Makzwell — CS2 Stats

US76561198107371885[U:1:147106157]Steam profile ↗✓ No bans

1,985Tracked matches33%Win rate2020Tracked since

CSDB Rating6.2 SolidAggressive Rifler

Ladder ranks via Leetify

Performance scores

Aim85

Positioning56

Utility59

0–100 skill scores via Leetify.

Recent form

COLD31–63–6Last 10031%Win rateLLWWLWLLLL

Last 10 vs previous 10: -10pp win rate · -0.03 avg rating

Player DNA

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

Aim8.5

Aggression6.6

Utility5.9

Positioning5.6

Opening Duels3.6

Clutch2.6

Sharp aimerExcellent counter-strafingStrong CT-side openerEffective flashes

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 iM 94% playstyle similarity

Most alike: aim profile, 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

Areas to improve

T-side openings. Opening success drops from 58% on CT to 31% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 680ms 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

Aim8.5

Positioning5.6

Utility5.9

Mechanics8.7

Opening Duels3.6

Win Impact0.0

Composite 6.2/10 (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 rating0.01+0.01

first ⅓ avg 0.00 → last ⅓ avg 0.01

Reaction time704ms−14ms

first ⅓ avg 718ms → last ⅓ avg 704ms

Headshot accuracy34.7%−1.9%

first ⅓ avg 36.5% → last ⅓ avg 34.7%

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

0.17Best rating — inferno 13–8

13–2Biggest win — dust2

5Longest win streak

L2Current streak

9–4In matches decided by ≤2 rounds

8Overtime games

Map breakdown

infernoBest map · 57% over 7cacheWeakest map · 0% over 5

Map	Grade	Played	Record	Win rate	Avg rating
dust2	D	21	6–15	29%	-0.01
nuke	D	16	5–11	31%	-0.02
mirage	A	16	9–7	56%	0.02
ancient	D	14	1–13	7%	0.00
anubis	B	8	4–4	50%	0.02
overpass	D	8	2–6	25%	-0.01
inferno	A	7	4–3	57%	0.01
cache	D	5	0–5	0%	-0.04
train	—	2	0–2	0%	-0.02
vertigo	—	1	0–1	0%	0.01
shelter	—	1	0–1	0%	-0.10
office	—	1	0–1	0%	-0.02

Across the last 100 tracked matches.

Faceit stats

Combat

1,545Matches

55%Win rate

1.23Avg K/D

65.8ADR

48%Headshot %

Clutches & streaks

33%1v1 clutch win

16%1v2 clutch win

9Longest win streak

Recent Faceit resultsWLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	33	36%	0.70	11.4
Dust2	31	42%	0.88	14.0
Mirage	29	41%	0.76	13.5
Anubis	23	43%	0.79	11.7
Inferno	14	57%	0.76	11.4
Nuke	13	46%	0.85	11.2
Overpass	11	9%	0.75	12.2
Vertigo	8	25%	1.01	13.8

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.

32.6%Headshot accuracy

37.7%Accuracy (enemy spotted)

31.6%Spray accuracy

89.3%Counter-strafing

9.5°Preaim

680msReaction time

30.6%T opening success

58.1%CT opening success

0.74Enemies flashed / flash

8.9%Flash assists

7.92HE damage / grenade

11.76Flashes / 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 30.5805% — below the 40% mark we flag

Spend your practice time on Cache

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

0% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
ancient	11–13	0.03	31%	26 Aug →
ancient	9–13	-0.01	33%	26 Aug →
anubis	16–14	0.04	33%	26 Aug →
nuke	13–10	0.05	24%	19 Aug →
ancient	6–13	0.01	14%	15 Aug →
mirage	13–8	0.12	45%	15 Aug →
ancient	13–16	0.02	28%	15 Aug →
cache	12–16	-0.02	26%	10 Aug →
mirage	4–13	-0.01	36%	10 Aug →
train	9–13	0.01	38%	10 Aug →
vertigo	12–12	0.01	29%	10 Aug →
anubis	13–11	0.07	52%	9 Aug →
mirage	13–5	0.05	35%	9 Aug →
cache	4–13	0.04	33%	7 Aug →
mirage	16–12	0.09	27%	4 Aug →
nuke	13–11	0.13	11%	4 Aug →
mirage	8–13	0.08	36%	27 Jul →
dust2	5–13	-0.03	30%	27 Jul →
nuke	10–13	0.01	46%	25 Jul →
ancient	8–13	0.05	28%	18 Jul →
nuke	4–13	-0.08	50%	18 Jul →
nuke	12–12	-0.05	40%	15 Jul →
shelter	5–13	-0.10	32%	9 Jul →
nuke	4–13	-0.02	32%	9 Jul →
dust2	3–13	0.01	33%	9 Jul →
dust2	9–13	-0.07	23%	9 Jul →
nuke	13–9	0.01	33%	9 Jul →
cache	10–13	-0.08	25%	8 Jul →
dust2	16–12	0.04	39%	26 Jun →
dust2	12–12	0.00	39%	8 Jun →
cache	6–13	-0.06	63%	3 Jun →
dust2	8–13	0.02	33%	3 Jun →
cache	9–13	-0.09	67%	28 May →
office	5–13	-0.02	33%	28 May →
nuke	3–13	-0.07	57%	24 May →
nuke	4–3	-0.05	0%	18 May →
dust2	13–11	-0.03	43%	18 May →
mirage	13–5	-0.04	38%	14 May →
dust2	8–13	-0.03	50%	14 May →
overpass	10–13	-0.05	19%	12 May →
mirage	13–7	0.01	50%	9 May →
nuke	5–13	-0.02	50%	9 May →
dust2	6–13	-0.07	19%	7 May →
dust2	2–13	-0.07	27%	5 May →
overpass	8–13	-0.02	35%	5 May →
anubis	7–13	-0.00	47%	30 Apr →
nuke	8–13	-0.01	38%	28 Apr →
inferno	5–13	-0.03	38%	28 Apr →
anubis	13–5	-0.01	25%	28 Apr →
anubis	12–12	0.00	20%	26 Apr →
nuke	2–13	-0.08	30%	26 Apr →
nuke	4–13	-0.09	33%	24 Apr →
dust2	4–13	-0.03	30%	23 Apr →
inferno	13–10	0.01	21%	21 Apr →
mirage	8–1	0.04	57%	21 Apr →
overpass	10–13	-0.01	25%	21 Apr →
ancient	9–13	-0.04	37%	20 Apr →
dust2	11–13	0.07	30%	17 Apr →
overpass	5–13	-0.00	23%	17 Apr →
train	3–13	-0.05	47%	15 Apr →
mirage	4–13	-0.03	48%	15 Apr →
anubis	13–8	0.03	39%	15 Apr →
ancient	11–13	-0.03	28%	15 Apr →
ancient	7–13	-0.04	19%	14 Apr →
anubis	15–15	0.06	27%	14 Apr →
dust2	13–10	-0.02	17%	14 Apr →
overpass	13–5	0.03	13%	13 Apr →
dust2	13–7	-0.04	27%	13 Apr →
ancient	13–8	0.01	54%	10 Apr →
overpass	16–14	-0.05	19%	10 Apr →
dust2	4–13	-0.04	33%	10 Apr →
overpass	8–13	-0.04	47%	9 Apr →
ancient	11–13	0.12	27%	7 Apr →
dust2	8–13	-0.03	31%	7 Apr →
mirage	6–13	0.02	32%	7 Apr →
ancient	6–13	-0.03	24%	6 Apr →
mirage	13–8	0.06	26%	4 Apr →
ancient	8–13	-0.03	27%	4 Apr →
nuke	3–13	-0.05	83%	3 Apr →
dust2	13–8	0.01	30%	2 Apr →
dust2	13–2	0.07	31%	2 Apr →
inferno	4–2	0.00	40%	2 Apr →
mirage	13–11	-0.04	24%	2 Apr →
mirage	5–13	-0.03	35%	1 Apr →
inferno	13–8	0.17	33%	1 Apr →
inferno	13–11	0.02	40%	28 Mar →
dust2	5–13	-0.02	29%	28 Mar →
inferno	2–13	-0.07	75%	25 Mar →
anubis	4–13	0.02	50%	25 Mar →
nuke	13–16	0.01	38%	25 Mar →
nuke	13–10	-0.04	42%	25 Mar →
ancient	6–13	-0.02	24%	23 Mar →
inferno	6–13	-0.02	16%	17 Mar →
mirage	13–6	0.00	29%	13 Mar →
mirage	1–13	-0.03	38%	13 Mar →
overpass	9–13	0.03	23%	13 Mar →
mirage	12–12	0.09	36%	13 Mar →
dust2	8–13	-0.02	54%	13 Mar →
dust2	3–13	0.02	50%	12 Mar →
ancient	7–13	0.02	38%	12 Mar →