Macroman — CS2 Stats

76561198282217228[U:1:321951500]✓ No bans

790Tracked matches43%Win rate2023Tracked since

465Hours in CS

CSDB Rating3.8 Learning

WingmanGold Nova III

Ladder ranks via Leetify

Performance scores

Aim39

Positioning41

Utility53

0–100 skill scores via Leetify.

Recent form

STEADY46–54Last 10046%Win rateLWWLLWLLWL

Last 10 vs previous 10: +0pp win rate · -0.00 avg rating

Player DNA

Aim3.9

Aggression4.2

Utility5.3

Positioning4.1

Opening Duels0.0

Clutch6.2

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 NiKo 78% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: lower positioning profile; 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

Reaction time. 639ms 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

Aim3.9

Positioning4.1

Utility5.3

Mechanics4.7

Opening Duels0.3

Win Impact2.8

Composite 3.8/10 (Learning), 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 rating-0.03−0.01

first ⅓ avg -0.02 → last ⅓ avg -0.03

Reaction time627ms+22ms

first ⅓ avg 606ms → last ⅓ avg 627ms

Headshot accuracy14.4%−4.4%

first ⅓ avg 18.8% → last ⅓ avg 14.4%

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

0.11Best rating — mirage 13–0

13–0Biggest win — ancient

5Longest win streak

9–5In matches decided by ≤2 rounds

7Overtime games

Map breakdown

dust2Best map · 57% over 28anubisWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	31	15–16	48%	-0.03
dust2	A	28	16–12	57%	-0.02
ancient	B	11	5–6	45%	-0.03
inferno	B	10	5–5	50%	-0.00
nuke	C	8	3–5	38%	-0.03
anubis	D	6	1–5	17%	-0.04
overpass	—	4	1–3	25%	-0.01
cache	—	1	0–1	0%	-0.07
office	—	1	0–1	0%	0.04

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

17,087Lifetime kills

0.84K/D

1,210Matches

45.0%Match win rate

46.1%Headshot % · Top 50% of tracked players

4.5%Shot accuracy

2,303MVPs

465Hours (in match)

1,218Bombs planted

297Bombs defused

Most-used weapons

AK-475,387

M4A4 / M4A1-S3,477

AWP2,586

P2000 / USP-S1,140

Glock-18774

Desert Eagle697

MAC-10389

MP9313

Galil AR300

FAMAS231

Lifetime map wins

1,470dust2

1,254inferno

1,055nuke

613vertigo

209train

50office

50cbble

22italy

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

Faceit stats

Combat

107Matches

51%Win rate

0.92Avg K/D

71.6ADR

48%Headshot %

Clutches & streaks

51%1v1 clutch win

16%1v2 clutch win

5Longest win streak

Recent Faceit resultsLWLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	34	56%	0.87	12.4
Dust2	21	52%	1.08	14.8
Ancient	13	69%	0.92	15.8
Anubis	8	38%	0.68	11.5
Vertigo	8	50%	0.94	11.9
Nuke	6	33%	0.87	16.2
Inferno	5	40%	1.13	15.2
Overpass	3	67%	0.69	12.0

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.

14.8%Headshot accuracy

28.2%Accuracy (enemy spotted)

28.9%Spray accuracy

71.1%Counter-strafing

9.4°Preaim

639msReaction time

32.3%T opening success

28.0%CT opening success

0.60Enemies flashed / flash

7.5%Flash assists

9.08HE damage / grenade

6.36Flashes / 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 14.7974% — below the 15% mark we flag
Aim Training →
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 32.2936% — 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.

17% 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
nuke	10–13	-0.05	13%	31 Jul →
ancient	13–5	-0.00	21%	22 Jun →
mirage	13–6	-0.06	15%	22 Jun →
mirage	5–13	-0.07	12%	22 Jun →
inferno	10–13	-0.07	4%	14 Jun →
anubis	13–4	-0.01	16%	11 Jun →
mirage	3–13	-0.04	22%	11 Jun →
anubis	12–16	-0.03	9%	11 Jun →
dust2	13–11	-0.03	21%	11 Jun →
dust2	9–13	-0.01	15%	9 Jun →
cache	11–13	-0.07	24%	8 Jun →
mirage	13–3	-0.04	8%	8 Jun →
ancient	7–13	-0.06	19%	8 Jun →
ancient	13–6	-0.05	6%	8 Jun →
dust2	13–9	0.02	27%	8 Jun →
nuke	9–13	-0.07	16%	7 Jun →
mirage	7–13	-0.03	12%	7 Jun →
dust2	13–8	0.03	16%	5 Jun →
dust2	6–13	-0.06	11%	5 Jun →
mirage	6–13	-0.01	11%	5 Jun →
mirage	13–7	0.06	19%	4 Jun →
ancient	10–13	-0.02	12%	4 Jun →
mirage	13–9	-0.05	18%	4 Jun →
mirage	0–13	-0.03	0%	4 Jun →
inferno	13–7	0.02	17%	3 Jun →
mirage	13–11	0.00	13%	3 Jun →
mirage	9–13	-0.08	21%	28 May →
mirage	2–13	0.01	22%	28 May →
office	9–13	0.04	13%	20 May →
dust2	13–2	0.01	6%	29 Mar →
overpass	10–13	-0.07	14%	24 Mar →
dust2	5–13	-0.08	12%	24 Mar →
nuke	6–13	-0.07	11%	24 Mar →
inferno	13–16	0.01	10%	24 Mar →
dust2	2–13	-0.09	24%	24 Mar →
dust2	6–13	-0.05	23%	21 Mar →
nuke	6–13	0.01	24%	21 Mar →
ancient	16–13	-0.04	17%	19 Mar →
dust2	13–10	0.03	15%	19 Mar →
mirage	4–13	-0.04	20%	18 Mar →
nuke	9–13	-0.06	10%	18 Mar →
dust2	13–3	0.08	17%	18 Mar →
inferno	5–13	-0.02	7%	18 Mar →
dust2	13–11	0.04	19%	17 Mar →
dust2	13–8	0.09	11%	17 Mar →
mirage	13–4	-0.03	34%	17 Mar →
mirage	13–5	0.02	33%	17 Mar →
ancient	16–19	-0.05	11%	16 Mar →
dust2	14–16	-0.01	12%	16 Mar →
dust2	13–10	-0.02	13%	16 Mar →
dust2	11–13	-0.08	21%	10 Mar →
nuke	13–8	-0.01	25%	10 Mar →
dust2	5–13	-0.07	29%	10 Mar →
mirage	6–13	-0.06	9%	5 Mar →
ancient	13–0	-0.03	6%	5 Mar →
mirage	6–13	-0.06	19%	5 Mar →
dust2	13–3	0.00	16%	5 Mar →
anubis	8–13	-0.02	21%	5 Mar →
mirage	8–13	0.02	25%	4 Mar →
inferno	13–8	-0.00	26%	4 Mar →
nuke	13–9	-0.03	14%	3 Mar →
mirage	8–13	-0.08	8%	3 Mar →
dust2	8–13	-0.09	13%	3 Mar →
dust2	13–9	-0.03	22%	2 Mar →
mirage	13–11	-0.05	16%	2 Mar →
ancient	11–13	0.02	19%	2 Mar →
mirage	5–13	-0.08	21%	2 Mar →
dust2	13–11	-0.03	16%	24 Feb →
inferno	13–10	-0.01	18%	24 Feb →
ancient	9–13	-0.10	19%	24 Feb →
mirage	5–13	-0.02	26%	23 Feb →
overpass	3–13	0.00	24%	23 Feb →
dust2	13–10	-0.03	31%	23 Feb →
nuke	13–4	0.07	19%	23 Feb →
dust2	13–7	0.05	16%	23 Feb →
mirage	13–5	-0.01	32%	23 Feb →
mirage	7–13	0.01	11%	23 Feb →
inferno	16–14	0.01	12%	22 Feb →
inferno	10–13	-0.03	19%	18 Feb →
anubis	4–13	-0.07	13%	17 Feb →
ancient	3–13	-0.06	8%	17 Feb →
mirage	11–13	-0.00	25%	16 Feb →
dust2	10–13	-0.02	13%	16 Feb →
ancient	13–11	0.01	16%	14 Feb →
mirage	13–11	-0.08	10%	14 Feb →
anubis	5–13	-0.04	32%	14 Feb →
dust2	13–7	-0.01	14%	14 Feb →
mirage	13–11	-0.05	21%	14 Feb →
inferno	9–13	-0.02	13%	14 Feb →
dust2	7–13	-0.06	11%	14 Feb →
dust2	6–13	-0.07	16%	14 Feb →
mirage	13–0	0.11	23%	14 Feb →
mirage	16–13	0.02	22%	13 Feb →
mirage	13–4	-0.04	15%	13 Feb →
inferno	13–8	0.06	20%	3 Feb →
overpass	13–10	0.04	26%	3 Feb →
anubis	8–13	-0.05	7%	2 Feb →
overpass	9–13	-0.02	21%	18 Jan →
mirage	13–10	-0.06	21%	16 Jan →
dust2	13–2	0.02	32%	16 Jan →