Doozz — CS2 Stats

76561198067333730[U:1:107068002]Steam profile ↗✓ No bans

213Tracked matches53%Win rate2021Tracked since

CSDB Rating6.2 SolidAggressive Rifler

Premier CS Rating20,499Pink band · top ~8% of ranked players (population est.)

CSDB Leaderboard#5038 of 11851 tracked

FaceitLevel 5Top 67.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim82

Positioning51

Utility46

0–100 skill scores via Leetify.

Recent form

STEADY59–39–2Last 10059%Win rateWWWLWLWLWL

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

Player DNA

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

Aim8.2

Aggression6.6

Utility4.6

Positioning5.1

Opening Duels2.1

Clutch0.0

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 89% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

Where you differ: lower 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

Areas to improve

Positioning. Positioning trails aim by 31 points — deaths here waste a strong aim profile.

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 578ms 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

Aim8.2

Positioning5.1

Utility4.6

Mechanics7.0

Opening Duels2.1

Win Impact6.1

Composite 6.2/10 (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 rating0.00−0.02

first ⅓ avg 0.02 → last ⅓ avg 0.00

Reaction time600ms−67ms

first ⅓ avg 666ms → last ⅓ avg 600ms

Headshot accuracy25.9%+0.3%

first ⅓ avg 25.6% → last ⅓ avg 25.9%

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

0.23Best rating — nuke 2–3

13–0Biggest win — dust2

9Longest win streak

W3Current streak

4–8In matches decided by ≤2 rounds

6Overtime games

Map breakdown

ancientBest map · 69% over 16anubisWeakest map · 20% over 5

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	33	20–13	61%	0.02
ancient	S	16	11–5	69%	0.02
mirage	A	16	10–6	63%	0.02
inferno	C	9	4–5	44%	0.01
overpass	A	8	5–3	63%	0.03
anubis	D	5	1–4	20%	-0.02
nuke	—	4	1–3	25%	0.07
train	—	4	2–2	50%	-0.00
vertigo	—	3	3–0	100%	0.03
office	—	1	1–0	100%	0.01
italy	—	1	1–0	100%	0.04

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

29Matches

52%Win rate

1.20Avg K/D

99.5ADR

46%Headshot %

Clutches & streaks

20%1v1 clutch win

14%1v2 clutch win

5Longest win streak

Recent Faceit resultsWWWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	4	75%	1.24	17.0
Anubis	3	33%	0.98	15.7
Vertigo	2	50%	1.33	16.0
Mirage	1	100%	1.38	36.0
Ancient	1	100%	2.36	26.0
Inferno	1	100%	1.55	17.0

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.

25.9%Headshot accuracy

33.2%Accuracy (enemy spotted)

35.2%Spray accuracy

81.7%Counter-strafing

8.0°Preaim

578msReaction time

31.9%T opening success

44.6%CT opening success

0.56Enemies flashed / flash

5.4%Flash assists

8.93HE damage / grenade

9.86Flashes / 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 31.9007% — 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.

20% win rate across 5 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
ancient	16–13	0.03	21%	5 Jul →
mirage	13–6	0.10	21%	5 Jul →
overpass	13–5	0.08	20%	5 Jul →
ancient	8–13	0.04	21%	5 Jul →
vertigo	13–9	-0.01	14%	28 Jun →
mirage	10–13	-0.02	26%	28 Jun →
office	13–10	0.01	27%	25 Jun →
dust2	11–13	-0.04	17%	25 Jun →
ancient	16–14	-0.01	15%	23 Jun →
anubis	9–13	-0.05	29%	22 Jun →
anubis	3–13	-0.05	29%	20 Jun →
dust2	9–13	0.02	60%	19 Jun →
dust2	6–13	-0.06	38%	19 Jun →
inferno	11–13	-0.03	18%	17 Jun →
dust2	9–13	-0.00	20%	17 Jun →
ancient	13–10	-0.03	32%	16 Jun →
mirage	13–5	0.03	34%	16 Jun →
mirage	16–12	0.05	21%	15 Jun →
vertigo	13–6	0.07	34%	15 Jun →
italy	13–6	0.04	27%	15 Jun →
inferno	4–13	-0.07	23%	15 Jun →
mirage	1–13	-0.07	38%	15 Jun →
dust2	13–9	-0.03	50%	14 Jun →
mirage	13–5	0.05	19%	14 Jun →
dust2	13–10	-0.06	15%	14 Jun →
inferno	10–13	-0.03	33%	12 Jun →
dust2	11–13	0.03	29%	1 Jun →
dust2	13–10	0.01	16%	30 May →
inferno	11–13	0.04	22%	30 May →
ancient	13–5	0.06	20%	30 May →
dust2	13–6	0.07	29%	30 May →
nuke	1–13	-0.04	16%	30 May →
dust2	13–4	0.05	19%	30 May →
inferno	16–12	0.07	20%	30 May →
anubis	15–15	-0.03	24%	30 May →
overpass	13–5	0.08	23%	30 May →
inferno	13–6	0.10	26%	30 May →
dust2	10–13	-0.03	52%	23 May →
vertigo	13–10	0.04	15%	23 May →
dust2	13–11	0.05	26%	23 May →
ancient	13–2	0.01	17%	23 May →
dust2	8–13	-0.05	14%	23 May →
dust2	13–3	0.08	28%	23 May →
dust2	10–13	0.02	30%	23 Feb →
inferno	10–5	0.03	21%	23 Feb →
dust2	12–12	-0.02	16%	21 Feb →
ancient	13–10	0.02	17%	21 Feb →
mirage	13–10	0.02	17%	21 Feb →
ancient	7–13	-0.04	16%	15 Sept →
overpass	13–6	-0.00	37%	15 Sept →
dust2	13–2	0.10	29%	15 Sept →
overpass	13–8	-0.02	12%	13 Sept →
ancient	13–8	0.01	19%	13 Sept →
dust2	13–8	0.01	9%	13 Sept →
nuke	13–8	0.04	48%	5 Sept →
mirage	13–1	0.01	30%	2 Sept →
mirage	8–13	0.09	24%	2 Sept →
train	13–5	-0.02	28%	2 Sept →
ancient	13–4	0.12	25%	2 Sept →
dust2	13–5	-0.03	23%	2 Sept →
ancient	13–11	-0.01	26%	2 Sept →
mirage	13–11	0.08	18%	30 Aug →
dust2	6–13	0.03	22%	30 Aug →
dust2	13–7	-0.08	70%	30 Aug →
ancient	13–5	0.07	58%	30 Aug →
mirage	11–13	-0.00	53%	30 Aug →
mirage	13–9	0.04	36%	27 Aug →
dust2	13–5	0.05	25%	27 Aug →
dust2	13–9	-0.05	31%	27 Aug →
dust2	13–8	0.16	47%	22 Aug →
dust2	13–0	0.00	10%	22 Aug →
dust2	13–9	0.03	50%	10 Aug →
ancient	13–9	0.04	18%	10 Aug →
overpass	13–6	-0.02	21%	10 Aug →
dust2	13–2	0.20	36%	10 Aug →
train	7–13	0.01	28%	31 Jul →
inferno	8–13	-0.04	20%	30 Jul →
overpass	13–16	0.07	20%	26 Jul →
inferno	13–3	0.04	14%	26 Jul →
overpass	9–8	0.01	73%	25 Jul →
mirage	13–2	-0.03	57%	25 Jul →
nuke	6–13	0.07	27%	25 Jul →
ancient	6–13	-0.04	38%	25 Jul →
dust2	13–2	0.03	23%	25 Jul →
dust2	13–5	0.15	25%	24 Jul →
dust2	8–13	-0.00	17%	23 Jul →
mirage	9–13	-0.03	18%	23 Jul →
overpass	10–13	0.01	21%	19 Jul →
ancient	4–13	0.07	32%	10 Jul →
anubis	13–5	0.05	12%	10 Jul →
train	7–13	0.02	18%	10 Jul →
nuke	2–3	0.23	38%	10 Jul →
anubis	1–13	-0.00	25%	27 Jun →
ancient	0–4	-0.06	25%	7 Jun →
mirage	13–7	0.06	18%	7 Jun →
mirage	5–13	-0.06	14%	5 Jun →
train	13–10	-0.01	10%	4 Jun →
dust2	11–13	-0.02	16%	3 Jun →
dust2	13–6	-0.03	12%	28 May →
dust2	2–13	-0.07	5%	27 May →