[BB] Majky^-^ — CS2 Stats

76561198043271405[U:1:83005677]Steam profile ↗✓ No bans

494Tracked matches59%Win rate2023Tracked since

CSDB Rating5.7 SolidAggressive Rifler

Premier CS Rating11,447Blue band · top ~47.2% of ranked players (population est.)

CSDB Leaderboard#29034 of 41507 tracked

WingmanGold Nova III

Ladder ranks via Leetify

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Performance scores

Aim73

Positioning48

Utility46

0–100 skill scores via Leetify.

Recent form

STEADY54–42–4Last 10054%Win rateLWLLWWLLWL

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.

Aim7.3

Aggression7.5

Utility4.6

Positioning4.8

Opening Duels3.4

Strong 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 b1t 89% 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 51% on CT to 36% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 586ms 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

Aim7.3

Positioning4.8

Utility4.6

Mechanics6.7

Opening Duels3.4

Win Impact7.9

Composite 5.7/10 (Solid), 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 rating-0.01−0.02

first ⅓ avg 0.01 → last ⅓ avg -0.01

Reaction time587ms−52ms

first ⅓ avg 639ms → last ⅓ avg 587ms

Headshot accuracy13.8%−2.9%

first ⅓ avg 16.7% → last ⅓ avg 13.8%

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

0.12Best rating — ancient 13–2

13–1Biggest win — overpass

5Longest win streak

8–5In matches decided by ≤2 rounds

9Overtime games

Map breakdown

infernoBest map · 80% over 20anubisWeakest map · 20% over 10

Map	Grade	Played	Record	Win rate	Avg rating
inferno	S	20	16–4	80%	0.02
ancient	A	20	11–9	55%	0.01
nuke	D	18	5–13	28%	-0.00
overpass	A	16	9–7	56%	0.01
anubis	D	10	2–8	20%	-0.02
mirage	S	8	6–2	75%	0.02
dust2	C	5	2–3	40%	-0.00
train	—	3	3–0	100%	0.04

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (20% over 10). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

17Matches

41%Win rate

0.77Avg K/D

—ADR

33%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

3Longest win streak

Recent Faceit resultsLLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	4	25%	0.99	14.3
Mirage	2	0%	0.98	18.5
Overpass	1	100%	1.24	21.0
Nuke	1	100%	0.89	17.0
Vertigo	1	0%	0.38	5.0

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.

13.3%Headshot accuracy

36.0%Accuracy (enemy spotted)

37.1%Spray accuracy

80.4%Counter-strafing

7.5°Preaim

586msReaction time

35.5%T opening success

51.3%CT opening success

0.70Enemies flashed / flash

2.4%Flash assists

11.63HE damage / grenade

2.21Flashes / 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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 13.2786% — below the 15% mark we flag
Aim Training →
Grenades & Utility
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 2.2105 — below the 4 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 35.5443% — 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.

20% win rate across 10 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
inferno	8–13	0.01	13%	3 Jul →
nuke	13–4	0.02	15%	3 Jul →
anubis	7–13	-0.04	14%	3 Jul →
ancient	8–13	-0.08	6%	8 Jun →
ancient	16–13	-0.07	13%	6 Jun →
dust2	13–7	0.03	16%	6 Jun →
overpass	9–13	-0.04	12%	6 Jun →
anubis	7–13	-0.02	8%	5 Jun →
overpass	16–13	-0.03	7%	5 Jun →
anubis	2–13	0.03	16%	5 Jun →
inferno	13–4	0.07	6%	29 May →
anubis	13–9	-0.00	37%	29 May →
inferno	13–11	-0.05	18%	29 May →
mirage	9–13	0.00	15%	29 May →
ancient	13–2	0.12	20%	22 May →
mirage	13–8	0.02	16%	22 May →
anubis	11–13	-0.04	10%	22 May →
inferno	13–4	-0.02	12%	13 May →
inferno	13–3	-0.00	5%	13 May →
anubis	10–13	-0.05	13%	13 May →
nuke	10–13	-0.05	6%	13 May →
ancient	13–11	0.03	12%	13 May →
overpass	13–10	0.03	13%	8 May →
anubis	9–13	-0.02	18%	8 May →
nuke	6–13	-0.04	28%	30 Apr →
overpass	13–9	0.03	13%	30 Apr →
inferno	13–9	0.00	4%	30 Apr →
anubis	13–11	-0.01	9%	30 Apr →
dust2	13–9	0.02	24%	24 Apr →
inferno	15–15	-0.06	8%	24 Apr →
ancient	13–9	-0.03	26%	24 Apr →
mirage	13–6	0.03	18%	24 Apr →
anubis	5–13	-0.06	7%	17 Apr →
inferno	13–5	0.11	18%	17 Apr →
ancient	13–2	0.03	22%	17 Apr →
mirage	13–5	0.08	20%	17 Apr →
nuke	7–13	-0.05	8%	17 Apr →
overpass	13–5	0.05	17%	17 Apr →
overpass	13–8	0.07	20%	17 Apr →
ancient	13–5	0.06	39%	17 Apr →
dust2	15–15	0.01	13%	10 Apr →
nuke	9–13	0.03	7%	10 Apr →
ancient	13–10	0.08	26%	10 Apr →
ancient	11–13	-0.09	9%	10 Apr →
ancient	12–16	-0.03	12%	2 Apr →
nuke	13–8	-0.01	12%	2 Apr →
inferno	13–9	0.01	5%	2 Apr →
nuke	6–13	0.00	8%	27 Mar →
inferno	7–13	0.01	11%	27 Mar →
mirage	13–10	-0.01	20%	27 Mar →
nuke	14–16	-0.02	19%	20 Mar →
inferno	13–10	-0.03	21%	20 Mar →
ancient	13–5	0.01	8%	20 Mar →
nuke	13–6	-0.01	11%	6 Mar →
inferno	7–13	-0.02	13%	6 Mar →
ancient	2–13	0.02	40%	6 Mar →
dust2	5–13	-0.02	19%	30 Jan →
nuke	10–13	0.00	8%	30 Jan →
overpass	10–13	-0.02	17%	23 Jan →
nuke	14–16	-0.03	21%	23 Jan →
inferno	13–7	0.10	23%	23 Jan →
mirage	13–11	0.03	15%	23 Jan →
anubis	8–13	0.00	18%	23 Jan →
train	13–9	0.07	14%	17 Jan →
ancient	4–13	0.03	10%	17 Jan →
mirage	13–5	0.04	19%	17 Jan →
train	16–12	0.01	11%	16 Jan →
inferno	13–11	0.08	23%	16 Jan →
inferno	13–9	0.00	26%	16 Jan →
nuke	13–7	0.06	25%	16 Jan →
ancient	12–12	0.02	24%	16 Jan →
inferno	9–3	0.09	20%	16 Jan →
overpass	10–13	0.02	20%	10 Jan →
ancient	13–3	0.04	35%	10 Jan →
overpass	13–8	0.03	12%	10 Jan →
dust2	8–13	-0.03	23%	10 Jan →
nuke	9–13	-0.04	6%	9 Jan →
inferno	13–7	0.08	13%	9 Jan →
train	13–4	0.05	7%	9 Jan →
ancient	7–13	-0.04	9%	9 Jan →
ancient	13–10	-0.04	14%	8 Jan →
mirage	9–13	-0.05	9%	8 Jan →
overpass	8–13	-0.00	17%	7 Jan →
inferno	13–8	-0.01	24%	7 Jan →
nuke	11–13	-0.03	19%	26 Dec →
ancient	7–13	0.04	22%	19 Dec →
nuke	6–13	-0.00	9%	19 Dec →
overpass	13–11	0.01	5%	19 Dec →
ancient	13–11	0.03	20%	19 Dec →
overpass	6–9	-0.07	3%	19 Dec →
nuke	5–9	0.07	4%	19 Dec →
inferno	9–7	0.07	9%	19 Dec →
inferno	13–9	0.04	26%	12 Dec →
nuke	13–6	-0.00	19%	12 Dec →
overpass	13–9	0.05	30%	12 Dec →
overpass	13–1	0.00	27%	5 Dec →
nuke	15–15	0.02	18%	5 Dec →
overpass	5–13	-0.07	10%	5 Dec →
overpass	8–13	0.03	9%	28 Nov →
ancient	9–13	0.04	15%	28 Nov →