Larska — CS2 Stats

76561199648937429[U:1:1688671701]Steam profile ↗✓ No bans

2,083Tracked matches55%Win rate2024Tracked since

CSDB Rating6.6 SolidAggressive Rifler

Ladder ranks via Leetify

Performance scores

Aim76

Positioning52

Utility75

0–100 skill scores via Leetify.

Recent form

STEADY59–39–2Last 10059%Win rateLWWWWWLWLL

Last 10 vs previous 10: +0pp win rate · -0.01 avg rating

Player DNA

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

Aim7.6

Aggression6.8

Utility7.5

Positioning5.2

Opening Duels3.6

Clutch3.4

Strong CT-side openerHigh utility contribution

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 Twistzz 91% playstyle similarity

Most alike: utility contribution, positioning profile.

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

Strengths

Utility. Utility score of 75 — grenade impact well above the norm.

Areas to improve

T-side openings. Opening success drops from 54% on CT to 35% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 614ms 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

Positioning5.2

Utility7.5

Mechanics7.3

Opening Duels3.6

Win Impact6.7

Composite 6.6/10 (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 rating0.01+0.00

first ⅓ avg 0.01 → last ⅓ avg 0.01

Reaction time622ms−24ms

first ⅓ avg 646ms → last ⅓ avg 622ms

Headshot accuracy29.0%−3.4%

first ⅓ avg 32.4% → last ⅓ avg 29.0%

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

0.11Best rating — ancient 13–4

13–2Biggest win — mirage

6Longest win streak

15–11In matches decided by ≤2 rounds

10Overtime games

Map breakdown

nukeBest map · 79% over 14infernoWeakest map · 44% over 9

Map	Grade	Played	Record	Win rate	Avg rating
ancient	A	33	20–13	61%	0.02
anubis	B	24	12–12	50%	0.01
nuke	S	14	11–3	79%	0.02
inferno	C	9	4–5	44%	0.02
dust2	C	9	4–5	44%	0.00
mirage	S	6	4–2	67%	0.00
cache	—	3	2–1	67%	0.03
train	—	1	1–0	100%	0.02
overpass	—	1	1–0	100%	-0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (44% over 9). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,999Matches

51%Win rate

1.12Avg K/D

82.2ADR

58%Headshot %

Clutches & streaks

37%1v1 clutch win

22%1v2 clutch win

8Longest win streak

Recent Faceit resultsWLWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	564	58%	1.17	16.7
Mirage	366	48%	1.08	16.6
Nuke	359	49%	1.10	16.6
Anubis	235	52%	1.14	17.1
Inferno	214	41%	1.04	16.0
Train	110	54%	1.21	17.6
Dust2	94	43%	1.05	15.8
Overpass	31	39%	0.94	15.2

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.

29.1%Headshot accuracy

31.1%Accuracy (enemy spotted)

32.8%Spray accuracy

82.9%Counter-strafing

9.2°Preaim

614msReaction time

35.4%T opening success

53.7%CT opening success

0.62Enemies flashed / flash

13.6%Flash assists

9.52HE damage / grenade

14.96Flashes / 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 35.365% — below the 40% mark we flag

Spend your practice time on Inferno

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

44% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	9–13	-0.01	30%	10 Aug →
cache	13–8	0.09	27%	10 Aug →
ancient	13–7	-0.05	22%	7 Aug →
mirage	13–2	0.06	27%	5 Aug →
inferno	13–10	0.03	33%	28 Jul →
nuke	13–10	0.07	43%	28 Jul →
ancient	4–13	-0.03	30%	28 Jul →
nuke	13–8	-0.05	14%	28 Jul →
anubis	11–13	-0.00	33%	28 Jul →
anubis	8–13	-0.02	36%	27 Jul →
ancient	7–13	0.02	26%	24 Jul →
anubis	14–16	0.00	25%	24 Jul →
mirage	13–11	-0.02	30%	24 Jul →
ancient	13–6	0.07	48%	24 Jul →
anubis	13–11	-0.03	22%	23 Jul →
nuke	16–12	0.09	27%	23 Jul →
inferno	5–13	-0.03	15%	23 Jul →
nuke	13–8	0.05	45%	23 Jul →
ancient	13–2	0.04	32%	23 Jul →
inferno	12–16	-0.03	22%	23 Jul →
train	13–2	0.02	39%	22 Jul →
ancient	12–12	0.03	43%	22 Jul →
anubis	9–13	-0.04	15%	22 Jul →
ancient	16–13	-0.00	27%	22 Jul →
ancient	10–13	-0.06	24%	21 Jul →
ancient	13–8	0.09	33%	21 Jul →
inferno	13–11	0.07	33%	21 Jul →
anubis	6–13	0.03	27%	21 Jul →
ancient	9–13	0.02	24%	21 Jul →
inferno	7–13	0.03	32%	20 Jul →
anubis	11–13	0.03	20%	20 Jul →
anubis	11–13	-0.01	22%	20 Jul →
nuke	13–4	-0.01	37%	20 Jul →
dust2	9–13	-0.01	38%	19 Jul →
ancient	8–13	0.01	23%	19 Jul →
anubis	16–14	-0.01	28%	19 Jul →
inferno	4–13	-0.04	24%	19 Jul →
nuke	9–13	-0.01	30%	19 Jul →
ancient	13–5	0.01	28%	19 Jul →
nuke	13–10	0.01	19%	18 Jul →
anubis	13–3	0.08	30%	18 Jul →
inferno	13–7	0.05	26%	18 Jul →
anubis	16–13	0.01	25%	18 Jul →
ancient	10–13	0.02	22%	18 Jul →
nuke	13–9	0.04	23%	18 Jul →
mirage	8–13	-0.01	32%	18 Jul →
anubis	14–16	0.00	23%	17 Jul →
anubis	13–10	0.01	27%	17 Jul →
inferno	13–11	0.09	29%	16 Jul →
ancient	13–8	0.09	25%	16 Jul →
anubis	13–4	0.05	46%	14 Jul →
cache	9–13	0.00	22%	13 Jul →
nuke	13–11	0.05	37%	12 Jul →
ancient	13–6	0.00	32%	12 Jul →
anubis	13–5	0.07	29%	12 Jul →
ancient	13–4	0.11	15%	12 Jul →
anubis	11–13	0.04	20%	12 Jul →
anubis	13–10	0.01	25%	12 Jul →
nuke	13–3	0.07	18%	12 Jul →
dust2	12–12	-0.00	26%	12 Jul →
cache	13–10	0.01	29%	11 Jul →
anubis	13–11	-0.00	30%	11 Jul →
ancient	10–13	0.05	35%	11 Jul →
ancient	13–11	-0.04	18%	11 Jul →
nuke	13–8	0.08	15%	10 Jul →
ancient	13–11	0.01	34%	10 Jul →
nuke	10–5	-0.06	13%	10 Jul →
ancient	10–13	0.03	32%	10 Jul →
anubis	10–1	0.06	60%	9 Jul →
anubis	3–13	-0.03	11%	9 Jul →
mirage	13–6	-0.02	11%	9 Jul →
dust2	10–13	0.02	32%	9 Jul →
ancient	13–2	0.01	36%	9 Jul →
anubis	13–11	0.03	18%	9 Jul →
ancient	13–9	0.03	20%	9 Jul →
dust2	11–13	0.02	27%	9 Jul →
dust2	7–13	0.01	44%	9 Jul →
ancient	13–3	0.05	40%	9 Jul →
mirage	7–13	-0.00	38%	9 Jul →
ancient	5–13	-0.01	23%	8 Jul →
ancient	16–12	0.05	19%	8 Jul →
ancient	13–6	0.08	43%	24 Jun →
anubis	11–13	-0.03	20%	24 Jun →
ancient	7–13	0.03	37%	23 Jun →
ancient	11–13	-0.02	42%	22 Jun →
anubis	13–11	-0.02	30%	22 Jun →
anubis	11–13	0.07	28%	22 Jun →
ancient	13–11	-0.00	16%	22 Jun →
dust2	13–11	-0.03	56%	22 Jun →
dust2	13–4	-0.01	45%	21 Jun →
nuke	7–13	-0.05	47%	21 Jun →
ancient	11–13	-0.02	45%	21 Jun →
ancient	13–9	0.05	35%	20 Jun →
dust2	16–14	0.02	26%	20 Jun →
ancient	13–8	0.04	28%	18 Jun →
ancient	13–3	0.03	35%	17 Jun →
dust2	19–15	-0.00	31%	17 Jun →
mirage	13–9	0.01	34%	17 Jun →
nuke	8–13	-0.04	32%	17 Jun →
overpass	13–11	-0.01	25%	17 Jun →