miem94 — CS2 Stats

FI76561198363749399[U:1:403483671]Steam profile ↗✓ No bans

721Tracked matches63%Win rate2020Tracked since

CSDB Rating6.3 SolidAggressive Rifler

FaceitLevel 10 · 2,145 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim78

Positioning64

Utility25

0–100 skill scores via Leetify.

Recent form

STEADY55–40–5Last 10055%Win rateWLLLWWWLWW

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

Player DNA

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

Aim7.8

Aggression8.6

Utility2.5

Positioning6.4

Opening Duels3.6

Clutch3.2

Limited 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 jL 86% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: lower aim profile; 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

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 575ms 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

Aim7.8

Positioning6.4

Utility2.5

Mechanics6.4

Opening Duels3.6

Win Impact9.4

Composite 6.3/10 (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 rating0.01−0.01

first ⅓ avg 0.02 → last ⅓ avg 0.01

Reaction time571ms−90ms

first ⅓ avg 661ms → last ⅓ avg 571ms

Headshot accuracy21.9%−7.1%

first ⅓ avg 29.0% → last ⅓ avg 21.9%

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

0.16Best rating — mirage 13–1

13–1Biggest win — mirage

5Longest win streak

7–6In matches decided by ≤2 rounds

8Overtime games

Map breakdown

anubisBest map · 80% over 5infernoWeakest map · 22% over 9

Map	Grade	Played	Record	Win rate	Avg rating
mirage	S	28	20–8	71%	0.03
nuke	B	19	10–9	53%	0.01
cache	A	10	6–4	60%	0.03
dust2	C	10	4–6	40%	0.03
inferno	D	9	2–7	22%	0.02
ancient	D	8	2–6	25%	0.02
anubis	S	5	4–1	80%	0.01
overpass	—	4	2–2	50%	-0.02
vertigo	—	3	1–2	33%	0.01
train	—	2	2–0	100%	0.06
office	—	1	1–0	100%	0.01
agency	—	1	1–0	100%	0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (22% over 9). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

617Matches

54%Win rate

1.10Avg K/D

82.1ADR

54%Headshot %

Clutches & streaks

36%1v1 clutch win

23%1v2 clutch win

10Longest win streak

Recent Faceit resultsWLLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	208	52%	1.13	17.4
Nuke	76	51%	1.08	17.6
Ancient	67	48%	1.07	16.9
Dust2	65	49%	1.09	17.2
Inferno	53	60%	1.06	15.7
Anubis	45	58%	1.09	17.0
Cache	16	75%	1.18	16.5
Train	14	79%	1.14	14.9

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.

21.0%Headshot accuracy

35.3%Accuracy (enemy spotted)

41.5%Spray accuracy

78.8%Counter-strafing

9.5°Preaim

575msReaction time

39.9%T opening success

49.2%CT opening success

0.38Enemies flashed / flash

3.4%Flash assists

4.56HE damage / grenade

1.39Flashes / 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 0.3809 — 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 39.9402% — 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.

22% 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
cache	13–9	0.02	18%	29 Aug →
mirage	9–13	-0.05	21%	28 Aug →
inferno	8–13	0.02	21%	28 Aug →
ancient	7–13	-0.06	23%	28 Aug →
nuke	13–7	-0.00	14%	26 Aug →
anubis	13–11	0.00	19%	22 Aug →
nuke	16–13	0.05	18%	20 Aug →
cache	9–13	-0.01	19%	20 Aug →
anubis	13–5	-0.01	23%	18 Aug →
mirage	13–3	-0.03	26%	18 Aug →
vertigo	4–13	-0.04	35%	18 Aug →
nuke	5–13	-0.02	20%	17 Aug →
vertigo	13–4	0.08	27%	7 Aug →
mirage	5–13	-0.04	24%	5 Aug →
mirage	8–13	-0.03	29%	1 Aug →
inferno	13–10	0.07	28%	1 Aug →
mirage	11–2	0.01	15%	31 Jul →
mirage	13–3	0.07	18%	31 Jul →
cache	13–4	0.02	30%	30 Jul →
mirage	13–3	0.08	27%	29 Jul →
dust2	7–13	-0.03	31%	20 Jul →
mirage	13–6	0.10	31%	19 Jul →
mirage	13–9	0.06	11%	14 Jul →
cache	13–6	-0.02	9%	14 Jul →
nuke	13–10	-0.03	19%	14 Jul →
cache	13–7	-0.01	9%	14 Jul →
anubis	11–13	0.03	13%	14 Jul →
cache	13–6	0.14	25%	14 Jul →
nuke	5–13	-0.06	18%	14 Jul →
dust2	13–5	0.02	15%	26 Jun →
nuke	13–10	-0.00	21%	21 Jun →
mirage	17–19	-0.04	21%	13 Jun →
cache	9–13	0.08	41%	8 Jun →
dust2	6–13	0.07	38%	6 Jun →
anubis	13–6	0.04	25%	3 Jun →
nuke	13–8	0.05	15%	1 Jun →
mirage	13–5	0.12	20%	1 Jun →
mirage	13–6	0.11	15%	29 May →
inferno	13–3	-0.02	9%	29 May →
dust2	9–13	0.01	32%	29 May →
cache	6–13	-0.02	18%	29 May →
ancient	15–15	0.03	12%	21 May →
mirage	13–5	0.01	28%	16 May →
mirage	10–13	-0.04	17%	15 May →
mirage	13–6	0.09	36%	15 May →
nuke	9–13	0.02	17%	15 May →
inferno	7–13	0.03	32%	13 May →
cache	13–8	0.03	25%	12 May →
mirage	13–8	-0.06	15%	12 May →
mirage	13–1	0.16	50%	12 May →
ancient	13–8	0.01	19%	12 May →
mirage	16–13	0.04	19%	5 May →
ancient	11–13	0.05	22%	5 May →
nuke	13–7	0.12	28%	3 May →
dust2	10–13	0.02	20%	1 May →
cache	12–12	0.11	25%	29 Apr →
mirage	13–10	0.12	25%	13 Apr →
dust2	15–15	0.09	23%	2 Apr →
mirage	13–9	0.08	32%	30 Mar →
dust2	13–10	0.07	24%	28 Mar →
inferno	9–13	0.01	19%	15 Mar →
nuke	13–4	0.08	15%	15 Mar →
nuke	1–13	-0.08	24%	15 Mar →
nuke	0–13	-0.02	30%	13 Mar →
anubis	13–5	-0.00	26%	4 Mar →
mirage	13–3	0.09	17%	4 Mar →
inferno	4–13	-0.07	24%	3 Mar →
nuke	13–11	0.02	27%	18 Feb →
nuke	16–14	0.04	30%	14 Feb →
vertigo	12–12	-0.01	13%	6 Feb →
office	13–4	0.01	28%	4 Feb →
inferno	12–12	0.04	33%	4 Feb →
mirage	11–13	-0.04	46%	2 Feb →
dust2	13–11	-0.02	34%	15 Jan →
overpass	8–13	0.01	34%	9 Jan →
mirage	9–13	0.00	48%	7 Jan →
overpass	13–11	-0.01	14%	6 Jan →
train	16–12	0.12	36%	5 Jan →
ancient	7–13	-0.01	42%	1 Jan →
nuke	10–13	0.06	55%	1 Jan →
inferno	8–13	0.09	23%	1 Jan →
ancient	13–2	0.09	23%	30 Dec →
inferno	9–13	0.01	36%	30 Dec →
nuke	6–13	0.03	21%	27 Dec →
mirage	7–13	-0.05	27%	27 Dec →
nuke	11–13	-0.02	46%	26 Dec →
nuke	13–10	0.07	25%	24 Dec →
train	13–1	0.01	29%	24 Dec →
overpass	13–9	-0.06	11%	22 Dec →
mirage	13–11	0.06	19%	22 Dec →
nuke	11–13	-0.02	32%	20 Dec →
ancient	10–13	0.04	19%	15 Dec →
mirage	13–3	0.10	23%	15 Dec →
mirage	13–10	0.04	17%	15 Dec →
dust2	13–5	0.08	25%	14 Dec →
overpass	5–13	-0.02	32%	8 Dec →
ancient	6–13	0.02	26%	6 Dec →
agency	13–3	0.01	21%	5 Dec →
dust2	2–13	-0.01	29%	29 Nov →
mirage	16–14	-0.02	31%	12 Nov →