Julz 🎗 — CS2 Stats

76561199091635838[U:1:1131370110]Steam profile ↗✓ No bans

5,086Tracked matches35%Win rate2023Tracked since

CSDB Rating3.7 LearningPositional Player

Premier CS Rating10,216Blue band · top ~53.8% of ranked players (population est.)

CSDB Leaderboard#177530 of 251255 tracked

WingmanMaster Guardian I

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 9 Oct 2026 (2 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: 10,216 +216 15 Aug – 9 Oct · 8 days played

10,895Peak Premier in tracked matches

38Days played since 2026-08-07

Premier CS Rating

679 below peak (10,895)
-679 over 30 days · declining
Next: Purple band at 15,000 — 4,784 to go
Reached: Blue band · Light Blue band

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

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Performance scores

Aim41

Positioning52

Utility50

0–100 skill scores via Leetify.

Recent form

COLD39–51–10Last 10039%Win rateWWLLLTWLLL

Last 10 vs previous 10: +20pp win rate · −0.01 avg rating · +1.0pp headshot accuracy · +63ms reaction

Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (−0.01), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

2–3 · 40% win rate
Avg rating -0.01
Avg headshot accuracy 15%
Avg reaction 659ms

Last 10

3–6–1 · 30% win rate
Avg rating -0.02
Avg headshot accuracy 12%
Avg reaction 672ms

Last 20

4–13–3 · 20% win rate
Avg rating -0.01
Avg headshot accuracy 11%
Avg reaction 640ms

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 (+1.1 against its own average).

Aim4.1

Utility5.0

Positioning5.2

Opening Duels2.2

Strong CT-side openerLimited utility dependence

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 71% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower opening-duel success; 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. 657ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 68% 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

Positioning5.2

Utility5.0

Mechanics4.0

Opening Duels3.1

Win Impact0.0

Composite 3.7/10 (Learning), 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-0.01−0.01

first ⅓ avg 0.00 → last ⅓ avg -0.01

Reaction time659ms−10ms

first ⅓ avg 668ms → last ⅓ avg 659ms

Headshot accuracy10.8%−2.3%

first ⅓ avg 13.1% → last ⅓ avg 10.8%

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

0.24Best match rating · 9–1 · inferno, 24 Aug →

28%Best headshot accuracy · 13–2 · dust2, 21 Aug →

492msFastest reaction time · 13–10 · train, 16 Aug →

13–2Biggest win · dust2, 21 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak

W2Current streak

4–6In matches decided by ≤2 rounds

5Overtime games

Map breakdown

trainBest map · 57% over 7dust2Weakest map · 34% over 32

Map	Grade	Played	Record	Win rate	Avg rating
dust2	D	32	11–21	34%	-0.01
mirage	C	14	5–9	36%	-0.02
cache	C	14	6–8	43%	0.00
ancient	C	11	4–7	36%	0.00
nuke	C	9	4–5	44%	0.03
train	A	7	4–3	57%	-0.01
inferno	C	5	2–3	40%	0.03
overpass	—	3	2–1	67%	-0.02
office	—	1	0–1	0%	-0.03
anubis	—	1	0–1	0%	-0.02
vertigo	—	1	1–0	100%	0.16
italy	—	1	0–1	0%	-0.03
boulder	—	1	0–1	0%	-0.00

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (34% over 32). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

11.2%Headshot accuracy

36.8%Accuracy (enemy spotted)

40.8%Spray accuracy

68.2%Counter-strafing

13.0°Preaim

657msReaction time

35.1%T opening success

49.7%CT opening success

0.65Enemies flashed / flash

6.5%Flash assists

10.87HE damage / grenade

3.26Flashes / 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 13.0126° — above the 12° mark we flag
Aim Training →
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 11.2009% — below the 15% mark we flag
Aim Training →
Grenades & Utility
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 3.2567 — below the 4 mark we flag
Grenade Lineups →

Spend your practice time on Dust 2

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

34% win rate across 32 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
train	11–5	-0.05	19%	11 Oct →
train	13–8	0.06	16%	11 Oct →
train	4–13	-0.04	17%	11 Oct →
dust2	3–13	0.03	10%	10 Oct →
ancient	6–13	-0.04	10%	10 Oct →
inferno	12–12	-0.01	8%	10 Oct →
mirage	16–13	-0.04	5%	9 Oct →
dust2	7–13	-0.08	6%	9 Oct →
ancient	6–13	-0.00	11%	5 Oct →
mirage	5–13	-0.00	14%	5 Oct →
dust2	12–12	-0.03	11%	4 Oct →
ancient	13–4	0.00	16%	4 Oct →
dust2	11–13	-0.02	14%	3 Oct →
cache	12–12	-0.03	8%	3 Oct →
nuke	2–13	-0.04	15%	1 Oct →
cache	6–13	0.04	4%	27 Sept →
mirage	4–13	-0.03	8%	27 Sept →
mirage	5–13	-0.03	10%	27 Sept →
cache	5–13	0.06	8%	26 Sept →
dust2	8–13	-0.01	13%	26 Sept →
train	12–12	0.01	12%	26 Sept →
dust2	13–9	0.01	17%	26 Sept →
ancient	9–13	0.01	10%	24 Sept →
dust2	4–13	-0.05	12%	23 Sept →
nuke	13–8	0.01	16%	23 Sept →
cache	13–5	-0.05	8%	23 Sept →
mirage	11–13	0.02	10%	23 Sept →
cache	13–9	-0.01	12%	23 Sept →
train	13–4	0.01	11%	22 Sept →
ancient	4–13	0.02	9%	22 Sept →
mirage	2–1	-0.00	0%	22 Sept →
dust2	6–13	0.01	10%	22 Sept →
inferno	11–13	-0.02	6%	21 Sept →
dust2	8–13	-0.04	16%	21 Sept →
nuke	13–10	0.05	11%	21 Sept →
dust2	5–13	-0.05	16%	15 Sept →
dust2	13–6	0.06	15%	15 Sept →
dust2	12–12	-0.04	16%	15 Sept →
dust2	13–7	0.06	14%	14 Sept →
nuke	13–6	0.07	17%	14 Sept →
inferno	13–7	-0.07	7%	12 Sept →
cache	12–12	0.01	14%	12 Sept →
dust2	9–13	-0.04	5%	12 Sept →
overpass	13–8	-0.05	16%	11 Sept →
ancient	6–13	-0.08	20%	8 Sept →
office	6–13	-0.03	14%	8 Sept →
dust2	13–7	0.04	21%	8 Sept →
dust2	13–11	-0.03	14%	5 Sept →
dust2	13–7	0.06	12%	5 Sept →
ancient	16–13	-0.02	10%	4 Sept →
dust2	5–13	-0.07	16%	31 Aug →
dust2	3–13	-0.07	9%	31 Aug →
dust2	12–12	-0.09	20%	29 Aug →
mirage	6–13	-0.04	17%	29 Aug →
cache	5–13	-0.06	22%	29 Aug →
cache	1–13	-0.02	12%	29 Aug →
anubis	10–13	-0.02	13%	29 Aug →
cache	13–11	0.10	21%	27 Aug →
vertigo	13–4	0.16	10%	26 Aug →
dust2	13–3	0.08	15%	26 Aug →
ancient	4–13	0.00	8%	25 Aug →
mirage	9–13	-0.09	12%	25 Aug →
dust2	5–13	0.03	17%	25 Aug →
nuke	8–13	-0.01	7%	24 Aug →
cache	13–8	-0.00	19%	24 Aug →
inferno	9–1	0.24	20%	24 Aug →
mirage	13–5	-0.02	14%	24 Aug →
overpass	13–7	0.02	9%	23 Aug →
dust2	16–14	-0.01	21%	23 Aug →
nuke	11–13	0.08	10%	23 Aug →
mirage	4–13	-0.02	17%	23 Aug →
dust2	12–16	-0.01	13%	22 Aug →
nuke	13–4	0.02	10%	22 Aug →
mirage	13–4	-0.03	9%	22 Aug →
dust2	6–3	-0.09	6%	22 Aug →
cache	13–4	0.06	15%	22 Aug →
mirage	13–7	-0.05	18%	21 Aug →
nuke	15–15	-0.00	10%	21 Aug →
dust2	13–2	0.00	28%	21 Aug →
italy	4–13	-0.03	9%	21 Aug →
boulder	10–13	-0.00	12%	21 Aug →
dust2	5–13	-0.02	17%	21 Aug →
overpass	12–12	-0.02	16%	20 Aug →
ancient	13–2	0.11	16%	20 Aug →
dust2	13–10	0.00	11%	19 Aug →
mirage	8–13	0.01	17%	18 Aug →
dust2	10–13	0.01	10%	17 Aug →
cache	8–13	-0.00	14%	17 Aug →
ancient	13–2	0.02	13%	16 Aug →
train	13–10	-0.04	8%	16 Aug →
dust2	4–13	0.03	15%	16 Aug →
inferno	11–13	0.02	12%	15 Aug →
nuke	11–13	0.07	15%	15 Aug →
dust2	5–13	0.02	12%	15 Aug →
cache	13–7	0.02	9%	10 Aug →
mirage	4–13	-0.01	11%	8 Aug →
train	3–13	0.01	9%	8 Aug →
ancient	12–12	-0.00	17%	8 Aug →
cache	7–13	-0.09	10%	8 Aug →
dust2	9–13	0.00	14%	7 Aug →