zerooreos — CS2 Stats

76561198207398821[U:1:247133093]Steam profile ↗✓ No bans

813Tracked matches36%Win rate2020Tracked since

CSDB Rating4.0 DevelopingClutch Specialist

Premier CS Rating11,456Blue band · top ~47.2% of ranked players (population est.)

Ladder ranks via Leetify

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Performance scores

Aim42

Positioning52

Utility54

0–100 skill scores via Leetify.

Recent form

STEADY38–57–5Last 10038%Win rateTWWLWLLWLL

Last 10 vs previous 10: +0pp win rate · +0.01 avg rating

Player DNA

Primary style: Clutch Specialist — Late-round 1vX conversion well above par.

Aim4.2

Aggression7.1

Utility5.4

Positioning5.2

Opening Duels3.1

Clutch9.4

Strong CT-side openerEffective flashesReliable in 1v1s

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 85% playstyle similarity

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

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

T-side openings. Opening success drops from 50% on CT to 35% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 646ms 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

Aim4.2

Positioning5.2

Utility5.4

Mechanics4.9

Opening Duels3.1

Win Impact0.2

Composite 4.0/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.00+0.02

first ⅓ avg -0.02 → last ⅓ avg -0.00

Reaction time649ms−30ms

first ⅓ avg 679ms → last ⅓ avg 649ms

Headshot accuracy20.2%+2.5%

first ⅓ avg 17.7% → last ⅓ avg 20.2%

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

0.14Best rating — mirage 13–1

13–1Biggest win — mirage

7Longest win streak

9–5In matches decided by ≤2 rounds

6Overtime games

Map breakdown

mirageBest map · 69% over 13infernoWeakest map · 20% over 15

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	19	7–12	37%	0.00
cache	D	15	5–10	33%	0.00
inferno	D	15	3–12	20%	-0.01
mirage	S	13	9–4	69%	0.02
anubis	A	11	6–5	55%	0.01
nuke	C	10	4–6	40%	-0.00
ancient	D	7	2–5	29%	-0.01
overpass	—	4	1–3	25%	0.03
vertigo	—	2	0–2	0%	-0.05
train	—	2	1–1	50%	-0.03
office	—	1	0–1	0%	0.03
poseidon	—	1	0–1	0%	-0.26

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (20% over 15). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

235Matches

50%Win rate

1.18Avg K/D

81.7ADR

39%Headshot %

Clutches & streaks

67%1v1 clutch win

0%1v2 clutch win

7Longest win streak

Recent Faceit resultsWWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	17	41%	1.18	16.1
Anubis	16	56%	1.30	18.5
Inferno	13	38%	1.15	15.7
Vertigo	11	64%	1.14	15.6
Ancient	9	44%	1.42	18.3
Nuke	7	71%	0.99	15.4
Overpass	5	80%	1.25	13.4
Dust2	3	33%	1.23	24.0

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.

19.5%Headshot accuracy

30.6%Accuracy (enemy spotted)

31.4%Spray accuracy

72.2%Counter-strafing

12.2°Preaim

646msReaction time

34.7%T opening success

50.4%CT opening success

0.70Enemies flashed / flash

8.0%Flash assists

11.65HE damage / grenade

8.45Flashes / 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 12.1886° — above the 12° mark we flag
Aim Training →

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.

20% win rate across 15 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
dust2	15–15	0.02	20%	24 Aug →
cache	13–7	0.00	20%	24 Aug →
mirage	13–7	0.02	31%	24 Aug →
dust2	7–13	0.00	12%	22 Aug →
inferno	16–13	0.02	19%	22 Aug →
cache	11–13	0.06	23%	22 Aug →
dust2	10–13	-0.00	28%	21 Aug →
nuke	13–9	0.06	26%	21 Aug →
inferno	5–13	0.00	23%	21 Aug →
nuke	2–13	-0.08	22%	18 Aug →
mirage	13–10	-0.02	17%	18 Aug →
inferno	7–13	-0.04	20%	18 Aug →
anubis	9–13	0.03	27%	18 Aug →
ancient	13–10	0.05	17%	18 Aug →
anubis	13–4	0.05	15%	14 Aug →
mirage	13–9	0.01	17%	12 Aug →
mirage	10–13	-0.04	8%	3 Aug →
dust2	7–13	0.02	24%	3 Aug →
ancient	4–13	-0.05	14%	3 Aug →
nuke	6–13	0.01	12%	1 Aug →
dust2	13–11	-0.01	19%	31 Jul →
vertigo	12–12	-0.03	11%	30 Jul →
inferno	5–13	-0.14	15%	30 Jul →
nuke	2–13	0.01	26%	30 Jul →
cache	11–13	0.01	13%	29 Jul →
train	0–13	-0.04	47%	28 Jul →
overpass	3–13	0.03	18%	28 Jul →
cache	6–13	-0.08	20%	28 Jul →
mirage	13–8	0.04	18%	28 Jul →
vertigo	4–13	-0.07	17%	28 Jul →
inferno	3–9	0.05	28%	28 Jul →
ancient	10–13	-0.00	22%	28 Jul →
anubis	16–14	0.06	18%	28 Jul →
dust2	4–13	-0.04	19%	28 Jul →
nuke	13–10	0.07	27%	28 Jul →
dust2	5–13	0.08	24%	26 Jul →
mirage	13–1	0.14	22%	26 Jul →
office	3–13	0.03	27%	26 Jul →
nuke	7–13	-0.02	28%	26 Jul →
dust2	7–13	-0.04	21%	23 Jul →
nuke	10–13	-0.06	21%	23 Jul →
cache	13–9	0.05	18%	17 Jul →
inferno	13–11	0.11	29%	16 Jul →
inferno	9–13	-0.00	29%	15 Jul →
anubis	13–7	0.09	20%	15 Jul →
ancient	6–8	0.00	19%	11 Jul →
inferno	7–13	0.03	21%	11 Jul →
mirage	13–9	-0.02	11%	11 Jul →
dust2	7–13	-0.03	26%	11 Jul →
inferno	7–13	-0.01	17%	9 Jul →
mirage	13–11	0.08	17%	9 Jul →
cache	13–8	0.03	27%	9 Jul →
cache	13–4	0.12	40%	7 Jul →
inferno	16–14	-0.02	15%	2 Jul →
ancient	13–4	0.04	20%	2 Jul →
mirage	13–3	0.08	15%	1 Jul →
dust2	13–8	0.01	20%	30 Jun →
overpass	11–13	0.04	20%	29 Jun →
anubis	11–13	-0.00	14%	28 Jun →
dust2	13–3	0.04	29%	28 Jun →
dust2	13–10	0.01	27%	28 Jun →
dust2	13–7	0.03	29%	27 Jun →
inferno	4–13	-0.08	31%	27 Jun →
ancient	7–13	-0.08	13%	27 Jun →
overpass	13–6	0.07	14%	26 Jun →
inferno	4–13	-0.07	8%	20 Jun →
anubis	9–13	-0.08	25%	20 Jun →
anubis	13–7	0.03	16%	20 Jun →
dust2	10–13	0.00	13%	20 Jun →
train	13–6	-0.02	16%	18 Jun →
anubis	9–13	-0.09	18%	18 Jun →
anubis	16–14	0.02	20%	15 Jun →
cache	0–13	-0.03	7%	14 Jun →
inferno	6–13	-0.05	10%	14 Jun →
dust2	5–13	-0.05	28%	14 Jun →
mirage	10–13	-0.03	33%	14 Jun →
cache	9–13	-0.02	23%	31 May →
poseidon	1–9	-0.26	15%	28 May →
nuke	3–13	-0.05	9%	28 May →
nuke	13–10	0.03	17%	28 May →
dust2	15–15	-0.07	17%	23 May →
ancient	10–13	-0.06	8%	22 May →
anubis	5–13	-0.05	6%	22 May →
overpass	5–13	-0.03	31%	22 May →
cache	3–13	-0.06	32%	2 May →
cache	4–13	-0.03	19%	1 May →
mirage	8–13	0.01	10%	1 May →
cache	13–11	0.06	20%	30 Apr →
mirage	13–11	0.01	21%	30 Apr →
inferno	10–13	0.01	22%	30 Apr →
cache	9–13	-0.01	11%	29 Apr →
cache	12–12	-0.03	31%	29 Apr →
cache	12–12	-0.02	23%	29 Apr →
dust2	5–13	-0.04	15%	28 Apr →
nuke	13–8	0.04	18%	27 Apr →
anubis	13–11	0.02	21%	18 Apr →
dust2	13–10	0.06	10%	18 Apr →
inferno	9–13	0.01	16%	16 Apr →
mirage	5–13	0.03	16%	11 Apr →
dust2	13–10	-0.00	14%	4 Apr →