DownUnderDaz 🎗 — CS2 Stats

AU76561199071628841[U:1:1111363113]Steam profile ↗✓ No bans

2,164Tracked matches36%Win rate2020Tracked since

2,649Hours in CS

CSDB Rating3.1 LearningPositional Player

Premier CS Rating1,058Grey band · top ~95.5% of ranked players (population est.)

CSDB Leaderboard#201843 of 251255 tracked

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 18 Sep 2026 (23 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 1,058 -859 14 Aug – 18 Sept · 5 days played

1,917Peak Premier in tracked matches

30Days played since 2026-07-13

Premier CS Rating

859 below peak (1,917)
-542 over 30 days · declining
Next: Light Blue band at 5,000 — 3,942 to go

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

How this compares with the same rank

Median values for Grey band among CSDB-tracked players (n=3,645), 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	Grey band median	Light Blue band median	vs Light Blue band
Headshot rate	31.5%	38.2%	39.9%	8.4% short
Shot accuracy	11.0%	3.6%	7.0%	above
Kill/death ratio	0.89	0.83	0.92	0.03 short
Match win rate	44.8%	40.2%	42.3%	above

This profile matches the typical Light Blue band player on 2 of 4 comparable metrics.

Widest gap: Headshot rate. That is the metric furthest from the Light Blue band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim41

Positioning40

Utility39

0–100 skill scores via Leetify.

Recent form

COLD32–62–6Last 10032%Win rateLWWTLLLLLW

Last 10 vs previous 10: 0pp win rate · +0.01 avg rating · −0.1pp headshot accuracy · +22ms reaction

Win rate 0pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

2–2–1 · 40% win rate
Avg rating -0.05
Avg headshot accuracy 13%
Avg reaction 528ms

Last 10

3–6–1 · 30% win rate
Avg rating -0.03
Avg headshot accuracy 12%
Avg reaction 559ms

Last 20

6–13–1 · 30% win rate
Avg rating -0.03
Avg headshot accuracy 12%
Avg reaction 549ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Positional Player — Positioning stands above the rest of this profile (+0.9 against its own average).

Aim4.1

Utility3.9

Positioning4.0

Opening Duels1.5

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

Plays most like ZywOo 80% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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. 587ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 70% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim4.1

Positioning4.0

Utility3.9

Mechanics4.4

Opening Duels2.0

Win Impact0.2

Composite 3.1/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.01

first ⅓ avg -0.01 → last ⅓ avg -0.02

Reaction time571ms−98ms

first ⅓ avg 669ms → last ⅓ avg 571ms

Headshot accuracy11.6%−1.7%

first ⅓ avg 13.3% → last ⅓ avg 11.6%

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.

Personal bests

0.14Best match rating · 13–4 · train, 22 Sept →

29%Best headshot accuracy · 11–5 · cache, 23 Jul →

469msFastest reaction time · 11–13 · inferno, 21 Sept →

13–2Biggest win · cache, 15 Sept →

Across the last 100 tracked matches.

Highlights

2Longest win streak

6–7In matches decided by ≤2 rounds

3Overtime games

Map breakdown

nukeBest map · 40% over 10trainWeakest map · 29% over 7

Map	Grade	Played	Record	Win rate	Avg rating
dust2	D	32	11–21	34%	-0.02
cache	C	13	5–8	38%	0.00
inferno	D	12	4–8	33%	-0.05
ancient	D	10	3–7	30%	-0.03
nuke	C	10	4–6	40%	-0.03
mirage	C	8	3–5	38%	-0.03
train	D	7	2–5	29%	-0.01
anubis	—	4	0–4	0%	-0.04
vertigo	—	1	0–1	0%	-0.06
office	—	1	0–1	0%	0.00
italy	—	1	0–1	0%	-0.03
overpass	—	1	0–1	0%	0.04

Across the last 100 tracked matches.

Lifetime stats

110,206Lifetime kills

0.89K/D · Top 50% of Grey band

9,658Matches

44.8%Match win rate · Top 25% of Grey band

31.5%Headshot %

11.0%Shot accuracy · Top 25% of Grey band

6,996MVPs

2,649Hours (in match)

3,966Bombs planted

1,134Bombs defused

Most-used weapons

AK-4734,621

M4A4 / M4A1-S25,335

SG 5537,997

AWP5,658

P904,781

Galil AR4,559

MP94,048

AUG4,002

Tec-92,963

Five-SeveN2,802

Lifetime map wins

8,099vertigo

5,199dust2

4,365inferno

4,084nuke

3,931cbble

2,332train

162office

53lake

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

Faceit stats

Combat

9Matches

11%Win rate

0.23Avg K/D

—ADR

50%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

1Longest win streak

Recent Faceit resultsLLLLL

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.

12.1%Headshot accuracy

31.2%Accuracy (enemy spotted)

33.0%Spray accuracy

69.8%Counter-strafing

11.3°Preaim

587msReaction time

38.5%T opening success

37.4%CT opening success

0.41Enemies flashed / flash

7.0%Flash assists

9.33HE damage / grenade

5.86Flashes / 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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 12.0844% — below the 15% mark we flag
Aim Training →
Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4105 — below the 0.5 mark we flag
Grenade Lineups →
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 38.4728% — below the 40% mark we flag

Spend your practice time on Train

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

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
vertigo	8–13	-0.06	14%	11 Oct →
dust2	7–5	-0.05	8%	11 Oct →
train	13–11	-0.04	18%	11 Oct →
dust2	12–12	-0.03	13%	7 Oct →
inferno	5–13	-0.09	12%	7 Oct →
train	7–13	0.01	9%	7 Oct →
ancient	6–13	0.03	13%	5 Oct →
mirage	5–13	0.01	9%	5 Oct →
dust2	4–13	-0.01	9%	23 Sept →
nuke	13–8	-0.02	13%	23 Sept →
mirage	8–13	-0.08	17%	23 Sept →
inferno	1–13	-0.11	10%	23 Sept →
train	13–4	0.14	18%	22 Sept →
ancient	4–13	-0.12	18%	22 Sept →
mirage	2–1	-0.06	0%	22 Sept →
inferno	11–13	0.04	9%	21 Sept →
dust2	8–13	0.01	10%	21 Sept →
nuke	13–10	-0.05	6%	21 Sept →
nuke	3–13	-0.04	11%	18 Sept →
ancient	5–13	-0.09	19%	18 Sept →
cache	13–2	0.13	8%	15 Sept →
inferno	13–10	0.04	19%	15 Sept →
dust2	5–13	-0.01	11%	15 Sept →
dust2	13–6	0.02	8%	15 Sept →
dust2	12–12	-0.05	8%	15 Sept →
cache	11–13	0.04	13%	11 Sept →
inferno	2–13	-0.09	14%	11 Sept →
dust2	9–13	-0.07	14%	11 Sept →
ancient	13–9	0.01	5%	11 Sept →
dust2	11–13	-0.03	16%	11 Sept →
dust2	7–13	-0.07	7%	11 Sept →
ancient	6–13	0.00	11%	8 Sept →
office	6–13	0.00	15%	8 Sept →
dust2	13–7	-0.05	4%	8 Sept →
dust2	6–13	-0.03	4%	31 Aug →
ancient	11–13	0.01	15%	31 Aug →
dust2	5–13	-0.03	19%	31 Aug →
dust2	6–13	-0.04	24%	30 Aug →
anubis	8–13	-0.04	16%	30 Aug →
dust2	11–13	-0.05	9%	30 Aug →
dust2	13–2	0.04	11%	21 Aug →
italy	4–13	-0.03	19%	21 Aug →
overpass	12–12	0.04	12%	20 Aug →
ancient	13–2	0.03	13%	20 Aug →
dust2	8–13	-0.02	7%	19 Aug →
ancient	7–13	-0.04	16%	19 Aug →
nuke	10–13	-0.06	4%	19 Aug →
train	8–13	-0.04	10%	18 Aug →
cache	13–10	0.01	6%	18 Aug →
dust2	3–13	-0.12	19%	18 Aug →
mirage	8–13	-0.07	6%	18 Aug →
train	8–13	-0.08	7%	18 Aug →
mirage	9–13	-0.06	6%	18 Aug →
cache	7–13	-0.04	8%	18 Aug →
nuke	11–13	-0.05	10%	15 Aug →
dust2	13–10	0.01	13%	14 Aug →
anubis	7–13	-0.02	21%	14 Aug →
inferno	16–12	-0.02	11%	14 Aug →
dust2	13–9	-0.03	11%	14 Aug →
train	12–12	0.03	10%	14 Aug →
dust2	5–13	-0.02	8%	11 Aug →
inferno	7–6	-0.07	24%	11 Aug →
dust2	13–11	-0.01	15%	11 Aug →
anubis	2–13	-0.14	14%	28 Jul →
cache	5–13	-0.06	18%	28 Jul →
dust2	7–13	-0.03	18%	28 Jul →
mirage	13–7	0.05	15%	28 Jul →
mirage	13–9	0.08	24%	28 Jul →
dust2	8–13	-0.03	6%	26 Jul →
dust2	9–13	0.06	15%	26 Jul →
cache	13–8	0.08	16%	26 Jul →
cache	4–13	-0.05	12%	24 Jul →
dust2	4–13	-0.04	16%	24 Jul →
train	6–13	-0.10	15%	23 Jul →
cache	11–5	-0.05	29%	23 Jul →
dust2	12–12	-0.07	12%	23 Jul →
nuke	6–13	-0.03	19%	23 Jul →
dust2	13–11	-0.01	16%	22 Jul →
nuke	15–15	0.00	7%	22 Jul →
dust2	16–13	0.02	14%	22 Jul →
inferno	6–13	-0.05	16%	22 Jul →
dust2	13–10	0.02	21%	22 Jul →
anubis	6–13	0.05	16%	22 Jul →
cache	11–13	0.04	22%	21 Jul →
nuke	13–10	-0.03	7%	20 Jul →
cache	13–6	0.01	14%	20 Jul →
cache	10–13	-0.02	7%	19 Jul →
dust2	3–13	-0.03	11%	19 Jul →
cache	9–13	-0.04	8%	19 Jul →
cache	3–13	-0.01	17%	19 Jul →
inferno	10–13	-0.02	4%	19 Jul →
nuke	13–10	-0.05	8%	19 Jul →
inferno	13–8	-0.05	6%	19 Jul →
nuke	9–13	0.06	10%	17 Jul →
inferno	10–13	-0.08	6%	14 Jul →
ancient	6–2	-0.05	18%	14 Jul →
mirage	6–13	-0.07	15%	14 Jul →
inferno	4–13	-0.04	10%	13 Jul →
ancient	4–13	-0.08	7%	13 Jul →
dust2	13–3	0.09	15%	13 Jul →