Mr_Univerz

Mr_Univerz — CS2 Stats

BE76561198348977910[U:1:388712182]Steam profile ↗✓ No bans

322Tracked matches59%Win rate2022Tracked since
459Hours in CS
CSDB Rating5.4 DevelopingPositional Player
WingmanSilver Elite Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 3 Sep 2026 (29 days ago). Ranks are recorded once per day this page is viewed.

+12Tracked matches · now 322
0.0ppWin rate · 59.3% → 59.3%

Rating over time

58Days played since 2026-04-17

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled.

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches16——
Win rate44%——
K/D0.71——
Headshot %33%——

Measured 1 Sep 2026 → 2 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

Performance scores

Aim78
Positioning39
Utility7

0–100 skill scores via Leetify.

Recent form

STEADY46–49–5Last 10046%Win rateLLWLWWWLWW

Last 10 vs previous 10: +20pp win rate · −0.01 avg rating · −2.6pp headshot accuracy · −116ms 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 -0.07
  • Avg headshot accuracy 12%
  • Avg reaction 483ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 13%
  • Avg reaction 553ms

Last 20

  • 10–8–2 · 50% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 14%
  • Avg reaction 611ms

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 (+2.2 against its own average).

Aim7.8
Utility0.7
Positioning3.9
Opening Duels1.1
Clutch1.0

Limited 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

ropz

Plays most like ropz 78% playstyle similarity

Most alike: aim profile, positioning profile.

Where you differ: lower utility contribution; lower opening-duel success.

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 40 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.

T-side openings. Opening success drops from 41% on CT to 25% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 622ms 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

Aim7.8
Positioning3.9
Utility0.7
Mechanics8.0
Opening Duels1.4
Win Impact8.1

Composite 5.4/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.05−0.01
first ⅓ avg -0.04 → last ⅓ avg -0.05
Reaction time622ms−136ms
first ⅓ avg 758ms → last ⅓ avg 622ms
Headshot accuracy13.4%−0.1%
first ⅓ avg 13.5% → last ⅓ avg 13.4%

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

0.08Best match rating · 13–0 · dust2, 29 Jul →
33%Best headshot accuracy · 6–13 · nuke, 9 May →
492msFastest reaction time · 9–13 · inferno, 28 Aug →
13–0Biggest win · inferno, 4 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L2Current streak
7–5In matches decided by ≤2 rounds
1Overtime games

Map breakdown

infernoBest map · 67% over 9vertigoWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
cacheC3615–2142%-0.03
mirageC166–1038%-0.05
nukeC114–736%-0.04
dust2B105–550%-0.01
infernoS96–367%-0.03
vertigoD51–420%-0.05
ancient—41–325%-0.04
anubis—43–175%-0.00
train—44–0100%-0.01
overpass—11–0100%-0.02

Across the last 100 tracked matches.

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

Lifetime stats

18,042Lifetime kills
1.06K/D · Top 50% of tracked players
1,002Matches
42.7%Match win rate
52.5%Headshot % · Top 25% of tracked players
0.9%Shot accuracy
1,284MVPs
459Hours (in match)
456Bombs planted
140Bombs defused

Most-used weapons

Lifetime map wins

1,208dust2
1,144nuke
1,124inferno
617vertigo
555train
10office
8italy

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

Faceit stats

Combat

18Matches
33%Win rate
0.85Avg K/D
59.3ADR
34%Headshot %

Clutches & streaks

25%1v1 clutch win
33%1v2 clutch win
2Longest win streak

Recent Faceit resultsLLLLL

MapMatchesWin rateAvg K/DAvg kills
Mirage540%0.6811.0
Inferno425%0.8211.0
Nuke425%0.5810.0
Anubis250%0.9613.5
Cache250%1.9813.0
Dust210%0.436.0

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.

14.6%Headshot accuracy
38.6%Accuracy (enemy spotted)
36.6%Spray accuracy
85.8%Counter-strafing
7.4°Preaim
622msReaction time
24.7%T opening success
41.1%CT opening success
0.12Enemies flashed / flash
0.0%Flash assists
1.68HE damage / grenade
1.08Flashes / 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.

  1. 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 14.5899% — below the 15% mark we flag

    Aim Training →
  2. 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 0.1232 — below the 0.5 mark we flag

    Grenade Lineups →
  3. 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 24.7295% — below the 40% mark we flag

Spend your practice time on Vertigo

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.

Vertigo callouts & strategy →Vertigo grenade lineups →

Recent matches

MapScoreRatingHS%Date
vertigo5–13-0.079%24 Sept →
mirage0–13-0.080%19 Sept →
cache13–9-0.0311%15 Sept →
mirage7–13-0.1025%9 Sept →
cache13–10-0.0616%9 Sept →
cache13–9-0.0321%7 Sept →
inferno13–6-0.039%7 Sept →
nuke8–13-0.0114%4 Sept →
inferno13–0-0.068%4 Sept →
dust213–4-0.0417%4 Sept →
nuke9–13-0.1321%31 Aug →
nuke13–8-0.0513%29 Aug →
inferno9–13-0.0327%28 Aug →
cache12–12-0.0018%28 Aug →
inferno13–11-0.0513%27 Aug →
cache6–13-0.0422%24 Aug →
mirage13–50.0214%22 Aug →
mirage12–12-0.0421%22 Aug →
dust23–13-0.040%22 Aug →
inferno13–10-0.018%21 Aug →
ancient13–0-0.020%21 Aug →
anubis12–12-0.0317%21 Aug →
cache13–11-0.0820%21 Aug →
ancient9–13-0.0511%20 Aug →
inferno9–13-0.1117%20 Aug →
vertigo13–7-0.0212%19 Aug →
mirage2–13-0.0610%19 Aug →
mirage13–8-0.0915%17 Aug →
train13–9-0.0614%17 Aug →
anubis8–2-0.050%17 Aug →
cache7–13-0.0311%17 Aug →
dust27–13-0.0620%15 Aug →
nuke13–5-0.028%14 Aug →
dust213–00.0722%14 Aug →
dust210–13-0.0215%13 Aug →
cache13–3-0.0213%12 Aug →
cache11–130.0220%12 Aug →
train13–70.0219%11 Aug →
train13–80.0521%10 Aug →
cache13–90.016%29 Jul →
dust213–00.0814%29 Jul →
vertigo10–13-0.0419%29 Jul →
cache8–13-0.0414%28 Jul →
inferno13–100.0217%27 Jul →
mirage16–13-0.073%27 Jul →
overpass13–11-0.026%24 Jul →
nuke13–110.026%24 Jul →
vertigo4–13-0.0611%24 Jul →
nuke7–13-0.077%23 Jul →
mirage13–11-0.0217%23 Jul →
mirage8–13-0.1120%23 Jul →
cache11–13-0.0021%22 Jul →
mirage11–13-0.067%22 Jul →
dust210–130.0522%22 Jul →
cache10–130.0211%18 Jul →
cache6–130.0517%6 Jul →
mirage9–20.020%6 Jul →
inferno13–6-0.0122%6 Jul →
cache13–60.0316%4 Jul →
mirage11–13-0.0419%3 Jul →
inferno12–12-0.018%3 Jul →
vertigo8–13-0.0618%11 Jun →
ancient4–13-0.046%11 Jun →
dust27–13-0.128%8 Jun →
nuke13–20.0711%7 Jun →
cache5–13-0.079%7 Jun →
cache4–13-0.0320%6 Jun →
cache13–2-0.030%1 Jun →
mirage4–13-0.0713%29 May →
anubis13–100.034%29 May →
nuke4–13-0.079%26 May →
cache13–50.0425%20 May →
cache12–12-0.0114%18 May →
cache13–6-0.1112%17 May →
cache9–13-0.0220%17 May →
mirage4–13-0.0614%16 May →
cache13–7-0.038%15 May →
cache10–13-0.0721%14 May →
cache5–13-0.0517%13 May →
cache8–13-0.1018%13 May →
cache10–13-0.0117%12 May →
mirage13–9-0.0310%10 May →
cache13–11-0.060%10 May →
nuke6–13-0.0933%9 May →
cache3–13-0.0423%7 May →
dust213–90.0417%7 May →
cache13–80.0119%7 May →
cache10–13-0.0713%6 May →
anubis13–50.037%5 May →
cache13–11-0.089%5 May →
cache4–13-0.0512%3 May →
nuke7–13-0.0610%2 May →
dust213–10-0.0515%2 May →
cache13–30.039%2 May →
cache8–13-0.0417%1 May →
ancient1–8-0.038%29 Apr →
cache7–13-0.0717%29 Apr →
mirage11–13-0.037%24 Apr →
train13–10-0.0517%17 Apr →
nuke3–130.0011%17 Apr →

Match data via Leetify.

Recent teammates

Milestones

100 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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