23 — CS2 Stats

76561199218874679[U:1:1258608951]Steam profile ↗✓ No bans

5,333Tracked matches52%Win rate2021Tracked since

CSDB Rating7.2 StrongAggressive Rifler

FaceitLevel 10 · 3,879 ELOTop 12.4% of ranked FACEIT players

WingmanSupreme Master First Class

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

Aim90

Positioning64

Utility37

0–100 skill scores via Leetify.

Recent form

STEADY59–39–2Last 10059%Win rateWLWLLWLWLL

Last 10 vs previous 10: -20pp win rate · -0.03 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim9.0

Aggression8.4

Utility3.7

Positioning6.4

Opening Duels5.0

Clutch3.4

Sharp aimerStrong CT-side opener

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 93% playstyle similarity

Most alike: opening-duel success, positioning 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

Aim. Aim score of 90 — the mechanical foundation is a clear strength.

CT openings. 62% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

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 62% on CT to 38% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim9.0

Positioning6.4

Utility3.7

Mechanics8.1

Opening Duels5.0

Win Impact5.6

Composite 7.2/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02−0.05

first ⅓ avg 0.07 → last ⅓ avg 0.02

Reaction time527ms−3ms

first ⅓ avg 530ms → last ⅓ avg 527ms

Headshot accuracy21.2%−4.6%

first ⅓ avg 25.9% → last ⅓ avg 21.2%

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

0.27Best rating — anubis 13–2

13–1Biggest win — inferno

10Longest win streak

6–4In matches decided by ≤2 rounds

Map breakdown

anubisBest map · 94% over 16mirageWeakest map · 33% over 6

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	18	9–9	50%	0.05
anubis	S	16	15–1	94%	0.05
ancient	B	15	8–7	53%	0.02
cache	A	12	7–5	58%	0.08
overpass	A	7	4–3	57%	0.07
nuke	S	6	4–2	67%	0.03
mirage	D	6	2–4	33%	0.02
train	S	6	4–2	67%	0.07
inferno	A	5	3–2	60%	0.06
italy	—	3	1–2	33%	0.05
vertigo	—	2	1–1	50%	0.05
alpine	—	2	1–1	50%	-0.02
boulder	—	1	0–1	0%	0.04
warden	—	1	0–1	0%	-0.04

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

4,893Matches

54%Win rate

1.27Avg K/D

88.7ADR

41%Headshot %

Clutches & streaks

37%1v1 clutch win

22%1v2 clutch win

15Longest win streak

Recent Faceit resultsLWWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	704	53%	1.27	17.9
Anubis	665	59%	1.35	18.8
Dust2	545	52%	1.30	18.6
Vertigo	185	60%	1.37	18.5
Overpass	150	63%	1.35	19.1
Nuke	132	51%	1.19	18.1
Inferno	102	49%	1.23	18.0
Mirage	73	47%	1.14	16.6

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.

20.9%Headshot accuracy

38.7%Accuracy (enemy spotted)

42.6%Spray accuracy

86.4%Counter-strafing

8.6°Preaim

512msReaction time

38.1%T opening success

62.2%CT opening success

0.40Enemies flashed / flash

6.7%Flash assists

6.05HE damage / grenade

5.74Flashes / 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 0.4035 — 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 38.1074% — 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.

33% win rate across 6 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
dust2	13–6	-0.01	15%	28 Aug →
anubis	8–13	-0.01	18%	27 Aug →
nuke	13–9	-0.03	34%	21 Aug →
dust2	8–13	-0.01	16%	17 Aug →
nuke	10–13	-0.03	7%	13 Aug →
ancient	13–7	0.04	25%	12 Aug →
inferno	6–13	-0.00	11%	12 Aug →
anubis	13–9	-0.05	32%	8 Aug →
mirage	5–13	-0.05	18%	7 Aug →
cache	11–13	0.00	24%	5 Aug →
inferno	13–5	0.03	17%	2 Aug →
cache	13–10	0.07	18%	31 Jul →
cache	13–5	0.06	15%	25 Jul →
ancient	9–13	-0.04	26%	21 Jul →
ancient	11–13	-0.02	13%	17 Jul →
ancient	7–13	0.01	20%	17 Jul →
dust2	10–13	-0.02	27%	17 Jul →
anubis	13–10	0.03	18%	13 Jul →
ancient	13–10	0.01	37%	13 Jul →
ancient	13–8	0.02	22%	13 Jul →
anubis	13–11	-0.04	14%	11 Jul →
dust2	9–13	0.05	13%	11 Jul →
boulder	10–13	0.04	24%	9 Jul →
dust2	10–13	0.15	24%	9 Jul →
ancient	13–11	0.02	23%	4 Jul →
mirage	6–13	-0.03	14%	1 Jul →
anubis	13–3	-0.05	0%	1 Jul →
ancient	12–12	0.00	32%	1 Jul →
nuke	13–3	0.13	32%	1 Jul →
overpass	13–6	0.08	31%	1 Jul →
inferno	13–1	0.06	16%	1 Jul →
cache	13–8	0.12	29%	1 Jul →
dust2	13–8	0.08	36%	1 Jul →
vertigo	10–13	0.10	38%	1 Jul →
mirage	9–13	0.04	33%	28 Jun →
dust2	13–11	0.02	13%	28 Jun →
nuke	6–13	-0.09	11%	25 Jun →
cache	13–4	0.11	50%	23 Jun →
dust2	13–7	0.03	42%	23 Jun →
mirage	13–4	-0.08	19%	23 Jun →
anubis	13–10	0.05	36%	17 Jun →
train	13–7	0.02	31%	17 Jun →
dust2	13–5	0.01	33%	17 Jun →
nuke	13–5	0.10	29%	17 Jun →
ancient	13–7	0.10	39%	16 Jun →
anubis	13–5	0.09	22%	16 Jun →
overpass	13–8	0.03	18%	12 Jun →
overpass	4–13	-0.07	27%	12 Jun →
train	7–13	0.09	32%	9 Jun →
cache	6–13	0.03	24%	9 Jun →
dust2	13–8	0.23	36%	9 Jun →
anubis	13–8	0.03	19%	9 Jun →
cache	13–7	0.07	36%	5 Jun →
dust2	10–13	0.05	29%	5 Jun →
train	9–13	-0.00	12%	5 Jun →
overpass	8–13	0.05	20%	5 Jun →
anubis	13–4	0.16	53%	5 Jun →
cache	13–7	0.16	24%	5 Jun →
italy	2–13	0.03	41%	5 Jun →
ancient	1–13	-0.01	42%	4 Jun →
dust2	7–13	-0.01	23%	4 Jun →
dust2	6–13	-0.01	37%	2 Jun →
train	13–5	0.08	33%	2 Jun →
warden	5–13	-0.04	22%	2 Jun →
overpass	9–13	0.10	38%	2 Jun →
nuke	13–11	0.11	21%	2 Jun →
train	13–7	0.12	34%	2 Jun →
cache	0–7	0.01	25%	2 Jun →
inferno	9–13	0.12	34%	2 Jun →
mirage	2–13	0.09	39%	2 Jun →
anubis	13–2	0.27	29%	2 Jun →
ancient	13–2	0.10	42%	2 Jun →
dust2	13–7	0.12	25%	2 Jun →
inferno	13–5	0.08	38%	30 May →
mirage	13–8	0.13	33%	30 May →
anubis	13–10	0.07	15%	30 May →
overpass	13–3	0.09	25%	30 May →
cache	7–13	0.12	29%	30 May →
dust2	13–4	0.14	37%	30 May →
ancient	4–13	-0.02	16%	30 May →
alpine	13–11	-0.00	17%	30 May →
italy	8–13	0.08	30%	30 May →
ancient	10–13	0.04	12%	29 May →
anubis	13–7	-0.02	23%	28 May →
anubis	13–3	0.09	27%	28 May →
anubis	13–7	0.03	20%	26 May →
alpine	4–13	-0.04	16%	25 May →
italy	13–3	0.04	32%	25 May →
overpass	13–11	0.20	27%	25 May →
vertigo	13–8	0.01	18%	25 May →
ancient	13–10	0.04	29%	25 May →
anubis	13–10	0.07	25%	25 May →
train	13–8	0.11	30%	24 May →
cache	13–2	0.07	50%	24 May →
dust2	13–6	-0.03	22%	22 May →
anubis	13–9	0.14	14%	15 May →
ancient	13–10	0.06	16%	15 May →
dust2	11–13	0.02	18%	13 May →
dust2	11–13	0.01	19%	11 May →
cache	12–12	0.09	22%	1 May →