lirre — CS2 Stats

SE76561198421920168[U:1:461654440]Steam profile ↗1 game ban

3,261Tracked matches53%Win rate2020Tracked since

7,229Hours in CS27Hrs last 2 wks

CSDB Rating5.9 SolidAggressive Rifler

WingmanGold Nova III

Ladder ranks via Leetify

Performance scores

Aim85

Positioning61

Utility19

0–100 skill scores via Leetify.

Recent form

STEADY51–49Last 10051%Win rateLLWLWLWWWL

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

Player DNA

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

Aim8.5

Aggression7.9

Utility1.9

Positioning6.1

Opening Duels3.5

Clutch5.4

Sharp aimerStrong CT-side openerLimited utility dependence

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 87% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution.

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

CT openings. 63% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

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 63% on CT to 26% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 573ms 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

Aim8.5

Positioning6.1

Utility1.9

Mechanics5.2

Opening Duels4.1

Win Impact6.1

Composite 5.9/10 (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 rating0.03−0.00

first ⅓ avg 0.03 → last ⅓ avg 0.03

Reaction time570ms−27ms

first ⅓ avg 598ms → last ⅓ avg 570ms

Headshot accuracy31.9%+7.0%

first ⅓ avg 24.9% → last ⅓ avg 31.9%

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 — ancient 13–9

13–0Biggest win — cache

7Longest win streak

L2Current streak

10–9In matches decided by ≤2 rounds

19Overtime games

Map breakdown

ancientBest map · 72% over 18anubisWeakest map · 0% over 6

Map	Grade	Played	Record	Win rate	Avg rating
mirage	A	25	14–11	56%	0.03
ancient	S	18	13–5	72%	0.03
vertigo	A	14	8–6	57%	0.03
cache	B	13	6–7	46%	0.03
dust2	C	9	4–5	44%	0.03
anubis	D	6	0–6	0%	-0.01
train	D	6	2–4	33%	0.04
nuke	C	5	2–3	40%	-0.00
inferno	—	3	2–1	67%	0.02
overpass	—	1	0–1	0%	0.11

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (0% over 6). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

173,288Lifetime kills

0.87K/D

8,934Matches

47.0%Match win rate · Top 50% of tracked players

48.5%Headshot % · Top 50% of tracked players

15.9%Shot accuracy · Top 25% of tracked players

29,357MVPs

4,673Hours (in match)

5,010Bombs planted

3,276Bombs defused

Most-used weapons

AK-4758,773

M4A4 / M4A1-S30,008

AWP19,705

Desert Eagle13,177

P2000 / USP-S9,977

Knife9,634

Glock-186,381

FAMAS4,029

Galil AR3,609

MP92,397

Lifetime map wins

11,530vertigo

8,776inferno

6,226dust2

5,364nuke

4,205train

570cbble

165lake

118office

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

Faceit stats

Combat

2,901Matches

51%Win rate

1.03Avg K/D

85.5ADR

46%Headshot %

Clutches & streaks

47%1v1 clutch win

32%1v2 clutch win

11Longest win streak

Recent Faceit resultsWLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	225	52%	1.06	17.0
Ancient	155	57%	1.09	17.5
Anubis	129	51%	1.15	18.9
Vertigo	93	53%	1.31	20.4
Nuke	56	48%	1.18	19.0
Inferno	34	53%	0.99	17.8
Overpass	32	62%	1.02	16.3
Dust2	25	44%	1.04	17.3

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.

32.1%Headshot accuracy

36.4%Accuracy (enemy spotted)

37.6%Spray accuracy

73.5%Counter-strafing

9.5°Preaim

573msReaction time

25.5%T opening success

62.6%CT opening success

0.32Enemies flashed / flash

4.0%Flash assists

6.40HE damage / grenade

2.99Flashes / 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 0.3246 — 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 25.5307% — 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.

0% 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
anubis	6–13	-0.03	32%	29 Aug →
cache	4–13	-0.10	16%	29 Aug →
nuke	13–2	-0.03	10%	29 Aug →
mirage	10–13	0.10	33%	29 Aug →
mirage	13–4	0.01	29%	29 Aug →
dust2	9–13	0.03	35%	29 Aug →
mirage	13–6	0.04	41%	26 Aug →
mirage	13–8	-0.01	19%	26 Aug →
vertigo	13–11	0.09	35%	26 Aug →
cache	8–13	0.02	33%	26 Aug →
train	16–19	0.01	18%	25 Aug →
ancient	13–6	0.08	27%	25 Aug →
vertigo	13–16	0.01	61%	25 Aug →
dust2	12–16	-0.02	40%	24 Aug →
vertigo	13–11	0.04	35%	24 Aug →
vertigo	6–13	0.07	18%	24 Aug →
ancient	11–13	0.06	35%	24 Aug →
ancient	13–5	0.07	49%	23 Aug →
mirage	13–8	0.09	24%	23 Aug →
train	14–16	0.02	27%	23 Aug →
ancient	6–13	-0.04	55%	23 Aug →
ancient	13–7	-0.01	23%	23 Aug →
ancient	16–14	0.07	31%	23 Aug →
cache	13–0	0.08	31%	23 Aug →
vertigo	13–10	-0.05	34%	23 Aug →
cache	13–3	0.13	33%	22 Aug →
cache	5–13	0.01	33%	22 Aug →
mirage	14–16	0.02	37%	22 Aug →
dust2	16–13	-0.00	26%	22 Aug →
ancient	13–7	0.08	30%	22 Aug →
anubis	13–16	-0.01	27%	21 Aug →
dust2	9–13	0.01	39%	21 Aug →
vertigo	11–13	0.05	35%	21 Aug →
vertigo	13–8	0.02	42%	21 Aug →
vertigo	13–6	0.05	51%	21 Aug →
dust2	21–25	0.02	30%	20 Aug →
inferno	13–6	0.02	27%	20 Aug →
nuke	14–16	-0.02	19%	19 Aug →
anubis	3–13	-0.06	23%	19 Aug →
cache	13–5	0.06	29%	15 Aug →
train	7–13	0.06	39%	15 Aug →
anubis	9–13	0.00	10%	15 Aug →
ancient	8–13	-0.05	32%	15 Aug →
vertigo	16–14	0.02	34%	14 Aug →
cache	16–13	0.00	23%	14 Aug →
ancient	13–9	-0.01	13%	14 Aug →
mirage	13–2	-0.00	29%	11 Aug →
dust2	13–10	0.04	22%	9 Aug →
mirage	13–5	0.08	41%	9 Aug →
ancient	13–9	0.20	32%	9 Aug →
mirage	8–13	0.05	26%	9 Aug →
mirage	10–13	0.05	45%	8 Aug →
mirage	13–11	0.16	28%	8 Aug →
nuke	10–13	0.02	29%	7 Aug →
cache	3–13	-0.07	15%	5 Aug →
anubis	4–13	-0.01	38%	4 Aug →
mirage	5–13	-0.04	27%	4 Aug →
mirage	10–13	0.07	40%	2 Aug →
mirage	10–13	-0.01	28%	2 Aug →
ancient	22–20	-0.01	14%	1 Aug →
mirage	13–10	-0.02	33%	1 Aug →
train	7–13	-0.00	29%	31 Jul →
mirage	14–16	0.01	26%	31 Jul →
ancient	13–11	-0.02	13%	31 Jul →
cache	8–13	0.06	27%	31 Jul →
cache	13–9	0.08	28%	31 Jul →
mirage	4–13	0.09	25%	25 Jul →
vertigo	11–13	0.03	27%	23 Jul →
ancient	19–15	0.06	20%	22 Jul →
mirage	13–4	0.00	16%	22 Jul →
vertigo	13–8	0.08	38%	22 Jul →
anubis	11–13	0.03	23%	22 Jul →
mirage	9–13	-0.02	22%	22 Jul →
nuke	13–10	0.02	22%	22 Jul →
mirage	13–9	-0.04	27%	21 Jul →
ancient	13–11	0.01	17%	21 Jul →
mirage	13–4	0.01	28%	21 Jul →
vertigo	13–6	-0.01	26%	18 Jul →
vertigo	10–13	0.01	10%	18 Jul →
mirage	12–16	-0.06	24%	18 Jul →
inferno	0–8	0.01	37%	18 Jul →
mirage	13–7	-0.00	30%	17 Jul →
dust2	10–13	0.09	29%	11 Jul →
cache	13–7	0.02	30%	11 Jul →
dust2	13–4	0.02	31%	11 Jul →
cache	4–13	0.15	23%	11 Jul →
ancient	5–13	-0.03	22%	10 Jul →
train	13–9	0.08	27%	10 Jul →
train	13–5	0.08	45%	9 Jul →
mirage	13–3	-0.01	10%	9 Jul →
inferno	22–20	0.03	31%	3 Jul →
vertigo	11–13	0.05	27%	3 Jul →
ancient	16–14	0.01	19%	3 Jul →
ancient	9–13	0.06	25%	30 Jun →
dust2	13–3	0.06	28%	30 Jun →
mirage	13–7	0.12	26%	30 Jun →
overpass	13–16	0.11	26%	30 Jun →
ancient	13–9	0.02	19%	29 Jun →
cache	6–13	-0.02	15%	29 Jun →
nuke	5–13	-0.01	18%	29 Jun →