LaRocca — CS2 Stats

US76561198092604009[U:1:132338281]Steam profile ↗✓ No bans

1,468Tracked matches52%Win rate2020Tracked since

CSDB Rating6.4 SolidAggressive Rifler

FaceitLevel 6Top 54.0% of ranked FACEIT players

WingmanLegendary Eagle Master

Ladder ranks via Leetify

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Performance scores

Aim81

Positioning55

Utility48

0–100 skill scores via Leetify.

Recent form

COLD50–40–10Last 10050%Win rateWLLTWLLLWL

Last 10 vs previous 10: -10pp win rate · -0.02 avg rating

Player DNA

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

Aim8.1

Aggression6.7

Utility4.8

Positioning5.5

Opening Duels3.4

Clutch1.2

Strong CT-side openerEffective flashes

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 91% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

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 53% on CT to 34% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 620ms 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

Aim8.1

Positioning5.5

Utility4.8

Mechanics8.2

Opening Duels3.4

Win Impact5.6

Composite 6.4/10 (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 rating0.03+0.02

first ⅓ avg 0.01 → last ⅓ avg 0.03

Reaction time637ms−8ms

first ⅓ avg 645ms → last ⅓ avg 637ms

Headshot accuracy19.4%+1.4%

first ⅓ avg 18.0% → last ⅓ avg 19.4%

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 — nuke 9–6

13–1Biggest win — mirage

6Longest win streak

6–12In matches decided by ≤2 rounds

11Overtime games

Map breakdown

trainBest map · 67% over 9cacheWeakest map · 33% over 6

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	26	11–15	42%	0.02
ancient	B	18	9–9	50%	0.02
nuke	B	16	8–8	50%	0.06
inferno	A	10	6–4	60%	-0.00
train	S	9	6–3	67%	0.02
cache	D	6	2–4	33%	0.04
anubis	—	4	4–0	100%	0.02
vertigo	—	4	1–3	25%	0.01
dust2	—	4	2–2	50%	0.02
jura	—	1	0–1	0%	-0.03
grail	—	1	0–1	0%	-0.01
brewery	—	1	1–0	100%	0.09

Across the last 100 tracked matches.

Faceit stats

Combat

68Matches

56%Win rate

1.28Avg K/D

88.4ADR

42%Headshot %

Clutches & streaks

26%1v1 clutch win

25%1v2 clutch win

6Longest win streak

Recent Faceit resultsLLLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	20	50%	1.18	17.8
Nuke	12	67%	1.34	19.1
Ancient	9	56%	1.05	19.6
Inferno	7	57%	1.53	18.1
Dust2	5	40%	1.39	24.0
Anubis	5	80%	2.06	20.0
Train	3	67%	1.22	21.0
Vertigo	2	0%	1.27	22.5

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.

19.6%Headshot accuracy

38.9%Accuracy (enemy spotted)

39.9%Spray accuracy

87.0%Counter-strafing

9.7°Preaim

620msReaction time

33.7%T opening success

53.4%CT opening success

0.73Enemies flashed / flash

6.9%Flash assists

9.22HE damage / grenade

8.98Flashes / 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 33.7224% — below the 40% mark we flag

Spend your practice time on Cache

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.

Cache callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
anubis	13–11	0.02	23%	28 Aug →
cache	9–13	0.03	21%	26 Aug →
nuke	8–13	-0.01	32%	26 Aug →
ancient	15–15	0.01	17%	26 Aug →
ancient	13–8	0.07	10%	26 Aug →
cache	6–13	-0.09	10%	23 Aug →
ancient	9–13	-0.02	19%	19 Aug →
nuke	11–13	-0.02	31%	17 Aug →
cache	13–4	0.10	22%	12 Aug →
mirage	6–13	-0.00	23%	6 Aug →
cache	13–5	0.13	15%	6 Aug →
mirage	13–11	0.03	19%	30 Jul →
ancient	10–0	0.10	17%	30 Jul →
cache	11–13	0.04	12%	30 Jul →
cache	12–12	0.04	19%	29 Jul →
vertigo	2–13	-0.01	33%	29 Jul →
inferno	13–9	-0.07	24%	12 Feb →
jura	7–13	-0.03	24%	30 Jul →
train	15–15	0.10	28%	3 Jul →
grail	2–13	-0.01	47%	2 Jul →
nuke	9–6	0.24	16%	2 Jul →
nuke	9–6	0.24	13%	2 Jul →
inferno	9–2	0.12	15%	1 Jul →
anubis	13–9	0.03	9%	1 Jul →
inferno	9–7	-0.01	9%	28 Jun →
mirage	13–6	0.03	18%	26 Jun →
vertigo	1–9	-0.12	13%	26 Jun →
nuke	13–11	0.01	19%	14 Jun →
mirage	11–13	0.07	16%	3 Jun →
inferno	13–2	0.03	22%	3 Jun →
nuke	7–9	-0.00	16%	2 Jun →
mirage	13–2	0.04	16%	30 May →
inferno	2–9	-0.11	14%	29 May →
nuke	13–9	0.06	18%	29 May →
ancient	11–13	0.02	17%	29 May →
mirage	13–1	0.08	10%	26 May →
mirage	17–19	-0.02	9%	25 May →
ancient	5–13	-0.03	17%	21 May →
train	13–6	0.00	8%	21 May →
mirage	9–13	0.06	22%	14 May →
ancient	13–1	0.05	13%	14 May →
train	13–4	0.02	10%	14 May →
inferno	6–9	0.03	19%	14 May →
train	9–13	-0.09	14%	12 May →
ancient	13–9	0.07	15%	12 May →
mirage	7–13	0.04	18%	8 May →
brewery	9–6	0.09	17%	8 May →
inferno	16–13	0.01	23%	7 May →
nuke	12–12	0.06	24%	6 May →
mirage	13–5	0.02	16%	5 May →
anubis	13–4	0.04	16%	1 May →
train	8–13	0.09	29%	1 May →
anubis	13–6	-0.00	10%	24 Apr →
inferno	9–4	0.14	18%	24 Apr →
nuke	13–9	0.11	19%	23 Apr →
mirage	13–8	0.01	18%	22 Apr →
nuke	9–13	0.01	11%	21 Apr →
nuke	13–10	-0.02	14%	18 Apr →
mirage	13–5	0.06	6%	17 Apr →
nuke	13–3	0.13	21%	17 Apr →
mirage	15–15	-0.01	23%	15 Apr →
ancient	13–5	-0.03	12%	15 Apr →
nuke	11–13	-0.01	13%	15 Apr →
ancient	13–11	0.04	9%	14 Apr →
mirage	16–12	0.06	9%	14 Apr →
ancient	6–13	-0.04	22%	14 Apr →
vertigo	13–1	0.17	20%	14 Apr →
mirage	16–12	-0.01	13%	11 Apr →
ancient	11–13	0.04	16%	11 Apr →
mirage	13–16	-0.01	17%	10 Apr →
train	13–5	0.03	19%	10 Apr →
mirage	10–13	0.04	27%	10 Apr →
mirage	13–2	0.11	16%	10 Apr →
inferno	1–8	-0.10	17%	9 Apr →
ancient	6–13	-0.01	18%	9 Apr →
inferno	8–8	-0.08	30%	9 Apr →
mirage	7–13	0.04	21%	9 Apr →
dust2	13–10	0.00	13%	8 Apr →
dust2	11–13	0.04	17%	8 Apr →
mirage	13–11	0.02	10%	8 Apr →
train	13–7	-0.00	15%	8 Apr →
ancient	11–13	-0.02	8%	8 Apr →
ancient	13–9	0.04	23%	7 Apr →
dust2	13–9	0.01	13%	7 Apr →
nuke	13–9	0.04	23%	4 Apr →
mirage	11–13	0.05	16%	4 Apr →
nuke	15–15	0.06	29%	4 Apr →
ancient	16–12	-0.01	18%	4 Apr →
dust2	15–15	0.03	19%	1 Apr →
mirage	2–13	-0.08	25%	1 Apr →
ancient	5–13	-0.05	14%	1 Apr →
train	13–7	0.02	16%	1 Apr →
mirage	12–12	-0.02	19%	1 Apr →
vertigo	12–12	0.01	21%	28 Mar →
mirage	4–13	-0.06	22%	26 Mar →
ancient	13–7	0.05	10%	24 Mar →
train	13–8	0.02	8%	24 Mar →
nuke	4–13	0.00	19%	24 Mar →
mirage	5–13	-0.03	22%	24 Mar →
mirage	11–13	0.06	21%	18 Mar →