DirtyAsshole — CS2 Stats

76561198000693664[U:1:40427936]Steam profile ↗✓ No bans

1,001Tracked matches55%Win rate2020Tracked since

CSDB Rating4.1 Developing

Premier CS Rating13,624Blue band · top ~35.7% of ranked players (population est.)

CSDB Leaderboard#24686 of 37689 tracked

FaceitLevel 3Top 90.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim42

Positioning54

Utility41

0–100 skill scores via Leetify.

Recent form

HOT53–46–1Last 10053%Win rateWLWLWLWWWW

Last 10 vs previous 10: +40pp win rate · -0.00 avg rating

Player DNA

Aim4.2

Aggression5.4

Utility4.1

Positioning5.4

Opening Duels2.4

Clutch1.0

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: opening-fight frequency, opening-duel success.

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

T-side openings. Opening success drops from 50% on CT to 29% on T — the same duels are being taken with worse setups on the attacking side.

Counter-strafing. Only 62% 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

Aim4.2

Positioning5.4

Utility4.1

Mechanics2.7

Opening Duels2.5

Win Impact6.7

Composite 4.1/10 (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-0.02+0.00

first ⅓ avg -0.02 → last ⅓ avg -0.02

Reaction time529ms−46ms

first ⅓ avg 575ms → last ⅓ avg 529ms

Headshot accuracy11.5%−1.4%

first ⅓ avg 12.9% → last ⅓ avg 11.5%

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

0.07Best rating — inferno 13–9

13–1Biggest win — anubis

5Longest win streak

11–7In matches decided by ≤2 rounds

9Overtime games

Map breakdown

nukeBest map · 78% over 9anubisWeakest map · 38% over 13

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	23	12–11	52%	-0.02
cache	B	22	10–12	45%	-0.02
ancient	A	16	10–6	63%	-0.01
anubis	C	13	5–8	38%	-0.01
dust2	A	10	6–4	60%	-0.02
nuke	S	9	7–2	78%	-0.01
mirage	C	7	3–4	43%	-0.00

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (38% over 13). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

11Matches

36%Win rate

0.57Avg K/D

55.7ADR

37%Headshot %

Clutches & streaks

25%1v1 clutch win

11%1v2 clutch win

1Longest win streak

Recent Faceit resultsWLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	4	25%	0.46	11.0
Anubis	3	67%	0.51	10.3
Ancient	1	100%	0.53	8.0
Mirage	1	0%	0.84	26.0
Train	1	0%	0.80	12.0

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.

11.3%Headshot accuracy

31.8%Accuracy (enemy spotted)

33.5%Spray accuracy

62.4%Counter-strafing

11.0°Preaim

524msReaction time

28.9%T opening success

50.2%CT opening success

0.46Enemies flashed / flash

4.9%Flash assists

6.55HE damage / grenade

2.82Flashes / 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 11.3484% — below the 15% mark we flag
Aim Training →
Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4632 — below the 0.5 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 28.9465% — below the 40% mark we flag

Spend your practice time on Anubis

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

38% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	13–4	-0.05	4%	27 Aug →
anubis	14–16	-0.06	18%	27 Aug →
cache	13–11	-0.01	5%	27 Aug →
inferno	11–13	-0.00	11%	26 Aug →
dust2	13–10	-0.01	18%	26 Aug →
mirage	10–13	-0.02	12%	25 Aug →
ancient	13–8	0.02	13%	25 Aug →
cache	13–9	-0.01	8%	25 Aug →
anubis	16–13	0.01	13%	24 Aug →
ancient	13–5	0.01	8%	24 Aug →
anubis	7–13	-0.03	22%	24 Aug →
nuke	13–10	0.03	4%	24 Aug →
ancient	11–13	-0.05	8%	24 Aug →
inferno	9–13	0.03	17%	24 Aug →
dust2	8–13	0.01	18%	23 Aug →
inferno	13–9	-0.01	21%	23 Aug →
cache	4–13	-0.04	23%	23 Aug →
nuke	8–13	-0.05	13%	20 Aug →
cache	13–7	0.05	5%	20 Aug →
inferno	9–13	-0.05	10%	20 Aug →
anubis	9–13	-0.04	3%	20 Aug →
cache	6–13	-0.02	12%	19 Aug →
dust2	13–8	-0.01	13%	19 Aug →
dust2	13–6	-0.04	3%	19 Aug →
anubis	0–13	-0.05	5%	19 Aug →
inferno	15–15	-0.04	12%	16 Aug →
nuke	13–8	-0.05	10%	16 Aug →
inferno	16–13	0.02	14%	15 Aug →
nuke	13–10	-0.04	2%	15 Aug →
ancient	13–8	0.01	11%	13 Aug →
inferno	8–13	-0.04	21%	13 Aug →
inferno	3–13	-0.07	13%	10 Aug →
cache	13–3	0.04	8%	10 Aug →
cache	10–13	-0.01	2%	10 Aug →
ancient	11–13	0.02	10%	9 Aug →
inferno	13–9	0.07	15%	9 Aug →
inferno	13–9	0.02	12%	9 Aug →
ancient	13–8	0.02	9%	9 Aug →
cache	4–13	-0.02	10%	9 Aug →
nuke	13–11	0.01	10%	9 Aug →
cache	13–6	-0.01	19%	9 Aug →
anubis	13–11	-0.02	4%	9 Aug →
nuke	13–9	-0.03	20%	9 Aug →
cache	13–9	0.01	7%	9 Aug →
ancient	12–16	-0.05	5%	8 Aug →
inferno	7–13	-0.05	13%	8 Aug →
inferno	13–10	-0.01	13%	8 Aug →
ancient	13–4	0.07	12%	8 Aug →
cache	13–9	0.04	7%	8 Aug →
anubis	6–13	-0.04	11%	8 Aug →
anubis	6–13	-0.02	14%	8 Aug →
nuke	13–6	0.00	22%	8 Aug →
dust2	5–13	0.00	17%	8 Aug →
dust2	13–9	0.00	15%	8 Aug →
inferno	13–11	-0.05	5%	8 Aug →
dust2	9–13	-0.03	9%	7 Aug →
ancient	13–7	-0.01	22%	7 Aug →
cache	7–13	-0.05	11%	7 Aug →
mirage	5–13	-0.02	21%	7 Aug →
cache	13–5	0.05	4%	7 Aug →
mirage	8–13	-0.03	9%	4 Aug →
ancient	6–13	-0.14	8%	4 Aug →
inferno	13–7	-0.01	8%	4 Aug →
anubis	13–11	-0.03	10%	4 Aug →
cache	16–14	-0.02	11%	3 Aug →
mirage	10–13	0.03	14%	3 Aug →
cache	11–13	-0.01	23%	31 Jul →
cache	9–13	-0.05	7%	30 Jul →
cache	7–13	-0.03	16%	30 Jul →
inferno	5–13	-0.03	10%	30 Jul →
inferno	13–7	-0.06	7%	30 Jul →
dust2	10–13	-0.06	12%	29 Jul →
ancient	16–14	-0.00	11%	29 Jul →
dust2	13–11	-0.04	8%	27 Jul →
cache	6–13	-0.11	3%	27 Jul →
dust2	13–5	0.01	21%	27 Jul →
anubis	9–13	0.03	22%	26 Jul →
ancient	10–13	-0.05	10%	26 Jul →
anubis	13–11	0.04	12%	26 Jul →
ancient	13–10	0.01	17%	25 Jul →
ancient	13–4	0.03	9%	25 Jul →
inferno	13–3	0.04	18%	25 Jul →
cache	2–13	-0.06	10%	25 Jul →
cache	13–8	-0.08	19%	25 Jul →
inferno	7–13	-0.06	8%	25 Jul →
anubis	3–13	-0.03	15%	25 Jul →
ancient	13–11	-0.00	22%	25 Jul →
mirage	13–11	-0.02	5%	25 Jul →
inferno	13–8	-0.01	24%	25 Jul →
nuke	10–13	-0.03	13%	24 Jul →
anubis	13–1	0.06	14%	24 Jul →
mirage	13–7	0.06	13%	24 Jul →
nuke	13–3	0.04	22%	24 Jul →
inferno	7–13	-0.06	5%	23 Jul →
cache	14–16	-0.03	10%	23 Jul →
inferno	13–10	-0.04	18%	23 Jul →
inferno	11–13	-0.05	14%	22 Jul →
mirage	13–6	-0.03	7%	22 Jul →
cache	13–16	-0.05	10%	22 Jul →
ancient	9–13	-0.07	14%	22 Jul →