1	86%	0.04
nuke	S	6	5–1	83%	0.03

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (50% over 10). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

46,559Lifetime kills

1.21K/D · Top 25% of tracked players

1,963Matches

54.0%Match win rate · Top 10% of tracked players

60.6%Headshot % · Top 10% of tracked players

10.0%Shot accuracy

6,302MVPs

1,231Hours (in match)

2,002Bombs planted

938Bombs defused

Most-used weapons

AK-4719,099

M4A4 / M4A1-S6,369

AWP5,574

Desert Eagle5,514

P2000 / USP-S3,046

Glock-181,730

SSG 081,228

Galil AR693

FAMAS630

MP9358

Lifetime map wins

3,922inferno

2,634dust2

1,121nuke

1,058vertigo

360train

24cbble

18lake

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

Faceit stats

Combat

132Matches

54%Win rate

1.11Avg K/D

79.0ADR

63%Headshot %

Clutches & streaks

26%1v1 clutch win

17%1v2 clutch win

9Longest win streak

Recent Faceit resultsLLWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	27	63%	1.07	18.3
Anubis	13	38%	1.34	15.2
Ancient	10	40%	1.08	18.5
Cache	10	70%	1.25	19.7
Dust2	6	50%	0.96	16.0
Inferno	2	0%	1.25	19.5
Nuke	2	100%	0.96	12.5
Overpass	1	100%	1.27	28.0

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.

31.4%Headshot accuracy

31.7%Accuracy (enemy spotted)

36.8%Spray accuracy

78.2%Counter-strafing

7.5°Preaim

547msReaction time

35.2%T opening success

52.8%CT opening success

0.61Enemies flashed / flash

11.3%Flash assists

6.54HE damage / grenade

4.61Flashes / 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 35.2019% — below the 40% mark we flag

Recent matches

Map	Score	Rating	HS%	Date
nuke	13–6	0.05	33%	23 Aug →
inferno	13–11	0.07	21%	23 Aug →
anubis	5–13	-0.11	19%	23 Aug →
inferno	13–9	0.03	30%	20 Aug →
dust2	5–13	-0.00	36%	20 Aug →
anubis	3–13	-0.01	32%	19 Aug →
anubis	13–8	0.01	26%	7 Aug →
anubis	13–8	0.09	39%	7 Aug →
dust2	5–13	0.00	40%	31 Jul →
ancient	16–13	-0.02	22%	31 Jul →
mirage	13–10	0.02	22%	29 Jul →
dust2	13–7	0.02	14%	29 Jul →
inferno	16–12	0.08	35%	28 Jul →
mirage	13–1	0.05	56%	28 Jul →
mirage	6–13	0.01	28%	24 Jul →
dust2	3–13	-0.08	14%	24 Jul →
inferno	13–7	0.12	42%	24 Jul →
mirage	13–11	0.14	41%	24 Jul →
nuke	7–13	0.04	27%	23 Jul →
mirage	16–12	0.02	49%	23 Jul →
ancient	13–3	0.05	30%	23 Jul →
nuke	13–6	-0.03	24%	23 Jul →
mirage	16–12	-0.02	16%	23 Jul →
mirage	10–13	-0.00	42%	22 Jul →
inferno	13–8	0.07	24%	22 Jul →
inferno	13–4	-0.02	50%	22 Jul →
dust2	13–10	0.04	32%	22 Jul →
inferno	13–1	-0.06	29%	22 Jul →
nuke	13–3	-0.01	50%	21 Jul →
dust2	13–8	-0.08	33%	21 Jul →
dust2	13–3	-0.01	43%	21 Jul →
dust2	3–0	-0.10	0%	21 Jul →
dust2	11–0	-0.01	46%	21 Jul →
mirage	13–0	-0.00	22%	20 Jul →
dust2	13–4	0.06	38%	20 Jul →
inferno	3–13	-0.07	27%	20 Jul →
mirage	6–13	-0.02	28%	20 Jul →
cache	8–13	-0.02	26%	20 Jul →
mirage	13–10	-0.01	25%	20 Jul →
inferno	12–16	0.03	43%	20 Jul →
anubis	13–8	-0.03	16%	20 Jul →
anubis	10–13	0.00	20%	19 Jul →
mirage	8–13	0.06	29%	19 Jul →
dust2	13–7	0.05	25%	19 Jul →
mirage	13–8	0.01	30%	19 Jul →
mirage	13–10	0.05	35%	19 Jul →
inferno	13–8	0.11	28%	19 Jul →
mirage	7–13	0.00	35%	19 Jul →
inferno	15–15	0.01	25%	19 Jul →
dust2	13–10	0.04	25%	19 Jul →
mirage	13–10	-0.02	27%	19 Jul →
ancient	13–8	0.02	38%	18 Jul →
mirage	13–8	-0.01	38%	18 Jul →
inferno	13–6	0.01	33%	18 Jul →
dust2	13–8	0.02	21%	18 Jul →
ancient	13–6	0.06	41%	18 Jul →
inferno	10–13	-0.01	23%	18 Jul →
ancient	13–8	0.14	42%	18 Jul →
dust2	13–8	0.12	21%	18 Jul →
nuke	13–9	0.14	30%	18 Jul →
mirage	13–8	0.11	37%	18 Jul →
dust2	9–13	0.09	28%	18 Jul →
nuke	13–5	-0.01	24%	17 Jul →
mirage	9–13	-0.03	25%	17 Jul →
inferno	13–3	0.05	38%	10 Jul →
mirage	13–1	0.03	27%	10 Jul →
anubis	13–1	0.06	33%	9 Jul →
cache	13–9	-0.01	22%	9 Jul →
mirage	13–3	0.07	32%	9 Jul →
mirage	13–1	0.07	14%	9 Jul →
dust2	13–10	-0.01	33%	9 Jul →
mirage	12–16	-0.05	26%	9 Jul →
dust2	13–4	0.02	32%	9 Jul →
mirage	0–13	-0.07	32%	9 Jul →
inferno	6–13	-0.06	29%	9 Jul →
mirage	6–13	0.01	23%	9 Jul →
cache	13–10	-0.02	17%	9 Jul →
mirage	13–10	0.07	27%	9 Jul →
cache	13–4	0.14	40%	9 Jul →
dust2	13–1	0.11	45%	9 Jul →
mirage	6–13	0.07	33%	9 Jul →
mirage	5–13	-0.06	27%	8 Jul →
mirage	13–2	-0.01	19%	8 Jul →
mirage	7–13	-0.03	33%	8 Jul →
cache	11–13	0.11	38%	8 Jul →
anubis	8–13	-0.01	25%	8 Jul →
inferno	13–3	0.10	32%	8 Jul →
ancient	7–13	-0.03	44%	8 Jul →
inferno	13–10	0.05	58%	8 Jul →
mirage	4–13	-0.07	42%	8 Jul →
cache	13–7	0.02	34%	8 Jul →
cache	13–3	0.09	47%	7 Jul →
cache	13–11	0.05	36%	7 Jul →
mirage	13–10	0.04	27%	7 Jul →
mirage	13–3	0.12	40%	7 Jul →
mirage	13–8	0.05	53%	7 Jul →
anubis	13–7	0.10	35%	6 Jul →
ancient	13–4	0.07	31%	6 Jul →
anubis	12–16	0.04	41%	6 Jul →
mirage	12–16	0.01	49%	5 Jul →