SkinnyP — CS2 Stats

AU76561198076033104[U:1:115767376]Steam profile ↗✓ No bans

2,397Tracked matches44%Win rate2020Tracked since

CSDB Rating5.9 SolidAggressive Rifler

WingmanMaster Guardian II

Ladder ranks via Leetify

Performance scores

Aim76

Positioning53

Utility42

0–100 skill scores via Leetify.

Recent form

COLD40–49–11Last 10040%Win rateWLLTWLLLTW

Last 10 vs previous 10: -30pp win rate · +0.01 avg rating

Player DNA

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

Aim7.6

Aggression7.3

Utility4.2

Positioning5.3

Opening Duels3.6

Clutch8.0

Strong CT-side openerLimited utility dependenceReliable in 1v1s

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 90% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: 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 58% on CT to 31% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 654ms 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

Aim7.6

Positioning5.3

Utility4.2

Mechanics8.3

Opening Duels3.6

Win Impact3.0

Composite 5.9/10 (Solid), 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-0.01−0.01

first ⅓ avg 0.00 → last ⅓ avg -0.01

Reaction time651ms+10ms

first ⅓ avg 641ms → last ⅓ avg 651ms

Headshot accuracy18.7%+3.8%

first ⅓ avg 14.9% → last ⅓ avg 18.7%

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.

Highlights

0.14Best rating — office 13–10

13–1Biggest win — office

3Longest win streak

6–6In matches decided by ≤2 rounds

5Overtime games

Map breakdown

infernoBest map · 89% over 9dust2Weakest map · 17% over 30

Map	Grade	Played	Record	Win rate	Avg rating
dust2	D	30	5–25	17%	-0.01
office	C	18	8–10	44%	0.02
mirage	C	15	6–9	40%	-0.04
cache	C	11	4–7	36%	-0.02
inferno	S	9	8–1	89%	0.00
nuke	S	7	6–1	86%	0.00
overpass	—	4	1–3	25%	-0.02
ancient	—	3	1–2	33%	-0.01
anubis	—	2	0–2	0%	0.02
train	—	1	1–0	100%	0.01

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (17% over 30). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

8Matches

38%Win rate

0.80Avg K/D

76.9ADR

47%Headshot %

Clutches & streaks

60%1v1 clutch win

0%1v2 clutch win

1Longest win streak

Recent Faceit resultsLWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	4	25%	0.77	14.8
Inferno	2	0%	0.73	12.5
Overpass	1	100%	0.53	8.0
Dust2	1	100%	1.29	18.0

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.

18.6%Headshot accuracy

36.2%Accuracy (enemy spotted)

36.9%Spray accuracy

87.5%Counter-strafing

8.4°Preaim

654msReaction time

30.6%T opening success

58.1%CT opening success

0.66Enemies flashed / flash

5.4%Flash assists

9.53HE damage / grenade

4.27Flashes / 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
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 30.6052% — below the 40% mark we flag

Spend your practice time on Dust 2

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

17% win rate across 30 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

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