Mak — CS2 Stats

76561197974890458[U:1:14624730]

1,196Tracked matches50%Win rate2022Tracked since

CSDB Rating5.9 SolidAggressive Rifler

Premier CS Rating22,305Top 50% of 819 CSDB-tracked playersPink band · top ~6% of ranked players (population est.)

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

Aim76

Positioning61

Utility29

0–100 skill scores via Leetify.

Recent form

STEADY52–40–8Last 10052%Win rateLWLWWLLLWW

Last 10 vs previous 10: +10pp win rate · -0.05 avg rating

Player DNA

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

Aim7.6

Aggression7.9

Utility2.9

Positioning6.1

Opening Duels3.3

Clutch6.0

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 88% playstyle similarity

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

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.

T-side openings. Opening success drops from 53% on CT to 33% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 550ms 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

Aim7.6

Positioning6.1

Utility2.9

Mechanics6.5

Opening Duels3.3

Win Impact5.0

Composite 5.9/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 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 time557ms−33ms

first ⅓ avg 590ms → last ⅓ avg 557ms

Headshot accuracy19.9%+2.2%

first ⅓ avg 17.7% → last ⅓ avg 19.9%

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

0.13Best rating — cache 13–9

13–0Biggest win — mirage

6Longest win streak

7–6In matches decided by ≤2 rounds

2Overtime games

Map breakdown

mirageBest map · 69% over 16infernoWeakest map · 38% over 16

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	18	9–9	50%	0.02
mirage	S	16	11–5	69%	0.01
inferno	C	16	6–10	38%	-0.00
cache	A	12	7–5	58%	0.02
ancient	B	10	5–5	50%	-0.01
nuke	S	9	6–3	67%	0.00
vertigo	A	8	5–3	63%	0.01
train	C	7	3–4	43%	0.01
anubis	—	2	0–2	0%	-0.02
office	—	1	0–1	0%	-0.02
overpass	—	1	0–1	0%	0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 16). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

15Matches

53%Win rate

1.32Avg K/D

76.8ADR

40%Headshot %

Clutches & streaks

50%1v1 clutch win

0%1v2 clutch win

2Longest win streak

Recent Faceit resultsWWLWW

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.

20.2%Headshot accuracy

34.8%Accuracy (enemy spotted)

34.1%Spray accuracy

79.1%Counter-strafing

8.7°Preaim

550msReaction time

33.1%T opening success

53.4%CT opening success

0.43Enemies flashed / flash

1.1%Flash assists

10.32HE damage / grenade

4.10Flashes / 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 0.4344 — 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 33.0577% — 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.

38% win rate across 16 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
mirage	6–13	-0.05	7%	19 Aug →
ancient	13–11	-0.02	24%	18 Aug →
nuke	6–13	-0.05	16%	18 Aug →
dust2	13–7	-0.01	13%	17 Aug →
inferno	13–8	-0.05	26%	17 Aug →
office	8–13	-0.02	17%	16 Aug →
anubis	8–13	-0.01	17%	16 Aug →
ancient	4–13	-0.05	26%	16 Aug →
nuke	13–10	0.04	19%	13 Aug →
train	13–8	-0.04	21%	12 Aug →
inferno	11–13	0.01	19%	9 Aug →
overpass	12–12	0.01	11%	9 Aug →
cache	10–13	0.04	11%	9 Aug →
vertigo	13–6	0.10	16%	9 Aug →
mirage	6–13	0.00	16%	9 Aug →
cache	10–13	0.03	22%	8 Aug →
dust2	13–11	0.03	24%	8 Aug →
mirage	13–6	-0.02	25%	7 Aug →
vertigo	6–13	0.01	45%	7 Aug →
mirage	13–1	0.04	21%	6 Aug →
ancient	8–13	-0.06	20%	5 Aug →
dust2	12–12	0.06	17%	5 Aug →
nuke	13–5	0.02	39%	4 Aug →
cache	13–5	0.02	22%	4 Aug →
dust2	13–7	0.12	32%	3 Aug →
nuke	13–10	-0.05	9%	3 Aug →
mirage	7–13	0.05	24%	3 Aug →
ancient	9–13	0.02	17%	1 Aug →
inferno	13–3	0.03	18%	1 Aug →
dust2	8–13	0.07	21%	1 Aug →
inferno	12–16	-0.04	16%	30 Jul →
cache	9–13	0.03	17%	30 Jul →
dust2	13–6	0.01	10%	29 Jul →
mirage	13–11	-0.07	16%	29 Jul →
mirage	3–13	-0.03	28%	27 Jul →
dust2	11–13	-0.02	13%	26 Jul →
train	11–13	0.04	12%	26 Jul →
cache	13–8	-0.07	5%	26 Jul →
train	12–12	-0.00	21%	26 Jul →
inferno	13–8	0.01	17%	26 Jul →
mirage	13–6	0.07	20%	26 Jul →
vertigo	13–8	0.01	24%	26 Jul →
nuke	13–11	-0.03	12%	25 Jul →
dust2	13–7	0.00	9%	25 Jul →
mirage	13–5	0.02	15%	25 Jul →
inferno	7–13	-0.05	23%	22 Jul →
train	12–12	-0.01	17%	22 Jul →
inferno	8–13	0.02	20%	21 Jul →
dust2	13–6	0.04	14%	20 Jul →
ancient	5–13	-0.03	7%	20 Jul →
mirage	13–10	-0.02	12%	19 Jul →
anubis	0–5	-0.04	10%	19 Jul →
inferno	13–9	-0.01	13%	19 Jul →
cache	11–13	0.04	13%	19 Jul →
ancient	13–11	0.04	23%	19 Jul →
nuke	13–11	0.01	13%	19 Jul →
dust2	4–13	-0.11	9%	19 Jul →
vertigo	13–9	-0.00	21%	18 Jul →
vertigo	13–6	0.04	13%	15 Jul →
cache	13–6	0.02	21%	15 Jul →
train	13–10	0.08	11%	15 Jul →
inferno	5–13	0.04	19%	14 Jul →
inferno	7–13	-0.05	20%	12 Jul →
ancient	13–6	0.04	24%	12 Jul →
dust2	12–12	0.07	17%	12 Jul →
train	13–7	-0.02	10%	12 Jul →
mirage	13–11	0.05	12%	12 Jul →
cache	13–9	0.13	19%	12 Jul →
mirage	13–0	-0.02	21%	11 Jul →
train	11–13	0.05	21%	11 Jul →
inferno	8–13	0.02	31%	11 Jul →
cache	13–9	-0.05	18%	11 Jul →
nuke	5–13	-0.04	26%	11 Jul →
dust2	9–13	0.01	17%	8 Jul →
mirage	5–13	0.05	28%	8 Jul →
ancient	13–4	0.05	24%	6 Jul →
vertigo	5–11	0.05	13%	6 Jul →
mirage	13–6	-0.00	14%	5 Jul →
dust2	12–12	0.07	18%	5 Jul →
dust2	7–13	-0.00	20%	5 Jul →
inferno	13–7	0.01	10%	5 Jul →
nuke	13–10	0.05	14%	5 Jul →
cache	13–9	0.03	6%	5 Jul →
vertigo	4–13	-0.07	12%	4 Jul →
dust2	13–6	-0.00	19%	4 Jul →
mirage	13–10	0.06	16%	4 Jul →
cache	12–12	0.01	20%	4 Jul →
inferno	12–12	0.02	12%	4 Jul →
ancient	13–6	0.03	25%	3 Jul →
ancient	7–13	-0.07	13%	2 Jul →
dust2	13–8	0.01	20%	2 Jul →
inferno	10–13	-0.03	14%	2 Jul →
mirage	13–9	-0.01	13%	2 Jul →
inferno	12–16	0.03	12%	2 Jul →
vertigo	13–9	-0.05	14%	2 Jul →
cache	13–10	0.04	13%	2 Jul →
nuke	8–13	0.05	21%	2 Jul →
dust2	13–3	0.04	21%	2 Jul →
inferno	13–5	-0.02	22%	2 Jul →
dust2	11–13	-0.03	20%	1 Jul →