m1kker — CS2 Stats

76561198017513816[U:1:57248088]

718Tracked matches64%Win rate2020Tracked since

CSDB Rating6.9 SolidHybrid Rifler

FaceitLevel 10 · 2,436 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

Share this profile

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim86

Positioning54

Utility68

0–100 skill scores via Leetify.

Recent form

STEADY67–28–5Last 10067%Win rateLWTLTWLWWW

Last 10 vs previous 10: -20pp win rate · +0.02 avg rating

Player DNA

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

Aim8.6

Aggression6.4

Utility6.8

Positioning5.4

Opening Duels2.4

Clutch2.0

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 Twistzz 96% playstyle similarity

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

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 86 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 32 points — deaths here waste a strong aim profile.

T-side openings. Opening success drops from 48% on CT to 32% 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

Aim8.6

Positioning5.4

Utility6.8

Mechanics6.7

Opening Duels2.4

Win Impact9.8

Composite 6.9/10 (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 rating0.03−0.02

first ⅓ avg 0.05 → last ⅓ avg 0.03

Reaction time541ms−54ms

first ⅓ avg 596ms → last ⅓ avg 541ms

Headshot accuracy24.7%+1.3%

first ⅓ avg 23.3% → last ⅓ avg 24.7%

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

0.16Best rating — nuke 13–0

13–0Biggest win — nuke

7Longest win streak

8–3In matches decided by ≤2 rounds

2Overtime games

Map breakdown

ancientBest map · 89% over 9mirageWeakest map · 47% over 15

Map	Grade	Played	Record	Win rate	Avg rating
train	S	17	14–3	82%	0.05
mirage	B	15	7–8	47%	0.04
cache	S	12	8–4	67%	0.04
anubis	S	12	8–4	67%	-0.01
inferno	S	9	6–3	67%	0.02
ancient	S	9	8–1	89%	0.01
nuke	S	9	7–2	78%	0.04
agency	B	8	4–4	50%	0.05
overpass	—	4	3–1	75%	0.02
dust2	—	2	0–2	0%	-0.03
grail	—	2	2–0	100%	0.07
jura	—	1	0–1	0%	0.05

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (47% over 15). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,153Matches

54%Win rate

1.29Avg K/D

75.6ADR

45%Headshot %

Clutches & streaks

30%1v1 clutch win

34%1v2 clutch win

8Longest win streak

Recent Faceit resultsLWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Nuke	21	52%	1.18	17.7
Ancient	20	75%	1.11	16.9
Mirage	19	32%	0.97	12.9
Anubis	18	50%	1.04	14.5
Inferno	8	50%	0.75	11.4
Cache	8	62%	1.46	14.5
Dust2	7	57%	1.01	15.6
Overpass	4	25%	0.83	14.0

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.

25.6%Headshot accuracy

36.3%Accuracy (enemy spotted)

39.0%Spray accuracy

80.2%Counter-strafing

9.0°Preaim

537msReaction time

31.7%T opening success

47.8%CT opening success

0.65Enemies flashed / flash

7.6%Flash assists

9.78HE damage / grenade

8.98Flashes / 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 31.6642% — below the 40% mark we flag

Spend your practice time on Mirage

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

47% win rate across 15 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	8–13	0.11	22%	30 Aug →
inferno	13–9	0.03	34%	28 Aug →
overpass	12–12	0.03	28%	13 Aug →
cache	9–13	-0.02	19%	12 Aug →
cache	12–12	0.04	15%	5 Aug →
inferno	13–5	0.10	26%	4 Aug →
mirage	1–13	-0.06	16%	4 Aug →
mirage	13–2	0.13	17%	31 Jul →
mirage	13–6	0.05	22%	28 Jul →
cache	13–11	0.10	29%	28 Jul →
cache	8–13	-0.00	26%	23 May →
inferno	12–16	-0.01	29%	23 May →
ancient	13–9	0.04	29%	23 May →
cache	13–11	0.08	26%	20 May →
cache	13–5	0.06	31%	20 May →
cache	13–10	0.04	38%	20 May →
cache	9–13	-0.01	35%	19 May →
cache	13–2	0.01	26%	19 May →
cache	13–5	0.10	23%	19 May →
anubis	13–11	-0.00	24%	19 May →
cache	13–5	0.03	18%	16 May →
cache	13–7	0.04	30%	10 May →
anubis	9–13	-0.00	21%	10 May →
anubis	13–7	-0.02	23%	25 Apr →
ancient	1–13	-0.04	35%	25 Apr →
anubis	5–13	-0.07	27%	25 Apr →
nuke	13–10	0.07	22%	25 Apr →
inferno	13–7	-0.01	23%	31 Mar →
nuke	13–0	0.16	31%	31 Mar →
nuke	10–13	-0.03	24%	14 Mar →
anubis	13–0	0.08	27%	14 Mar →
anubis	3–13	-0.09	0%	14 Mar →
inferno	3–13	-0.04	21%	14 Mar →
ancient	16–13	0.01	12%	14 Mar →
nuke	13–4	0.04	30%	14 Mar →
dust2	11–13	-0.02	20%	14 Mar →
inferno	13–10	-0.01	32%	14 Mar →
ancient	13–3	0.04	27%	14 Mar →
inferno	13–10	-0.06	9%	14 Mar →
ancient	13–6	0.06	30%	14 Mar →
anubis	13–11	0.05	36%	14 Mar →
mirage	10–13	-0.02	30%	14 Mar →
mirage	7–13	0.00	26%	14 Mar →
ancient	13–11	-0.05	31%	14 Mar →
inferno	13–9	0.06	16%	14 Mar →
mirage	13–3	0.01	23%	14 Mar →
mirage	6–13	-0.02	29%	26 Dec →
overpass	13–10	0.00	32%	17 Jul →
overpass	13–9	-0.02	23%	17 Jul →
mirage	12–12	0.01	33%	27 Jun →
nuke	13–8	0.05	30%	27 Jun →
ancient	11–6	0.02	25%	23 Jun →
anubis	13–4	0.01	25%	23 Jun →
anubis	4–13	-0.05	19%	23 Jun →
agency	13–11	0.04	26%	6 Jun →
agency	13–5	0.13	38%	31 May →
agency	4–4	0.05	23%	31 May →
mirage	12–12	0.12	30%	31 May →
mirage	2–4	-0.03	17%	31 May →
overpass	13–4	0.06	22%	31 May →
train	8–13	-0.00	21%	31 May →
anubis	13–7	0.05	30%	16 May →
nuke	13–10	-0.01	30%	16 May →
agency	13–0	0.04	39%	16 May →
ancient	13–10	0.02	16%	16 May →
mirage	13–10	0.11	34%	16 May →
ancient	13–10	0.01	34%	14 May →
train	13–6	0.01	22%	14 May →
mirage	9–13	0.01	22%	14 May →
nuke	13–5	0.09	25%	14 May →
agency	0–13	-0.03	55%	10 May →
agency	13–3	0.09	31%	10 May →
grail	13–8	0.08	31%	10 May →
grail	13–7	0.05	33%	10 May →
anubis	13–7	-0.01	14%	10 May →
agency	10–13	0.02	27%	10 May →
agency	9–13	0.06	26%	9 May →
jura	12–12	0.05	20%	9 May →
nuke	13–11	0.02	27%	30 Apr →
anubis	13–9	-0.01	23%	30 Apr →
mirage	13–7	0.07	30%	30 Apr →
dust2	9–13	-0.03	28%	28 Apr →
mirage	13–3	0.15	23%	28 Apr →
nuke	3–13	-0.03	9%	28 Apr →
mirage	13–11	0.09	25%	28 Apr →
train	13–10	0.06	23%	27 Apr →
train	13–7	0.03	18%	27 Apr →
train	13–9	0.02	21%	27 Apr →
train	13–4	0.07	18%	27 Apr →
train	13–7	0.04	18%	27 Apr →
train	13–1	0.06	30%	27 Apr →
train	7–13	-0.02	17%	25 Apr →
train	13–2	0.07	16%	25 Apr →
train	13–8	0.05	16%	25 Apr →
train	13–5	-0.01	14%	25 Apr →
train	13–9	0.14	22%	25 Apr →
train	9–13	0.02	14%	23 Apr →
train	13–2	0.06	21%	23 Apr →
train	13–5	0.13	22%	23 Apr →
train	13–0	0.10	29%	23 Apr →