Macavelli — CS2 Stats

76561198000638481[U:1:40372753]Steam profile ↗✓ No bans

2,054Tracked matches46%Win rate2020Tracked since

CSDB Rating3.9 LearningSupport

Ladder ranks via Leetify

Performance scores

Aim48

Positioning38

Utility70

0–100 skill scores via Leetify.

Recent form

COLD48–50–2Last 10048%Win rateLWLLLWLWLL

Last 10 vs previous 10: -10pp win rate · -0.01 avg rating

Player DNA

Primary style: Support — Utility contribution leads the profile while opening activity stays low.

Aim4.8

Aggression3.5

Utility7.0

Positioning3.8

Opening Duels0.4

Clutch3.4

Strong 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 77% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-fight frequency; 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 39% on CT to 24% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 601ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 66% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim4.8

Positioning3.8

Utility7.0

Mechanics3.6

Opening Duels1.1

Win Impact3.8

Composite 3.9/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.00

first ⅓ avg -0.01 → last ⅓ avg -0.01

Reaction time594ms+30ms

first ⅓ avg 563ms → last ⅓ avg 594ms

Headshot accuracy12.7%+1.3%

first ⅓ avg 11.4% → last ⅓ avg 12.7%

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

0.12Best rating — mirage 13–2

13–1Biggest win — mirage

6Longest win streak

5–7In matches decided by ≤2 rounds

8Overtime games

Map breakdown

infernoBest map · 52% over 23ancientWeakest map · 36% over 11

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	33	14–19	42%	-0.02
nuke	B	23	11–12	48%	-0.03
inferno	B	23	12–11	52%	-0.01
ancient	C	11	4–7	36%	-0.02
anubis	—	4	4–0	100%	-0.01
cache	—	3	2–1	67%	-0.02
dust2	—	2	0–2	0%	-0.01
vertigo	—	1	1–0	100%	-0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (36% over 11). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

483Matches

51%Win rate

0.88Avg K/D

69.8ADR

34%Headshot %

Clutches & streaks

37%1v1 clutch win

17%1v2 clutch win

9Longest win streak

Recent Faceit resultsLLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	120	43%	0.80	12.2
Nuke	101	62%	0.88	13.9
Inferno	96	54%	0.88	13.9
Ancient	55	56%	0.88	13.8
Anubis	39	49%	0.81	13.0
Cache	8	62%	0.73	11.5
Dust2	7	0%	0.50	7.9
Overpass	6	17%	1.08	16.2

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.

12.6%Headshot accuracy

36.3%Accuracy (enemy spotted)

39.4%Spray accuracy

66.4%Counter-strafing

12.1°Preaim

601msReaction time

23.8%T opening success

39.2%CT opening success

0.67Enemies flashed / flash

6.8%Flash assists

7.87HE damage / grenade

11.47Flashes / 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
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 12.1282° — above the 12° mark we flag
Aim Training →
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 12.5531% — below the 15% mark we flag
Aim Training →

Spend your practice time on Ancient

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

36% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
nuke	7–13	-0.04	18%	14 Aug →
vertigo	13–11	-0.02	13%	7 Aug →
mirage	9–13	-0.06	14%	7 Aug →
nuke	10–13	-0.00	8%	7 Aug →
mirage	8–13	-0.01	11%	7 Aug →
ancient	13–9	-0.00	9%	7 Aug →
inferno	7–13	-0.11	6%	7 Aug →
inferno	11–1	0.06	18%	7 Aug →
mirage	8–13	-0.03	16%	1 Aug →
nuke	11–13	-0.02	11%	1 Aug →
nuke	13–8	0.05	10%	27 Jul →
mirage	3–13	-0.03	23%	27 Jul →
nuke	15–15	-0.01	17%	24 Jul →
ancient	13–9	-0.01	18%	24 Jul →
nuke	13–2	-0.05	12%	18 Jul →
nuke	9–13	-0.03	12%	18 Jul →
nuke	15–15	-0.00	11%	18 Jul →
inferno	9–13	-0.04	6%	4 Jul →
inferno	13–9	-0.04	2%	4 Jul →
mirage	6–13	-0.01	19%	4 Jul →
anubis	13–9	-0.05	9%	3 Jul →
inferno	6–13	-0.04	14%	3 Jul →
mirage	13–2	0.12	19%	3 Jul →
inferno	13–7	0.02	10%	3 Jul →
mirage	13–8	-0.06	16%	3 Jul →
mirage	13–5	-0.04	17%	3 Jul →
inferno	9–13	0.03	14%	3 Jul →
nuke	4–13	-0.07	9%	3 Jul →
mirage	3–13	-0.02	8%	26 Jun →
mirage	13–4	0.02	11%	26 Jun →
inferno	13–8	0.03	10%	26 Jun →
nuke	13–8	-0.03	9%	26 Jun →
nuke	8–13	-0.00	18%	26 Jun →
anubis	13–11	0.02	15%	13 Jun →
mirage	8–13	-0.08	13%	12 Jun →
nuke	14–16	-0.04	7%	12 Jun →
inferno	10–13	-0.05	10%	12 Jun →
nuke	13–3	-0.01	13%	12 Jun →
nuke	7–13	-0.05	11%	12 Jun →
mirage	5–13	-0.07	12%	12 Jun →
mirage	0–13	-0.07	20%	5 Jun →
nuke	13–7	-0.05	12%	29 May →
mirage	13–7	0.03	16%	29 May →
dust2	4–13	-0.01	15%	15 May →
mirage	11–13	-0.01	24%	13 May →
inferno	13–6	0.04	13%	13 May →
dust2	14–16	-0.01	15%	13 May →
inferno	8–13	-0.05	6%	9 May →
mirage	5–13	-0.07	29%	9 May →
cache	13–6	0.01	13%	8 May →
cache	13–6	-0.04	15%	8 May →
nuke	13–9	-0.05	17%	8 May →
mirage	13–6	-0.07	8%	30 Apr →
ancient	13–7	-0.04	13%	30 Apr →
cache	10–13	-0.02	6%	30 Apr →
inferno	16–19	-0.07	11%	24 Apr →
mirage	13–4	0.02	22%	24 Apr →
ancient	3–13	-0.02	20%	24 Apr →
inferno	13–3	0.01	13%	24 Apr →
inferno	13–5	-0.02	9%	17 Apr →
mirage	8–13	-0.04	8%	17 Apr →
ancient	14–16	-0.02	11%	17 Apr →
mirage	6–13	-0.06	8%	10 Apr →
mirage	13–1	0.04	19%	5 Apr →
mirage	11–13	-0.01	8%	4 Apr →
nuke	13–7	-0.05	18%	2 Apr →
inferno	11–13	-0.02	9%	2 Apr →
mirage	8–13	0.03	8%	2 Apr →
inferno	13–6	0.08	21%	2 Apr →
anubis	13–6	0.06	11%	28 Mar →
mirage	13–5	0.11	13%	28 Mar →
mirage	9–13	0.00	15%	28 Mar →
inferno	10–13	-0.09	3%	28 Mar →
inferno	13–6	-0.04	6%	27 Mar →
mirage	13–10	0.04	11%	27 Mar →
nuke	13–5	-0.07	0%	27 Mar →
mirage	13–8	0.00	16%	27 Mar →
mirage	5–13	-0.04	11%	27 Mar →
nuke	13–6	0.05	13%	27 Mar →
ancient	10–13	-0.03	16%	20 Mar →
ancient	6–13	-0.01	12%	20 Mar →
mirage	13–1	-0.01	9%	14 Mar →
inferno	6–13	0.03	11%	14 Mar →
nuke	10–13	-0.05	10%	13 Mar →
mirage	8–13	-0.02	10%	13 Mar →
inferno	13–10	0.01	16%	7 Mar →
ancient	7–13	0.02	17%	7 Mar →
ancient	8–13	0.02	8%	6 Mar →
inferno	8–13	-0.01	14%	6 Mar →
ancient	5–13	-0.09	9%	28 Feb →
mirage	5–13	-0.08	8%	28 Feb →
ancient	13–8	-0.03	14%	28 Feb →
anubis	16–14	-0.08	16%	28 Feb →
nuke	9–13	-0.02	7%	27 Feb →
inferno	13–8	-0.07	17%	27 Feb →
nuke	13–2	-0.02	9%	27 Feb →
mirage	13–6	-0.01	8%	27 Feb →
inferno	13–11	-0.01	17%	21 Feb →
mirage	13–9	-0.03	11%	21 Feb →
nuke	16–14	-0.03	11%	21 Feb →