LeeVanCleef — CS2 Stats

76561197960467147[U:1:201419]Steam profile ↗✓ No bans

2,051Tracked matches45%Win rate2021Tracked since

CSDB Rating3.8 Learning

Premier CS Rating9,893Light Blue band · top ~55.4% of ranked players (population est.)

CSDB Leaderboard#42715 of 59278 tracked

FaceitLevel 3Top 90.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim48

Positioning48

Utility48

0–100 skill scores via Leetify.

Recent form

STEADY42–54–4Last 10042%Win rateLWLLWWLLLW

Last 10 vs previous 10: -10pp win rate · -0.05 avg rating

Player DNA

Aim4.8

Aggression5.8

Utility4.8

Positioning4.8

Opening Duels1.6

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 b1t 83% 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 50% on CT to 22% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 606ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 66% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim4.8

Positioning4.8

Utility4.8

Mechanics3.6

Opening Duels2.6

Win Impact3.3

Composite 3.8/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01+0.01

first ⅓ avg -0.02 → last ⅓ avg -0.01

Reaction time604ms−67ms

first ⅓ avg 671ms → last ⅓ avg 604ms

Headshot accuracy10.4%−4.2%

first ⅓ avg 14.6% → last ⅓ avg 10.4%

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

0.12Best rating — cache 13–2

13–2Biggest win — dust2

5Longest win streak

6–8In matches decided by ≤2 rounds

14Overtime games

Map breakdown

nukeBest map · 60% over 10cacheWeakest map · 22% over 9

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	29	15–14	52%	-0.01
anubis	D	18	5–13	28%	-0.01
ancient	C	15	6–9	40%	-0.02
nuke	A	10	6–4	60%	-0.01
dust2	B	10	5–5	50%	-0.01
cache	D	9	2–7	22%	0.00
overpass	A	5	3–2	60%	-0.03
mirage	—	4	0–4	0%	-0.04

Across the last 100 tracked matches.

Faceit stats

Combat

22Matches

41%Win rate

0.82Avg K/D

—ADR

38%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

4Longest win streak

Recent Faceit resultsWWLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	5	60%	1.01	13.6
Mirage	5	60%	1.07	11.6
Overpass	3	67%	0.63	9.7
Ancient	3	33%	0.95	15.0
Vertigo	2	0%	0.72	9.0
Anubis	2	0%	0.68	16.0

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.

10.9%Headshot accuracy

36.5%Accuracy (enemy spotted)

38.0%Spray accuracy

66.1%Counter-strafing

10.9°Preaim

606msReaction time

22.2%T opening success

50.5%CT opening success

0.55Enemies flashed / flash

4.1%Flash assists

12.42HE damage / grenade

4.29Flashes / 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 10.8718% — 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 22.1531% — below the 40% mark we flag

Spend your practice time on Cache

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

22% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
anubis	9–13	-0.04	12%	14 Aug →
cache	13–9	-0.06	10%	14 Aug →
cache	4–13	-0.02	10%	9 Aug →
ancient	8–13	-0.04	8%	9 Aug →
nuke	13–9	0.00	6%	9 Aug →
dust2	13–2	-0.02	15%	9 Aug →
inferno	8–13	-0.06	6%	9 Aug →
anubis	5–13	-0.03	19%	7 Aug →
dust2	10–13	0.04	16%	7 Aug →
inferno	13–9	0.00	17%	7 Aug →
anubis	7–13	0.01	10%	5 Aug →
cache	13–2	0.12	15%	5 Aug →
inferno	13–11	0.01	8%	5 Aug →
ancient	6–13	-0.00	6%	5 Aug →
nuke	13–6	0.02	9%	4 Aug →
ancient	13–9	0.03	15%	4 Aug →
anubis	10–13	-0.01	13%	4 Aug →
cache	7–13	0.02	6%	4 Aug →
inferno	11–13	0.04	19%	25 Jul →
anubis	13–10	0.03	12%	25 Jul →
cache	5–13	-0.03	14%	25 Jul →
inferno	11–13	0.04	11%	25 Jul →
ancient	13–6	0.01	10%	25 Jul →
inferno	16–13	-0.00	11%	24 Jul →
inferno	7–13	-0.03	11%	24 Jul →
nuke	13–6	-0.02	4%	24 Jul →
cache	10–13	0.01	3%	24 Jul →
mirage	15–15	-0.04	5%	4 Jul →
ancient	3–13	-0.07	15%	4 Jul →
dust2	13–11	-0.04	16%	4 Jul →
anubis	2–13	-0.00	0%	3 Jul →
ancient	9–13	-0.07	5%	13 Jun →
inferno	7–13	-0.02	8%	13 Jun →
overpass	5–13	-0.05	3%	11 Jun →
nuke	13–10	-0.01	4%	11 Jun →
inferno	6–13	0.01	13%	11 Jun →
ancient	13–2	0.12	20%	11 Jun →
inferno	13–2	0.04	5%	10 Jun →
inferno	16–13	-0.01	5%	10 Jun →
ancient	13–10	0.03	13%	10 Jun →
anubis	13–11	0.07	9%	10 Jun →
dust2	14–16	-0.01	17%	10 Jun →
ancient	8–13	0.01	12%	10 Jun →
cache	6–13	0.00	19%	10 Jun →
nuke	10–13	-0.05	3%	9 Jun →
anubis	15–15	-0.00	4%	9 Jun →
inferno	10–13	0.02	8%	9 Jun →
ancient	8–13	-0.04	15%	8 Jun →
anubis	11–13	0.03	10%	8 Jun →
cache	7–13	0.01	16%	7 May →
cache	5–13	-0.05	11%	7 May →
anubis	13–16	0.01	11%	24 Apr →
inferno	13–5	-0.01	6%	23 Apr →
dust2	13–10	-0.04	10%	23 Apr →
nuke	13–11	-0.04	2%	23 Apr →
anubis	13–10	-0.07	11%	11 Apr →
inferno	13–10	-0.02	19%	11 Apr →
mirage	8–13	-0.03	4%	10 Apr →
inferno	16–14	-0.07	9%	10 Apr →
ancient	11–13	-0.04	4%	1 Apr →
nuke	13–6	0.05	14%	1 Apr →
mirage	7–13	-0.07	13%	30 Mar →
anubis	7–13	-0.08	5%	29 Mar →
dust2	13–16	-0.07	12%	29 Mar →
inferno	5–13	-0.03	7%	28 Mar →
inferno	13–11	-0.01	22%	28 Mar →
inferno	16–13	-0.03	21%	28 Mar →
inferno	7–13	-0.00	23%	28 Mar →
ancient	9–13	-0.05	8%	15 Mar →
inferno	9–13	0.02	14%	15 Mar →
nuke	9–13	-0.06	25%	14 Mar →
ancient	16–13	-0.04	11%	14 Mar →
anubis	13–6	0.05	16%	14 Mar →
inferno	13–9	0.03	21%	14 Mar →
inferno	11–13	-0.04	16%	23 Feb →
overpass	13–10	-0.04	2%	23 Feb →
nuke	11–13	0.01	16%	23 Feb →
overpass	13–10	-0.05	22%	22 Feb →
anubis	10–13	-0.06	10%	22 Feb →
overpass	13–16	-0.04	15%	22 Feb →
dust2	13–3	0.05	30%	22 Feb →
dust2	11–13	-0.03	16%	15 Feb →
inferno	13–7	0.04	10%	15 Feb →
anubis	7–13	0.02	10%	14 Feb →
inferno	15–15	-0.04	16%	9 Feb →
inferno	13–10	-0.01	8%	9 Feb →
inferno	10–13	-0.01	12%	9 Feb →
ancient	13–10	-0.03	13%	9 Feb →
dust2	13–9	-0.01	8%	8 Feb →
overpass	13–3	0.02	6%	8 Feb →
nuke	2–13	-0.04	8%	8 Feb →
anubis	16–12	-0.02	16%	8 Feb →
anubis	8–13	-0.02	8%	8 Feb →
dust2	9–13	-0.03	13%	8 Feb →
ancient	6–13	-0.06	10%	7 Feb →
mirage	15–15	-0.02	20%	7 Feb →
inferno	13–7	-0.01	36%	1 Feb →
anubis	10–13	-0.06	7%	1 Feb →
inferno	13–7	-0.03	14%	1 Feb →
inferno	9–13	-0.07	24%	31 Jan →