sleazley𝔰 — CS2 Stats

76561198103622569[U:1:143356841]Steam profile ↗✓ No bans

959Tracked matches46%Win rate2020Tracked since

CSDB Rating3.6 LearningSupport

WingmanGold Nova I

Ladder ranks via Leetify

Performance scores

Aim21

Positioning42

Utility47

0–100 skill scores via Leetify.

Recent form

COLD41–50–9Last 10041%Win rateTTWLLWLLWL

Last 10 vs previous 10: −10pp win rate · +0.02 avg rating · +0.4pp headshot accuracy · −5ms reaction

Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

1–2–2 · 20% win rate
Avg rating -0.03
Avg headshot accuracy 14%
Avg reaction 669ms

Last 10

3–5–2 · 30% win rate
Avg rating -0.03
Avg headshot accuracy 12%
Avg reaction 623ms

Last 20

7–9–4 · 35% win rate
Avg rating -0.03
Avg headshot accuracy 12%
Avg reaction 625ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Support — Utility contribution stands above the rest of this profile (+1.7 against its own average).

Aim2.1

Utility4.7

Positioning4.2

Opening Duels0.2

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.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

Plays most like ZywOo 59% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower opening-duel success; 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

Strengths

Flashes. 0.76 enemies blinded per flash — utility that consistently lands.

Areas to improve

CT openings. Opening success drops from 53% on T to 30% on CT — first contacts on the defending side are being lost.

Reaction time. 626ms 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

Aim2.1

Positioning4.2

Utility4.7

Mechanics5.3

Opening Duels2.9

Win Impact3.7

Composite 3.6/10 (Learning), 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-0.03+0.02

first ⅓ avg -0.05 → last ⅓ avg -0.03

Reaction time613ms−19ms

first ⅓ avg 632ms → last ⅓ avg 613ms

Headshot accuracy12.7%−1.8%

first ⅓ avg 14.5% → last ⅓ avg 12.7%

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.

Personal bests

0.08Best match rating · 4–1 · dust2, 6 Sept →

35%Best headshot accuracy · 2–13 · dust2, 19 Aug →

438msFastest reaction time · 5–13 · dust2, 7 Oct →

13–2Biggest win · dust2, 19 Oct →

Across the last 100 tracked matches.

Highlights

6Longest win streak

5–2In matches decided by ≤2 rounds

Map breakdown

Strongest and weakest map need 5+ matches on two different maps — 1 of 5 maps qualify so far.

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	95	39–56	41%	-0.03
fachwerk	—	2	1–1	50%	-0.09
cache	—	1	0–1	0%	-0.06
nuke	—	1	1–0	100%	-0.01
inferno	—	1	0–1	0%	-0.06

Across the last 100 tracked matches.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

12.9%Headshot accuracy

22.7%Accuracy (enemy spotted)

24.9%Spray accuracy

73.8%Counter-strafing

12.4°Preaim

626msReaction time

53.1%T opening success

29.7%CT opening success

0.76Enemies flashed / flash

5.4%Flash assists

5.91HE damage / grenade

9.09Flashes / 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
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 12.4469° — above the 12° mark we flag
Aim Training →
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 12.9415% — below the 15% mark we flag
Aim Training →

Recent matches

Map	Score	Rating	HS%	Date
dust2	12–12	0.00	19%	23 Oct →
dust2	12–12	-0.05	10%	23 Oct →
dust2	13–10	-0.02	14%	23 Oct →
dust2	6–13	-0.06	15%	23 Oct →
dust2	3–13	-0.04	12%	21 Oct →
dust2	13–11	-0.05	18%	21 Oct →
dust2	4–13	-0.05	0%	20 Oct →
dust2	7–13	-0.01	10%	20 Oct →
dust2	13–2	0.06	14%	19 Oct →
dust2	9–13	-0.04	13%	19 Oct →
dust2	6–13	-0.04	14%	16 Oct →
dust2	12–12	-0.05	18%	16 Oct →
dust2	5–2	-0.14	9%	16 Oct →
dust2	4–13	-0.03	15%	14 Oct →
dust2	13–7	-0.03	3%	14 Oct →
dust2	5–13	-0.05	10%	13 Oct →
dust2	12–12	-0.09	14%	13 Oct →
dust2	9–13	-0.02	12%	12 Oct →
dust2	13–7	-0.00	12%	12 Oct →
dust2	13–10	0.01	13%	11 Oct →
dust2	13–4	-0.03	9%	10 Oct →
dust2	13–10	0.04	14%	10 Oct →
dust2	13–8	-0.03	10%	10 Oct →
dust2	13–7	-0.01	21%	10 Oct →
dust2	11–13	0.01	15%	9 Oct →
dust2	13–7	-0.05	2%	9 Oct →
dust2	10–13	0.01	8%	9 Oct →
dust2	2–13	-0.04	25%	9 Oct →
dust2	2–13	-0.06	15%	8 Oct →
dust2	10–13	0.02	22%	8 Oct →
dust2	10–13	-0.07	9%	8 Oct →
dust2	8–13	-0.02	7%	8 Oct →
dust2	5–13	-0.09	19%	7 Oct →
dust2	13–4	-0.01	12%	7 Oct →
dust2	9–13	0.00	16%	6 Oct →
dust2	13–9	0.03	13%	5 Oct →
dust2	6–13	-0.01	20%	3 Oct →
dust2	13–11	0.03	9%	3 Oct →
dust2	8–13	0.01	8%	2 Oct →
dust2	13–8	-0.06	11%	2 Oct →
dust2	9–13	-0.03	4%	2 Oct →
dust2	13–10	-0.03	10%	1 Oct →
dust2	7–13	-0.04	8%	1 Oct →
dust2	4–13	-0.09	8%	30 Sept →
dust2	5–13	-0.05	12%	30 Sept →
dust2	13–5	-0.02	16%	29 Sept →
dust2	3–13	-0.04	13%	29 Sept →
dust2	9–13	-0.06	8%	26 Sept →
dust2	8–13	-0.05	14%	25 Sept →
dust2	13–10	-0.03	14%	24 Sept →
dust2	13–5	-0.01	21%	24 Sept →
dust2	13–10	0.01	12%	23 Sept →
dust2	13–11	-0.03	11%	23 Sept →
dust2	10–13	-0.07	6%	23 Sept →
dust2	13–10	-0.05	20%	22 Sept →
dust2	5–13	-0.01	9%	21 Sept →
dust2	12–12	-0.05	8%	19 Sept →
dust2	9–13	0.02	14%	19 Sept →
dust2	13–8	0.04	18%	18 Sept →
dust2	13–10	0.01	16%	17 Sept →
dust2	11–13	-0.01	18%	17 Sept →
dust2	13–6	-0.04	17%	17 Sept →
dust2	6–13	-0.03	14%	17 Sept →
dust2	12–12	-0.05	8%	15 Sept →
dust2	13–11	-0.03	13%	14 Sept →
dust2	13–9	0.06	15%	14 Sept →
fachwerk	2–13	-0.09	4%	13 Sept →
fachwerk	5–0	-0.09	0%	13 Sept →
dust2	2–13	-0.09	12%	13 Sept →
dust2	12–12	-0.06	13%	12 Sept →
dust2	10–13	0.04	11%	10 Sept →
dust2	13–7	-0.05	5%	10 Sept →
dust2	10–13	-0.07	17%	7 Sept →
dust2	13–11	-0.09	8%	7 Sept →
dust2	7–13	-0.10	24%	7 Sept →
dust2	9–13	-0.06	5%	6 Sept →
dust2	6–13	-0.05	23%	6 Sept →
dust2	4–1	0.08	6%	6 Sept →
dust2	7–13	-0.09	11%	26 Aug →
dust2	3–13	-0.09	20%	26 Aug →
dust2	2–13	-0.08	21%	22 Aug →
cache	9–13	-0.06	8%	22 Aug →
dust2	5–13	-0.05	18%	21 Aug →
dust2	13–5	-0.04	12%	21 Aug →
dust2	12–12	-0.09	14%	20 Aug →
nuke	13–4	-0.01	20%	20 Aug →
dust2	13–4	-0.03	13%	20 Aug →
dust2	3–13	-0.13	16%	20 Aug →
dust2	13–10	-0.02	10%	19 Aug →
dust2	2–13	-0.09	35%	19 Aug →
dust2	13–10	-0.02	11%	19 Aug →
inferno	4–13	-0.06	24%	17 Aug →
dust2	13–6	-0.09	11%	17 Aug →
dust2	12–12	-0.07	10%	17 Aug →
dust2	13–4	-0.04	23%	17 Aug →
dust2	5–13	-0.11	12%	16 Aug →
dust2	9–13	0.01	14%	16 Aug →
dust2	13–6	-0.00	14%	16 Aug →
dust2	8–13	-0.06	21%	15 Aug →
dust2	13–4	-0.00	18%	15 Aug →