Mada — CS2 Stats

DK76561197998357743[U:1:38092015]Steam profile ↗✓ No bans

2,592Tracked matches55%Win rate2020Tracked since

7,553Hours in CS

CSDB Rating6.1 SolidAggressive Rifler

FaceitLevel 10 · 2,559 ELOTop 12.4% of ranked FACEIT players

WingmanLegendary Eagle

Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 10 among CSDB-tracked players (n=4,917), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

Metric	This player	Level 10 median
Headshot rate	56.4%	51.9%
Shot accuracy	16.0%	13.7%
Kill/death ratio	1.03	1.08
Match win rate	47.7%	48.7%

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Performance scores

Aim71

Positioning53

Utility66

0–100 skill scores via Leetify.

Recent form

STEADY50–48–2Last 10050%Win rateWLLLWLWLWW

Last 10 vs previous 10: +0pp win rate · -0.02 avg rating

Player DNA

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

Aim7.1

Aggression6.8

Utility6.6

Positioning5.3

Opening Duels2.4

Clutch3.8

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 92% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: 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. 567ms 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

Aim7.1

Positioning5.3

Utility6.6

Mechanics5.7

Opening Duels2.4

Win Impact6.7

Composite 6.1/10 (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 rating0.00−0.04

first ⅓ avg 0.05 → last ⅓ avg 0.00

Reaction time572ms+19ms

first ⅓ avg 553ms → last ⅓ avg 572ms

Headshot accuracy29.7%+6.2%

first ⅓ avg 23.5% → last ⅓ avg 29.7%

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

0.27Best rating — ancient 4–1

13–0Biggest win — mirage

7Longest win streak

2–9In matches decided by ≤2 rounds

11Overtime games

Map breakdown

dust2Best map · 60% over 15infernoWeakest map · 40% over 10

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	20	10–10	50%	0.02
mirage	A	18	10–8	56%	0.03
dust2	A	15	9–6	60%	0.02
nuke	B	13	6–7	46%	0.01
anubis	B	12	6–6	50%	0.02
overpass	B	10	5–5	50%	0.07
inferno	C	10	4–6	40%	0.03
cache	—	2	0–2	0%	0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (40% over 10). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

396,458Lifetime kills

1.03K/D

13,718Matches

47.7%Match win rate

56.4%Headshot % · Top 50% of Level 10 players

16.0%Shot accuracy · Top 50% of Level 10 players

34,752MVPs

7,553Hours (in match)

17,480Bombs planted

3,433Bombs defused

Most-used weapons

AK-47152,690

M4A4 / M4A1-S57,109

AWP37,110

P2000 / USP-S30,186

Desert Eagle25,628

P25015,327

Glock-1810,921

SSG 086,180

Tec-96,087

Knife6,001

Lifetime map wins

15,449dust2

14,976nuke

14,851inferno

12,820train

9,603cbble

6,086vertigo

592office

336lake

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

Faceit stats

Combat

4,261Matches

52%Win rate

1.02Avg K/D

78.9ADR

51%Headshot %

Clutches & streaks

39%1v1 clutch win

22%1v2 clutch win

14Longest win streak

Recent Faceit resultsWLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	239	62%	1.23	17.4
Mirage	178	40%	1.04	15.3
Nuke	165	54%	1.14	15.5
Anubis	143	57%	1.18	16.4
Dust2	65	43%	0.95	14.6
Overpass	60	45%	1.16	16.2
Train	42	57%	1.14	17.9
Vertigo	38	45%	1.07	17.1

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.

29.8%Headshot accuracy

29.8%Accuracy (enemy spotted)

33.4%Spray accuracy

75.8%Counter-strafing

10.8°Preaim

567msReaction time

34.8%T opening success

44.3%CT opening success

0.59Enemies flashed / flash

14.5%Flash assists

9.45HE damage / grenade

10.08Flashes / 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 34.8121% — 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.

40% win rate across 10 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
ancient	13–7	-0.03	26%	28 Aug →
dust2	11–13	-0.04	30%	22 Aug →
nuke	8–13	-0.09	16%	20 Aug →
cache	18–22	0.01	41%	13 Aug →
nuke	13–9	-0.01	26%	9 Aug →
nuke	11–13	0.01	22%	9 Aug →
ancient	13–4	0.06	36%	7 Aug →
cache	7–13	0.01	29%	7 Aug →
ancient	13–8	0.04	31%	7 Aug →
ancient	16–14	0.02	37%	13 Jul →
nuke	13–9	0.01	26%	13 Jul →
dust2	13–16	-0.04	27%	26 May →
anubis	9–13	-0.06	28%	24 May →
dust2	15–15	-0.05	31%	22 May →
ancient	13–7	0.03	15%	22 May →
anubis	13–6	0.06	38%	22 May →
ancient	2–13	-0.05	31%	18 May →
overpass	13–1	0.11	40%	15 May →
nuke	8–13	0.06	30%	3 May →
mirage	13–4	0.09	21%	3 May →
dust2	13–7	-0.01	41%	3 May →
mirage	13–8	0.01	31%	28 Apr →
overpass	13–6	-0.04	32%	28 Apr →
anubis	13–7	0.05	28%	25 Apr →
ancient	1–13	-0.07	40%	25 Apr →
anubis	5–13	-0.04	30%	25 Apr →
nuke	13–10	0.04	32%	25 Apr →
mirage	9–13	-0.01	21%	23 Apr →
ancient	2–13	-0.06	21%	23 Apr →
mirage	13–6	0.10	32%	21 Apr →
dust2	13–9	0.02	22%	20 Apr →
anubis	9–13	-0.04	37%	20 Apr →
overpass	8–13	0.03	33%	11 Apr →
mirage	6–13	-0.00	34%	11 Apr →
dust2	8–13	0.03	29%	11 Apr →
mirage	8–13	0.01	29%	11 Apr →
overpass	8–13	0.03	31%	11 Apr →
ancient	3–13	-0.05	24%	11 Apr →
inferno	9–13	0.01	23%	11 Apr →
dust2	16–13	0.00	26%	9 Apr →
mirage	13–0	0.14	23%	9 Apr →
inferno	10–13	-0.02	26%	8 Apr →
ancient	6–13	-0.09	24%	7 Apr →
dust2	13–4	-0.04	16%	6 Apr →
inferno	13–0	0.19	42%	3 Apr →
anubis	13–8	0.03	30%	3 Apr →
nuke	13–2	0.06	38%	3 Apr →
ancient	13–9	0.07	25%	3 Apr →
anubis	13–3	0.09	31%	3 Apr →
nuke	13–7	0.04	31%	3 Apr →
nuke	9–13	-0.00	31%	2 Apr →
inferno	16–13	0.05	32%	2 Apr →
mirage	5–13	-0.02	26%	2 Apr →
ancient	4–1	0.27	31%	2 Apr →
dust2	13–5	0.05	39%	1 Apr →
dust2	13–6	-0.03	41%	1 Apr →
nuke	8–13	0.04	29%	29 Mar →
ancient	13–10	-0.02	21%	20 Mar →
overpass	13–16	0.12	29%	19 Mar →
inferno	8–13	0.05	29%	19 Mar →
dust2	4–13	-0.03	26%	19 Mar →
inferno	13–10	0.08	31%	19 Mar →
mirage	10–13	-0.08	50%	13 Mar →
overpass	13–7	0.06	25%	12 Mar →
anubis	13–11	0.07	22%	6 Mar →
mirage	13–6	0.00	20%	6 Mar →
ancient	10–13	-0.00	26%	6 Mar →
nuke	13–7	0.02	33%	6 Mar →
mirage	13–10	0.01	14%	6 Mar →
nuke	12–12	-0.02	25%	6 Mar →
ancient	11–13	0.06	37%	5 Mar →
mirage	13–6	0.04	24%	2 Mar →
inferno	13–6	0.02	24%	2 Mar →
anubis	11–13	0.02	19%	2 Mar →
overpass	13–10	0.11	27%	1 Mar →
inferno	7–13	-0.00	13%	1 Mar →
mirage	13–9	0.12	27%	1 Mar →
ancient	14–16	0.10	29%	28 Feb →
overpass	13–6	0.17	21%	28 Feb →
anubis	11–13	0.01	14%	27 Feb →
mirage	5–13	0.07	22%	27 Feb →
ancient	14–16	0.02	23%	27 Feb →
mirage	13–5	0.04	30%	26 Feb →
dust2	13–1	0.12	37%	14 Feb →
ancient	11–13	0.08	21%	12 Feb →
dust2	13–6	0.23	24%	12 Feb →
anubis	13–5	0.06	16%	12 Feb →
mirage	10–13	0.07	15%	12 Feb →
inferno	5–13	-0.04	30%	11 Feb →
overpass	7–13	0.07	19%	11 Feb →
mirage	13–7	0.04	18%	11 Feb →
inferno	10–13	-0.00	35%	10 Feb →
dust2	13–1	0.15	14%	10 Feb →
dust2	13–16	-0.00	25%	9 Feb →
mirage	11–13	-0.02	22%	8 Feb →
anubis	5–13	-0.04	24%	8 Feb →
ancient	13–9	-0.03	18%	3 Feb →
nuke	16–19	0.02	24%	31 Jan →
overpass	10–13	0.01	16%	31 Jan →
ancient	13–9	0.04	38%	24 Jan →