limaNe — CS2 Stats

76561198298134003[U:1:337868275]Steam profile ↗✓ No bans

1,646Tracked matches42%Win rate2020Tracked since

CSDB Rating6.5 SolidAggressive Rifler

Premier CS Rating24,556Top 50% of 819 CSDB-tracked playersPink band · top ~3.5% of ranked players (population est.)

CSDB Leaderboard#2375 of 12416 tracked

FaceitLevel 9 · 2,196 ELOTop 20.7% of ranked FACEIT players

WingmanLegendary Eagle Master

Ladder ranks via Leetify

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Performance scores

Aim85

Positioning61

Utility59

0–100 skill scores via Leetify.

Recent form

COLD55–36–9Last 10055%Win rateLWLLLLLLWL

Last 10 vs previous 10: -30pp win rate · -0.02 avg rating

Player DNA

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

Aim8.5

Aggression8.6

Utility5.9

Positioning6.1

Opening Duels4.2

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 jL 94% 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 85 — the mechanical foundation is a clear strength.

CT openings. 61% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 61% on CT to 33% 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

Aim8.5

Positioning6.1

Utility5.9

Mechanics7.3

Opening Duels4.2

Win Impact2.4

Composite 6.5/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.03−0.02

first ⅓ avg 0.05 → last ⅓ avg 0.03

Reaction time536ms−109ms

first ⅓ avg 645ms → last ⅓ avg 536ms

Headshot accuracy18.8%−1.0%

first ⅓ avg 19.8% → last ⅓ avg 18.8%

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

0.20Best rating — dust2 12–12

13–1Biggest win — train

9Longest win streak

8–7In matches decided by ≤2 rounds

1Overtime games

Map breakdown

anubisBest map · 75% over 8infernoWeakest map · 43% over 14

Map	Grade	Played	Record	Win rate	Avg rating
nuke	B	15	8–7	53%	0.03
cache	B	15	8–7	53%	0.03
inferno	C	14	6–8	43%	0.05
ancient	B	13	7–6	54%	0.04
dust2	A	8	5–3	63%	0.04
anubis	S	8	6–2	75%	0.07
train	C	7	3–4	43%	0.04
overpass	B	6	3–3	50%	0.05
vertigo	S	6	4–2	67%	0.03
office	—	4	3–1	75%	0.06
mirage	—	3	1–2	33%	0.05
boulder	—	1	1–0	100%	-0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (43% over 14). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

711Matches

54%Win rate

1.24Avg K/D

95.0ADR

41%Headshot %

Clutches & streaks

37%1v1 clutch win

28%1v2 clutch win

9Longest win streak

Recent Faceit resultsLWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Nuke	14	36%	1.49	21.2
Mirage	14	64%	1.51	19.2
Anubis	13	46%	1.31	17.2
Ancient	9	56%	1.33	17.8
Overpass	6	33%	1.00	15.2
Inferno	5	40%	1.26	18.4
Cache	5	60%	1.97	17.4
Dust2	3	67%	1.87	22.3

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.

18.7%Headshot accuracy

39.5%Accuracy (enemy spotted)

41.0%Spray accuracy

82.8%Counter-strafing

9.5°Preaim

526msReaction time

32.9%T opening success

60.6%CT opening success

0.54Enemies flashed / flash

3.8%Flash assists

9.09HE damage / grenade

7.49Flashes / 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 32.8832% — 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.

43% win rate across 14 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	8–13	0.03	26%	26 Aug →
nuke	13–4	0.03	12%	26 Aug →
inferno	11–13	0.09	21%	26 Aug →
cache	9–13	0.01	10%	26 Aug →
train	4–13	0.06	26%	20 Aug →
overpass	3–13	-0.05	28%	20 Aug →
nuke	4–13	-0.06	9%	20 Aug →
cache	11–13	0.00	15%	20 Aug →
inferno	13–11	0.09	18%	20 Aug →
ancient	8–13	0.02	17%	20 Aug →
nuke	12–12	0.02	13%	19 Aug →
inferno	12–12	0.05	23%	19 Aug →
cache	13–6	-0.01	18%	19 Aug →
dust2	6–13	0.01	20%	19 Aug →
nuke	13–10	0.08	18%	19 Aug →
office	1–4	0.07	22%	19 Aug →
cache	13–5	-0.04	6%	19 Aug →
anubis	13–9	0.09	35%	18 Aug →
inferno	11–13	0.06	15%	18 Aug →
dust2	13–2	0.05	31%	18 Aug →
inferno	12–16	0.08	20%	18 Aug →
inferno	0–13	-0.08	25%	18 Aug →
nuke	13–4	0.06	22%	18 Aug →
cache	12–12	0.02	17%	18 Aug →
ancient	13–4	0.02	20%	18 Aug →
dust2	13–9	0.03	23%	18 Aug →
train	12–12	0.06	20%	18 Aug →
nuke	2–11	0.05	16%	18 Aug →
office	13–8	0.02	16%	18 Aug →
dust2	0–13	-0.09	0%	18 Aug →
cache	1–13	-0.03	22%	18 Aug →
anubis	13–3	0.14	18%	18 Aug →
train	13–1	0.10	18%	18 Aug →
nuke	13–7	0.03	13%	17 Aug →
train	4–2	0.02	22%	17 Aug →
overpass	12–12	0.01	19%	17 Aug →
dust2	13–10	0.04	9%	17 Aug →
inferno	12–12	0.09	13%	17 Aug →
anubis	13–10	0.04	18%	17 Aug →
mirage	6–13	-0.00	25%	15 Aug →
ancient	9–13	-0.02	21%	13 Aug →
cache	11–13	0.06	21%	13 Aug →
ancient	3–13	-0.03	5%	13 Aug →
nuke	6–13	-0.02	13%	13 Aug →
dust2	12–12	0.20	20%	13 Aug →
cache	9–13	0.09	19%	13 Aug →
inferno	13–8	0.02	19%	13 Aug →
ancient	12–12	0.02	10%	13 Aug →
ancient	10–13	0.02	19%	12 Aug →
nuke	13–1	0.05	22%	12 Aug →
office	13–9	0.03	25%	12 Aug →
inferno	13–4	0.12	17%	12 Aug →
anubis	13–9	0.04	12%	12 Aug →
ancient	13–4	0.09	28%	12 Aug →
vertigo	4–13	-0.04	22%	11 Aug →
cache	13–7	0.15	25%	11 Aug →
ancient	9–13	-0.00	16%	11 Aug →
nuke	13–9	0.06	34%	11 Aug →
cache	13–2	0.08	23%	11 Aug →
overpass	7–13	0.01	12%	11 Aug →
train	7–13	0.01	14%	11 Aug →
ancient	13–7	0.11	11%	11 Aug →
dust2	13–2	0.03	37%	11 Aug →
vertigo	13–8	0.00	19%	11 Aug →
anubis	11–13	0.09	16%	9 Aug →
cache	13–10	0.06	21%	9 Aug →
cache	13–11	-0.03	20%	8 Aug →
train	4–13	-0.01	19%	6 Aug →
inferno	13–11	0.04	23%	6 Aug →
ancient	13–6	-0.06	7%	6 Aug →
train	13–7	0.02	8%	6 Aug →
anubis	8–13	0.04	12%	6 Aug →
ancient	13–10	0.11	14%	6 Aug →
anubis	13–3	0.07	19%	6 Aug →
nuke	12–12	0.04	15%	6 Aug →
inferno	13–10	0.09	23%	6 Aug →
ancient	13–2	0.06	11%	6 Aug →
cache	13–4	-0.00	21%	6 Aug →
vertigo	13–9	0.02	17%	6 Aug →
nuke	11–13	0.05	20%	4 Aug →
anubis	13–10	0.07	22%	4 Aug →
vertigo	13–10	0.08	22%	4 Aug →
overpass	13–7	0.15	18%	4 Aug →
mirage	6–13	0.05	12%	4 Aug →
nuke	13–5	0.06	26%	4 Aug →
ancient	13–8	0.12	23%	4 Aug →
dust2	13–9	0.03	19%	4 Aug →
mirage	13–11	0.11	18%	4 Aug →
cache	13–11	0.04	12%	4 Aug →
inferno	13–11	0.06	23%	4 Aug →
overpass	13–5	0.18	29%	3 Aug →
vertigo	7–5	0.02	24%	3 Aug →
boulder	13–7	-0.03	21%	3 Aug →
cache	6–13	0.09	27%	3 Aug →
inferno	11–13	-0.03	26%	1 Aug →
nuke	13–5	-0.03	44%	1 Aug →
overpass	13–4	0.00	15%	1 Aug →
nuke	1–13	-0.03	16%	1 Aug →
vertigo	9–13	0.12	25%	1 Aug →
office	13–3	0.10	22%	1 Aug →