hi — CS2 Stats

76561199103948792[U:1:1143683064]Steam profile ↗✓ No bans

463Tracked matches50%Win rate2022Tracked since

CSDB Rating4.4 Developing

FaceitLevel 8 · 1,237 ELOTop 31.2% of ranked FACEIT players

WingmanSupreme Master First Class

Ladder ranks via Leetify

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Performance scores

Aim59

Positioning50

Utility33

0–100 skill scores via Leetify.

Recent form

STEADY39–49–12Last 10039%Win rateLWWLTLLWLW

Last 10 vs previous 10: -20pp win rate · +0.01 avg rating

Player DNA

Aim5.9

Aggression7.1

Utility3.3

Positioning5.0

Opening Duels2.0

Clutch3.6

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 ropz 81% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

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

Areas to improve

Reaction time. 685ms 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

Aim5.9

Positioning5.0

Utility3.3

Mechanics6.3

Opening Duels2.0

Win Impact5.0

Composite 4.4/10 (Developing), 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 rating0.00−0.02

first ⅓ avg 0.03 → last ⅓ avg 0.00

Reaction time678ms+8ms

first ⅓ avg 669ms → last ⅓ avg 678ms

Headshot accuracy21.3%−1.8%

first ⅓ avg 23.1% → last ⅓ avg 21.3%

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

0.24Best rating — inferno 9–2

13–0Biggest win — cache

5Longest win streak

8–4In matches decided by ≤2 rounds

5Overtime games

Map breakdown

anubisBest map · 58% over 12mirageWeakest map · 25% over 8

Map	Grade	Played	Record	Win rate	Avg rating
inferno	C	20	7–13	35%	0.04
cache	D	13	4–9	31%	0.01
anubis	A	12	7–5	58%	0.04
train	C	9	4–5	44%	0.01
nuke	D	9	3–6	33%	-0.00
mirage	D	8	2–6	25%	-0.03
overpass	B	8	4–4	50%	0.04
vertigo	B	8	4–4	50%	0.01
ancient	—	4	0–4	0%	0.00
dust2	—	4	1–3	25%	0.01
office	—	4	2–2	50%	-0.01
stronghold	—	1	1–0	100%	0.00

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (25% over 8). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

260Matches

52%Win rate

1.16Avg K/D

85.3ADR

48%Headshot %

Clutches & streaks

38%1v1 clutch win

29%1v2 clutch win

9Longest win streak

Recent Faceit resultsWWWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	89	54%	1.18	16.5
Dust2	42	52%	1.14	17.2
Anubis	42	40%	1.13	15.8
Ancient	34	53%	1.09	16.2
Inferno	25	56%	1.21	16.2
Nuke	11	55%	1.22	14.2
Vertigo	10	40%	1.02	14.6
Overpass	3	67%	1.45	19.7

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.

21.1%Headshot accuracy

32.3%Accuracy (enemy spotted)

35.3%Spray accuracy

78.3%Counter-strafing

9.6°Preaim

685msReaction time

42.2%T opening success

33.7%CT opening success

0.44Enemies flashed / flash

3.9%Flash assists

5.95HE damage / grenade

5.06Flashes / 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
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4401 — below the 0.5 mark we flag
Grenade Lineups →
Advanced Mechanics
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 33.6984% — below the 40% mark we flag

Spend your practice time on Mirage

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

25% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
mirage	5–13	-0.07	19%	17 Aug →
train	13–10	0.13	24%	13 Aug →
overpass	13–11	0.12	29%	10 Aug →
ancient	9–13	0.08	24%	10 Aug →
dust2	12–12	0.03	15%	28 Jul →
cache	7–13	-0.02	19%	22 Jul →
train	6–13	-0.01	30%	22 Jul →
anubis	13–8	-0.02	23%	22 Jul →
cache	5–13	-0.03	24%	21 Jul →
anubis	13–11	-0.03	25%	21 Jul →
nuke	4–13	-0.01	13%	19 Jul →
dust2	7–0	0.01	5%	19 Jul →
anubis	7–13	-0.03	15%	19 Jul →
mirage	13–9	0.05	12%	16 Jul →
cache	16–14	-0.00	25%	16 Jul →
ancient	12–12	0.02	20%	11 Jul →
dust2	10–13	-0.01	16%	10 Jul →
overpass	13–9	-0.03	26%	9 Jul →
nuke	13–11	0.05	17%	9 Jul →
office	13–4	0.05	21%	8 Jul →
office	7–13	-0.01	16%	8 Jul →
cache	2–13	-0.06	15%	3 Jul →
cache	4–13	0.03	20%	3 Jul →
nuke	13–10	-0.00	25%	28 Jun →
cache	7–13	-0.01	24%	24 Jun →
cache	13–5	0.08	24%	24 Jun →
train	13–11	0.03	25%	18 Jun →
train	9–13	-0.07	17%	18 Jun →
train	10–13	-0.06	11%	18 Jun →
vertigo	13–5	0.01	44%	3 Jun →
vertigo	2–13	0.02	30%	3 Jun →
mirage	8–13	-0.08	28%	28 May →
anubis	12–12	-0.00	23%	27 May →
anubis	5–13	-0.01	17%	27 May →
vertigo	13–8	0.07	28%	20 May →
office	13–11	-0.03	25%	13 May →
cache	12–12	0.02	18%	7 May →
cache	13–0	0.17	48%	7 May →
cache	7–13	-0.03	16%	6 May →
mirage	10–13	-0.07	23%	29 Apr →
cache	4–13	-0.03	9%	29 Apr →
cache	4–13	-0.05	17%	29 Apr →
cache	16–13	0.05	17%	23 Apr →
anubis	15–15	0.10	18%	22 Apr →
train	13–5	-0.07	24%	22 Apr →
mirage	7–13	-0.03	25%	22 Apr →
inferno	9–5	0.13	16%	20 Apr →
ancient	7–13	-0.03	29%	17 Apr →
overpass	11–13	-0.01	25%	17 Apr →
nuke	3–13	-0.07	14%	17 Apr →
inferno	4–9	-0.07	17%	17 Apr →
nuke	7–13	-0.00	16%	17 Apr →
inferno	6–9	-0.00	12%	17 Apr →
mirage	5–13	-0.05	17%	16 Apr →
inferno	9–4	0.16	19%	15 Apr →
inferno	5–9	-0.04	16%	15 Apr →
inferno	13–8	0.10	14%	15 Apr →
inferno	11–13	-0.01	33%	10 Apr →
inferno	9–1	0.14	15%	10 Apr →
inferno	6–9	-0.05	26%	10 Apr →
vertigo	12–12	-0.02	19%	8 Apr →
vertigo	12–12	-0.05	35%	8 Apr →
vertigo	13–11	0.06	19%	8 Apr →
inferno	5–9	-0.02	26%	8 Apr →
stronghold	13–5	0.00	14%	6 Apr →
anubis	13–9	0.06	24%	6 Apr →
anubis	13–7	0.14	22%	1 Apr →
nuke	13–5	0.10	23%	1 Apr →
inferno	9–4	0.10	30%	1 Apr →
anubis	12–12	-0.00	14%	1 Apr →
anubis	13–9	0.07	17%	1 Apr →
anubis	13–9	0.08	20%	1 Apr →
anubis	13–4	0.06	16%	1 Apr →
inferno	7–9	-0.05	27%	31 Mar →
ancient	7–13	-0.05	18%	31 Mar →
mirage	13–8	-0.03	18%	27 Mar →
inferno	5–13	0.04	20%	26 Mar →
inferno	13–16	0.03	23%	23 Mar →
office	5–13	-0.06	42%	20 Mar →
inferno	4–9	-0.05	24%	20 Mar →
inferno	9–2	0.24	35%	20 Mar →
vertigo	4–9	-0.02	21%	19 Mar →
nuke	5–13	-0.10	8%	18 Mar →
vertigo	13–4	0.01	16%	18 Mar →
inferno	7–9	0.05	31%	14 Mar →
overpass	9–5	0.06	22%	14 Mar →
overpass	8–13	-0.04	11%	14 Mar →
overpass	13–8	-0.02	23%	12 Mar →
inferno	8–8	-0.01	26%	29 Jan →
overpass	8–13	0.01	22%	17 Jan →
overpass	8–13	0.22	22%	17 Jan →
nuke	6–13	-0.01	46%	10 Jan →
dust2	8–13	-0.01	27%	9 Jan →
nuke	12–12	0.03	39%	9 Jan →
mirage	15–15	0.04	14%	9 Jan →
inferno	9–7	-0.08	16%	8 Jan →
train	13–5	0.14	30%	2 Jan →
inferno	8–8	0.09	22%	2 Jan →
train	2–13	-0.03	21%	1 Jan →
train	4–13	0.04	21%	1 Jan →