$lim — CS2 Stats

76561198271863486[U:1:311597758]

1,244Tracked matches44%Win rate2020Tracked since

CSDB Rating4.8 DevelopingHybrid Rifler

FaceitLevel 9 · 1,723 ELOTop 20.7% of ranked FACEIT players

WingmanGold Nova Master

Ladder ranks via Leetify

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Performance scores

Aim62

Positioning49

Utility42

0–100 skill scores via Leetify.

Recent form

COLD49–40–11Last 10049%Win rateLLLWTWWLLL

Last 10 vs previous 10: +0pp win rate · -0.03 avg rating

Player DNA

Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.

Aim6.2

Aggression5.0

Utility4.2

Positioning4.9

Opening Duels2.8

Clutch4.4

Strong 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 NiKo 85% playstyle similarity

Most alike: opening-fight frequency, opening-duel success.

Where you differ: lower utility contribution; 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

T-side openings. Opening success drops from 55% on CT to 27% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 622ms 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

Aim6.2

Positioning4.9

Utility4.2

Mechanics6.4

Opening Duels3.1

Win Impact3.1

Composite 4.8/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 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 time620ms−32ms

first ⅓ avg 651ms → last ⅓ avg 620ms

Headshot accuracy15.3%−0.6%

first ⅓ avg 16.0% → last ⅓ avg 15.3%

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 — train 13–3

13–2Biggest win — office

4Longest win streak

L3Current streak

5–8In matches decided by ≤2 rounds

8Overtime games

Map breakdown

dust2Best map · 57% over 42overpassWeakest map · 33% over 9

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	42	24–18	57%	0.01
ancient	C	10	4–6	40%	-0.02
inferno	C	10	4–6	40%	-0.01
overpass	D	9	3–6	33%	0.00
office	A	7	4–3	57%	0.01
train	D	6	2–4	33%	0.03
nuke	B	6	3–3	50%	0.02
mirage	—	4	2–2	50%	0.02
vertigo	—	4	3–1	75%	-0.01
cache	—	1	0–1	0%	-0.06
anubis	—	1	0–1	0%	-0.06

Across the last 100 tracked matches.

Overpass is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Overpass lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

388Matches

56%Win rate

1.04Avg K/D

80.9ADR

45%Headshot %

Clutches & streaks

42%1v1 clutch win

22%1v2 clutch win

7Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	128	61%	1.15	16.0
Overpass	46	50%	0.94	14.5
Mirage	42	50%	0.91	13.7
Nuke	39	46%	0.90	13.6
Inferno	34	59%	0.96	14.2
Ancient	30	53%	0.90	14.6
Cache	9	56%	0.98	14.9
Vertigo	7	57%	1.21	20.4

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.

15.8%Headshot accuracy

33.9%Accuracy (enemy spotted)

35.6%Spray accuracy

78.9%Counter-strafing

9.3°Preaim

622msReaction time

27.3%T opening success

55.0%CT opening success

0.34Enemies flashed / flash

6.2%Flash assists

11.12HE damage / grenade

8.74Flashes / 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
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.3429 — below the 0.5 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 27.3407% — below the 40% mark we flag

Spend your practice time on Overpass

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

Overpass callouts & strategy →Overpass grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
cache	4–13	-0.06	6%	26 Aug →
ancient	5–9	-0.05	10%	24 Aug →
ancient	11–13	-0.04	22%	22 Aug →
dust2	13–5	-0.03	12%	21 Aug →
inferno	8–8	0.07	28%	16 Jul →
dust2	13–5	-0.03	11%	16 Jul →
dust2	13–10	0.04	7%	16 Jul →
dust2	10–13	0.05	9%	15 Jul →
office	9–13	0.08	27%	13 Jul →
office	9–13	-0.06	15%	13 Jul →
dust2	13–8	0.01	16%	12 Jul →
overpass	5–7	-0.00	31%	5 Jul →
dust2	9–13	0.01	23%	24 Jun →
dust2	12–12	0.01	21%	24 Jun →
dust2	13–6	0.00	11%	24 Jun →
train	12–12	0.01	16%	20 Jun →
train	13–3	0.11	20%	20 Jun →
ancient	13–16	-0.04	14%	14 Jun →
mirage	5–13	0.04	23%	10 Jun →
nuke	7–9	0.10	8%	6 Jun →
vertigo	13–5	-0.02	20%	6 Jun →
vertigo	13–11	0.03	11%	6 Jun →
anubis	12–12	-0.06	20%	29 May →
inferno	13–11	0.08	17%	24 May →
dust2	7–13	-0.01	23%	24 May →
dust2	13–7	0.04	11%	24 May →
nuke	10–13	0.01	19%	19 May →
office	13–2	-0.02	9%	18 May →
office	11–13	-0.06	15%	18 May →
inferno	0–4	-0.03	0%	3 May →
nuke	13–7	0.02	12%	24 Apr →
inferno	7–13	-0.01	12%	23 Apr →
train	13–7	0.04	8%	22 Apr →
overpass	6–13	-0.04	18%	21 Apr →
dust2	13–8	-0.00	20%	21 Apr →
dust2	13–10	0.01	19%	21 Apr →
overpass	13–7	-0.07	11%	21 Apr →
inferno	9–4	0.05	38%	20 Apr →
dust2	6–13	0.05	13%	19 Apr →
overpass	8–13	-0.03	16%	19 Apr →
dust2	10–13	0.05	15%	16 Apr →
overpass	16–12	0.05	20%	12 Apr →
vertigo	13–5	-0.03	15%	8 Apr →
dust2	6–13	-0.04	38%	8 Apr →
inferno	6–13	-0.04	18%	2 Apr →
dust2	13–7	0.01	23%	2 Apr →
dust2	15–15	0.00	19%	28 Mar →
ancient	13–11	-0.02	11%	26 Mar →
mirage	13–7	0.02	21%	25 Mar →
overpass	8–8	-0.01	5%	25 Mar →
dust2	13–6	0.07	22%	25 Mar →
dust2	13–9	-0.01	11%	25 Mar →
overpass	11–13	0.04	17%	23 Mar →
office	13–5	0.05	24%	18 Mar →
inferno	13–11	0.03	21%	18 Mar →
ancient	7–13	-0.10	27%	18 Mar →
inferno	7–9	-0.20	11%	11 Mar →
dust2	4–13	0.06	23%	11 Mar →
overpass	13–2	0.03	16%	11 Mar →
dust2	16–13	0.02	16%	8 Mar →
dust2	13–8	0.03	30%	5 Mar →
dust2	8–13	-0.06	17%	4 Mar →
dust2	13–5	0.06	22%	4 Mar →
dust2	11–13	0.05	24%	4 Mar →
dust2	12–12	0.03	35%	3 Mar →
dust2	13–2	-0.03	14%	2 Mar →
dust2	13–9	0.05	19%	25 Feb →
train	12–12	0.04	27%	25 Feb →
train	8–13	0.01	25%	25 Feb →
dust2	13–6	0.05	14%	23 Feb →
dust2	13–7	0.03	12%	23 Feb →
ancient	13–5	0.08	15%	8 Feb →
dust2	9–13	-0.15	0%	30 Jan →
dust2	13–5	0.05	17%	30 Jan →
overpass	10–13	0.05	26%	28 Jan →
office	13–8	-0.02	14%	23 Jan →
office	13–6	0.08	18%	23 Jan →
inferno	16–13	-0.02	14%	21 Jan →
ancient	15–15	0.01	16%	10 Jan →
dust2	13–4	0.04	20%	9 Jan →
dust2	5–13	-0.04	12%	9 Jan →
dust2	13–6	0.02	10%	9 Jan →
mirage	6–13	0.04	9%	9 Jan →
dust2	13–10	0.04	17%	7 Jan →
dust2	13–5	0.05	13%	4 Jan →
dust2	7–13	-0.02	13%	3 Jan →
dust2	9–13	-0.04	15%	24 Dec →
dust2	11–13	0.03	25%	24 Dec →
ancient	16–13	-0.01	17%	23 Dec →
dust2	8–3	0.09	20%	22 Dec →
dust2	15–15	-0.01	20%	21 Dec →
train	8–13	-0.01	6%	21 Dec →
inferno	4–13	-0.02	17%	20 Dec →
nuke	13–9	0.03	10%	18 Dec →
mirage	13–10	-0.02	16%	16 Dec →
ancient	8–1	0.03	20%	16 Dec →
nuke	13–11	0.03	13%	16 Dec →
ancient	3–13	-0.05	11%	12 Dec →
nuke	4–9	-0.07	15%	6 Dec →
vertigo	8–8	0.00	32%	6 Dec →