La Caraméra — CS2 Stats

FR76561199824936775[U:1:1864671047]Steam profile ↗✓ No bans

286Tracked matches37%Win rate2025Tracked since

144Hours in CS

CSDB Rating4.2 Developing

Ladder ranks via Leetify

Performance scores

Aim58

Positioning33

Utility49

0–100 skill scores via Leetify.

Recent form

COLD40–53–7Last 10040%Win rateLWLWLLLLLT

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

Player DNA

Aim5.8

Aggression3.7

Utility4.9

Positioning3.3

Opening Duels0.3

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 b1t 76% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower opening-fight frequency; 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. 617ms 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

Aim5.8

Positioning3.3

Utility4.9

Mechanics6.2

Opening Duels0.8

Win Impact0.7

Composite 4.2/10 (Developing), 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-0.02−0.01

first ⅓ avg -0.01 → last ⅓ avg -0.02

Reaction time629ms−108ms

first ⅓ avg 738ms → last ⅓ avg 629ms

Headshot accuracy16.7%+4.3%

first ⅓ avg 12.4% → last ⅓ avg 16.7%

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

0.13Best rating — nuke 9–1

13–1Biggest win — mirage

6Longest win streak

2–6In matches decided by ≤2 rounds

4Overtime games

Map breakdown

trainBest map · 50% over 10anubisWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	53	19–34	36%	-0.01
mirage	B	13	6–7	46%	-0.03
train	B	10	5–5	50%	-0.03
anubis	D	6	1–5	17%	-0.01
inferno	D	6	2–4	33%	-0.02
cache	—	3	0–3	0%	-0.02
nuke	—	3	2–1	67%	0.04
overpass	—	3	3–0	100%	0.03
vertigo	—	2	1–1	50%	-0.01
ancient	—	1	1–0	100%	-0.00

Across the last 100 tracked matches.

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

Lifetime stats

5,581Lifetime kills

0.82K/D

410Matches

54.9%Match win rate · Top 10% of tracked players

42.9%Headshot %

0.0%Shot accuracy

773MVPs

144Hours (in match)

455Bombs planted

72Bombs defused

Most-used weapons

AK-472,291

M4A4 / M4A1-S1,350

MAC-10409

MP9364

Glock-18339

P2000 / USP-S324

Desert Eagle86

FAMAS79

Five-SeveN76

Tec-961

Lifetime map wins

1,643dust2

618inferno

393train

209vertigo

148nuke

13office

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

15.7%Headshot accuracy

33.4%Accuracy (enemy spotted)

34.8%Spray accuracy

77.9%Counter-strafing

10.2°Preaim

617msReaction time

25.9%T opening success

36.7%CT opening success

0.54Enemies flashed / flash

17.0%Flash assists

12.02HE damage / grenade

1.87Flashes / 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
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 1.8699 — below the 4 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 25.8671% — below the 40% mark we flag

Spend your practice time on Anubis

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 6 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

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