stepped on — CS2 Stats

76561198345821521[U:1:385555793]

1,227Tracked matches41%Win rate2020Tracked since

5,116Hours in CS15Hrs last 2 wks

CSDB Rating4.7 DevelopingHybrid Rifler

Premier CS Rating11,036Blue band · top ~49.4% of ranked players (population est.)

CSDB Leaderboard#11969 of 16568 tracked

FaceitLevel 3Top 90.6% of ranked FACEIT players

Ladder ranks via Leetify

Share this profile

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim64

Positioning55

Utility24

0–100 skill scores via Leetify.

Recent form

STEADY32–63–5Last 10032%Win rateLWLLLWWWTL

Last 10 vs previous 10: +0pp win rate · +0.01 avg rating

Player DNA

Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.

Aim6.4

Aggression7.7

Utility2.4

Positioning5.5

Opening Duels3.7

Clutch0.0

Strong 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 84% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: lower utility contribution; 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

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 57% on CT to 33% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 575ms 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

Aim6.4

Positioning5.5

Utility2.4

Mechanics6.6

Opening Duels3.7

Win Impact1.9

Composite 4.7/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 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 time585ms−65ms

first ⅓ avg 650ms → last ⅓ avg 585ms

Headshot accuracy20.3%+5.8%

first ⅓ avg 14.5% → last ⅓ avg 20.3%

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

0.17Best rating — cache 13–8

13–1Biggest win — inferno

3Longest win streak

3–7In matches decided by ≤2 rounds

9Overtime games

Map breakdown

dust2Best map · 67% over 12ancientWeakest map · 10% over 10

Map	Grade	Played	Record	Win rate	Avg rating
cache	C	25	9–16	36%	0.01
nuke	C	20	7–13	35%	0.01
inferno	D	14	2–12	14%	-0.04
dust2	S	12	8–4	67%	0.01
ancient	D	10	1–9	10%	-0.03
mirage	D	7	1–6	14%	-0.01
anubis	A	5	3–2	60%	0.03
vertigo	—	3	0–3	0%	-0.02
train	—	3	1–2	33%	-0.02
overpass	—	1	0–1	0%	-0.04

Across the last 100 tracked matches.

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

Lifetime stats

56,211Lifetime kills

1.07K/D · Top 50% of tracked players

2,810Matches

44.6%Match win rate

27.7%Headshot %

15.0%Shot accuracy · Top 50% of tracked players

8,218MVPs

1,271Hours (in match)

3,536Bombs planted

869Bombs defused

Most-used weapons

AWP24,743

AK-4710,033

M4A4 / M4A1-S5,870

P2000 / USP-S3,037

Glock-182,111

Desert Eagle1,539

MAC-101,050

Knife1,027

XM1014913

MP9645

Lifetime map wins

6,398dust2

4,011inferno

2,768nuke

882vertigo

487cbble

432train

62lake

26office

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

Faceit stats

Combat

180Matches

53%Win rate

1.28Avg K/D

95.2ADR

21%Headshot %

Clutches & streaks

0%1v1 clutch win

0%1v2 clutch win

6Longest win streak

Recent Faceit resultsWLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Train	1	0%	1.36	19.0
Dust2	1	0%	0.54	7.0

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.

20.0%Headshot accuracy

32.8%Accuracy (enemy spotted)

26.4%Spray accuracy

79.7%Counter-strafing

9.4°Preaim

575msReaction time

32.8%T opening success

56.6%CT opening success

0.53Enemies flashed / flash

7.4%Flash assists

1.70HE damage / grenade

3.33Flashes / 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.

Grenades & Utility
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 3.3308 — below the 4 mark we flag
Grenade Lineups →
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 32.7641% — below the 40% mark we flag

Spend your practice time on Ancient

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

10% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	10–13	-0.03	15%	27 Aug →
ancient	13–8	0.02	21%	27 Aug →
nuke	11–13	0.03	41%	27 Aug →
nuke	11–13	0.01	28%	26 Aug →
cache	5–13	-0.04	26%	26 Aug →
inferno	13–1	0.07	0%	26 Aug →
cache	13–7	0.01	9%	26 Aug →
nuke	13–5	0.10	22%	25 Aug →
cache	15–15	-0.03	14%	25 Aug →
dust2	14–16	-0.03	19%	24 Aug →
cache	15–15	0.06	24%	24 Aug →
dust2	13–9	0.12	20%	24 Aug →
anubis	11–13	-0.03	15%	22 Aug →
ancient	9–13	0.02	16%	19 Aug →
dust2	13–7	-0.04	13%	18 Aug →
mirage	8–13	-0.04	19%	16 Aug →
anubis	13–3	0.06	12%	16 Aug →
mirage	6–13	-0.05	29%	15 Aug →
dust2	13–11	0.02	6%	15 Aug →
ancient	8–13	-0.11	14%	13 Aug →
mirage	3–10	0.02	67%	13 Aug →
dust2	13–6	-0.01	29%	12 Aug →
inferno	5–13	-0.08	10%	11 Aug →
inferno	11–13	0.01	19%	10 Aug →
cache	13–4	0.07	23%	10 Aug →
anubis	13–8	-0.01	25%	7 Aug →
ancient	15–15	-0.01	15%	7 Aug →
inferno	11–13	-0.04	5%	6 Aug →
ancient	7–13	-0.10	25%	6 Aug →
cache	7–13	-0.04	36%	6 Aug →
nuke	8–13	0.04	14%	5 Aug →
nuke	8–13	-0.03	18%	5 Aug →
cache	9–13	-0.06	23%	5 Aug →
nuke	13–8	-0.03	39%	5 Aug →
inferno	5–13	-0.07	29%	5 Aug →
nuke	13–8	-0.01	21%	5 Aug →
nuke	4–13	0.01	13%	4 Aug →
inferno	4–13	-0.05	3%	4 Aug →
nuke	13–10	0.04	18%	4 Aug →
dust2	13–7	0.08	9%	4 Aug →
inferno	2–7	-0.05	10%	18 Jul →
cache	13–6	-0.05	0%	17 Jul →
dust2	13–4	0.02	22%	17 Jul →
nuke	7–13	0.03	16%	17 Jul →
anubis	3–13	-0.03	22%	17 Jul →
mirage	7–13	-0.06	43%	16 Jul →
cache	7–13	0.01	15%	16 Jul →
nuke	4–13	-0.06	16%	16 Jul →
nuke	4–13	0.03	50%	15 Jul →
dust2	13–10	0.04	18%	15 Jul →
nuke	12–16	0.06	36%	13 Jul →
cache	13–3	0.05	16%	13 Jul →
anubis	13–4	0.14	9%	13 Jul →
cache	13–8	0.17	33%	13 Jul →
mirage	8–13	0.09	12%	13 Jul →
dust2	2–13	-0.02	21%	13 Jul →
cache	10–13	-0.01	22%	13 Jul →
nuke	3–13	-0.05	11%	13 Jul →
ancient	8–13	-0.05	7%	9 Jul →
cache	3–13	-0.09	17%	7 Jul →
cache	13–1	0.12	50%	7 Jul →
inferno	2–13	-0.09	5%	2 Jul →
mirage	15–15	-0.06	23%	1 Jul →
inferno	6–13	-0.10	7%	1 Jul →
cache	12–12	0.04	24%	9 Jun →
nuke	4–13	-0.04	14%	3 Jun →
vertigo	9–13	-0.05	0%	2 Jun →
vertigo	5–13	0.01	9%	31 May →
cache	9–13	0.06	27%	29 May →
inferno	4–13	-0.06	13%	28 May →
cache	9–13	-0.07	19%	25 May →
vertigo	3–13	-0.03	21%	24 May →
nuke	13–9	0.07	21%	23 May →
dust2	6–13	-0.07	9%	23 May →
cache	8–13	0.01	6%	22 May →
inferno	8–13	-0.08	0%	22 May →
cache	10–13	-0.04	13%	20 May →
train	13–5	0.09	33%	20 May →
ancient	12–16	-0.06	28%	18 May →
cache	10–13	0.04	19%	18 May →
cache	7–13	-0.04	10%	17 May →
nuke	13–10	0.01	12%	17 May →
dust2	13–16	-0.03	17%	15 May →
overpass	2–13	-0.04	15%	14 May →
ancient	2–13	-0.02	13%	14 May →
inferno	13–9	0.03	8%	13 May →
train	7–13	-0.09	0%	13 May →
ancient	9–13	0.03	33%	13 May →
dust2	13–9	0.02	15%	13 May →
nuke	13–11	0.04	14%	12 May →
inferno	14–16	-0.07	5%	12 May →
cache	10–13	-0.02	16%	12 May →
ancient	10–13	-0.01	12%	12 May →
mirage	13–4	0.07	15%	11 May →
train	2–13	-0.06	11%	11 May →
cache	13–3	-0.00	10%	11 May →
cache	13–11	0.03	16%	11 May →
nuke	8–13	0.04	16%	10 May →
cache	13–4	-0.04	11%	10 May →
nuke	9–13	-0.06	14%	10 May →