Domas — CS2 Stats

76561199207852601[U:1:1247586873]✓ No bans

4,949Tracked matches45%Win rate2021Tracked since

8,884Hours in CS5Hrs last 2 wks

CSDB Rating6.7 SolidAggressive Rifler

Premier CS Rating27,598Top 5% of 29,473 CSDB-tracked playersRed band · top ~1.8% of ranked players (population est.)

CSDB Leaderboard#1047 of 42406 tracked

FaceitLevel 10 · 3,357 ELOTop 12.4% of ranked FACEIT players

WingmanSupreme Master First Class

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	70.1%	51.9%
Shot accuracy	12.2%	13.7%
Kill/death ratio	0.96	1.08
Match win rate	52.8%	48.7%

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Performance scores

Aim88

Positioning48

Utility61

0–100 skill scores via Leetify.

Recent form

STEADY48–47–5Last 10048%Win rateWWWWLLWLLL

Last 10 vs previous 10: +10pp win rate · -0.06 avg rating

Player DNA

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

Aim8.8

Aggression7.6

Utility6.1

Positioning4.8

Opening Duels4.0

Clutch3.6

Sharp aimer

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 93% playstyle similarity

Most alike: opening-fight frequency, 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

Strengths

Aim. Aim score of 88 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 40 points — deaths here waste a strong aim profile.

Reaction time. 551ms 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

Aim8.8

Positioning4.8

Utility6.1

Mechanics7.5

Opening Duels4.0

Win Impact3.3

Composite 6.7/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01−0.04

first ⅓ avg 0.05 → last ⅓ avg 0.01

Reaction time574ms+25ms

first ⅓ avg 549ms → last ⅓ avg 574ms

Headshot accuracy28.1%−7.1%

first ⅓ avg 35.2% → last ⅓ avg 28.1%

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

0.47Best rating — dust2 1–1

13–1Biggest win — dust2

7Longest win streak

W4Current streak

6–4In matches decided by ≤2 rounds

7Overtime games

Map breakdown

mirageBest map · 67% over 12cacheWeakest map · 20% over 5

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	25	10–15	40%	0.03
ancient	B	19	10–9	53%	0.04
inferno	A	15	9–6	60%	0.03
mirage	S	12	8–4	67%	0.04
anubis	D	9	3–6	33%	0.03
nuke	D	6	2–4	33%	0.02
cache	D	5	1–4	20%	0.03
train	—	4	3–1	75%	0.10
vertigo	—	2	1–1	50%	0.03
fachwerk	—	1	1–0	100%	0.07
overpass	—	1	0–1	0%	0.05
poseidon	—	1	0–1	0%	0.06

Across the last 100 tracked matches.

Lifetime stats

202,238Lifetime kills

0.96K/D

6,052Matches

52.8%Match win rate · Top 25% of Level 10 players

70.1%Headshot % · Top 5% of Level 10 players

12.2%Shot accuracy

22,204MVPs

4,303Hours (in match)

5,796Bombs planted

1,587Bombs defused

Most-used weapons

AK-4782,770

M4A4 / M4A1-S35,025

P2000 / USP-S30,781

Desert Eagle12,757

Glock-186,988

Galil AR5,276

MP94,655

AWP4,324

FAMAS3,659

Knife3,642

Lifetime map wins

13,526inferno

7,014dust2

6,791vertigo

4,455nuke

815train

640cbble

425office

98lake

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

Faceit stats

Combat

3,246Matches

53%Win rate

1.11Avg K/D

81.4ADR

60%Headshot %

Clutches & streaks

38%1v1 clutch win

20%1v2 clutch win

12Longest win streak

Recent Faceit resultsWWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	531	51%	1.05	15.1
Ancient	528	54%	1.12	16.5
Dust2	216	56%	1.07	15.6
Inferno	185	51%	1.04	14.4
Vertigo	127	58%	1.10	15.5
Nuke	120	50%	1.06	15.8
Overpass	102	61%	1.21	16.5
Anubis	85	39%	0.96	14.3

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.

29.3%Headshot accuracy

36.0%Accuracy (enemy spotted)

37.2%Spray accuracy

83.9%Counter-strafing

9.5°Preaim

551msReaction time

45.2%T opening success

47.2%CT opening success

0.62Enemies flashed / flash

17.2%Flash assists

9.43HE damage / grenade

6.17Flashes / match

Recommended for you

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.

20% 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
anubis	13–11	0.00	28%	27 Aug →
ancient	13–8	0.08	42%	27 Aug →
dust2	13–11	-0.10	27%	22 Aug →
inferno	9–5	-0.20	0%	22 Aug →
mirage	3–13	-0.10	33%	22 Aug →
anubis	8–13	0.02	38%	22 Aug →
ancient	13–8	-0.01	22%	22 Aug →
vertigo	8–13	0.01	30%	20 Aug →
nuke	2–13	0.02	28%	13 Aug →
train	3–13	0.11	33%	13 Aug →
nuke	13–6	0.12	29%	13 Aug →
cache	9–13	0.05	37%	8 Aug →
ancient	10–13	-0.01	12%	8 Aug →
inferno	10–13	-0.05	42%	8 Aug →
dust2	13–4	-0.01	29%	7 Aug →
mirage	15–15	0.03	15%	7 Aug →
dust2	10–0	0.09	40%	7 Aug →
inferno	9–13	0.08	26%	6 Aug →
anubis	4–13	0.11	36%	6 Aug →
fachwerk	13–8	0.07	37%	6 Aug →
anubis	2–13	-0.08	29%	6 Aug →
mirage	7–1	0.02	29%	6 Aug →
mirage	13–2	0.16	33%	6 Aug →
mirage	13–6	0.15	29%	2 Aug →
nuke	0–13	-0.05	27%	2 Aug →
dust2	13–4	-0.06	25%	2 Aug →
dust2	0–2	-0.30	0%	2 Aug →
dust2	13–10	0.09	39%	2 Aug →
ancient	10–13	0.01	19%	2 Aug →
dust2	3–13	0.04	36%	2 Aug →
cache	9–13	0.00	22%	2 Aug →
dust2	11–13	0.13	33%	31 Jul →
inferno	8–13	-0.03	24%	31 Jul →
anubis	8–13	0.09	29%	31 Jul →
ancient	8–13	-0.01	26%	28 Jul →
nuke	1–7	-0.07	60%	27 Jul →
dust2	8–13	-0.03	38%	27 Jul →
dust2	2–13	-0.09	29%	27 Jul →
dust2	13–1	0.04	46%	27 Jul →
cache	3–13	0.04	32%	27 Jul →
dust2	13–8	0.09	33%	27 Jul →
inferno	13–6	0.03	45%	27 Jul →
ancient	15–15	0.08	24%	27 Jul →
inferno	0–13	-0.07	0%	27 Jul →
ancient	13–6	0.12	39%	27 Jul →
dust2	7–13	0.09	24%	26 Jul →
inferno	16–14	0.14	37%	26 Jul →
ancient	1–13	-0.01	15%	26 Jul →
dust2	8–13	-0.00	34%	26 Jul →
ancient	13–9	0.14	37%	26 Jul →
nuke	2–13	0.09	32%	26 Jul →
cache	16–13	0.06	25%	26 Jul →
ancient	10–13	0.07	36%	26 Jul →
mirage	13–5	0.04	25%	25 Jul →
ancient	13–5	0.08	27%	25 Jul →
dust2	9–13	0.04	48%	22 Jul →
cache	9–13	-0.02	23%	21 Jul →
dust2	6–13	0.02	35%	21 Jul →
mirage	13–2	0.00	33%	21 Jul →
mirage	13–9	0.12	38%	20 Jul →
mirage	13–3	0.00	43%	20 Jul →
dust2	13–3	0.14	46%	20 Jul →
inferno	13–8	0.11	29%	20 Jul →
inferno	13–8	0.17	41%	19 Jul →
ancient	13–10	0.06	26%	19 Jul →
dust2	5–13	-0.04	55%	14 Jul →
dust2	7–13	0.04	25%	9 Jul →
anubis	3–10	0.09	17%	9 Jul →
dust2	13–4	0.04	22%	9 Jul →
dust2	6–13	0.00	57%	9 Jul →
ancient	13–9	0.08	37%	9 Jul →
anubis	13–10	0.01	37%	4 Jul →
mirage	13–7	0.11	27%	2 Jul →
overpass	15–15	0.05	23%	2 Jul →
nuke	13–11	0.04	24%	1 Jul →
inferno	13–11	0.13	36%	1 Jul →
ancient	6–2	0.13	38%	1 Jul →
dust2	12–16	-0.06	38%	1 Jul →
inferno	16–13	-0.01	20%	24 Jun →
dust2	1–13	-0.04	27%	24 Jun →
ancient	3–13	0.02	29%	24 Jun →
inferno	13–8	0.06	43%	24 Jun →
inferno	9–13	0.02	31%	24 Jun →
train	13–10	0.05	39%	23 Jun →
train	13–9	0.11	32%	23 Jun →
ancient	13–11	-0.02	25%	23 Jun →
ancient	9–3	-0.05	29%	15 Jun →
anubis	12–12	0.03	33%	15 Jun →
inferno	13–2	0.03	29%	15 Jun →
mirage	0–13	-0.06	50%	9 Jun →
anubis	13–6	-0.02	52%	27 May →
mirage	11–13	0.05	51%	21 May →
train	13–5	0.12	40%	20 May →
dust2	13–4	0.12	45%	16 May →
dust2	1–1	0.47	100%	16 May →
ancient	0–13	-0.01	29%	16 May →
vertigo	5–1	0.05	22%	15 May →
ancient	8–13	-0.05	26%	14 May →
poseidon	8–8	0.06	24%	8 May →
inferno	10–13	0.02	33%	7 May →