m4Nu

m4Nu — CS2 Stats

DE76561197974323692[U:1:14057964]Steam profile ↗✓ No bans

1,727Tracked matches43%Win rate2021Tracked since
1,816Hours in CS51Hrs last 2 wks
CSDB Rating6.2 SolidPositional Player
Premier CS Rating14,006Blue band · top ~33.7% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 2 Oct 2026 (yesterday). 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: 14,006 -9,047 7 Apr – 2 Oct · 17 days played
13,22023,053peak 23,0537 Apr2 Oct
23,275Peak Premier in tracked matches
26Days played since 2026-04-07

Premier CS Rating

  • 9,047 below peak (23,053)
  • -8,499 over 90 days
  • Next: Purple band at 15,000 — 994 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band

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

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches63——
Win rate37%——
K/D1.17——
Headshot %43%——

Measured 6 Sep 2026 → 3 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.

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=21,222), 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.

MetricThis playerBlue band medianPurple band medianvs Purple band
Headshot rate41.0%42.0%44.3%3.3% short
Shot accuracy4.8%9.6%11.9%7.1% short
Kill/death ratio1.210.981.03above
Match win rate44.3%43.8%45.2%meets

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

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

Share this profile

CSDB.GGm4NuPREMIER14,006 · Blue bandcsdb.gg/stats

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Performance scores

Aim80
Positioning74
Utility44

0–100 skill scores via Leetify.

Recent form

STEADY37–55–8Last 10037%Win rateTWLLWWLWLW

Last 10 vs previous 10: +20pp win rate · +0.02 avg rating · −2.0pp 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).

Last 5 · 10 · 20 matches

Last 5

  • 2–2–1 · 40% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 17%
  • Avg reaction 538ms

Last 10

  • 5–4–1 · 50% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 16%
  • Avg reaction 542ms

Last 20

  • 8–11–1 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 17%
  • Avg reaction 573ms

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 (+1.4 against its own average).

Aim8.0
Utility4.4
Positioning7.4
Opening Duels6.1

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

s1mple

Plays most like s1mple 92% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower aim profile; 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

Strengths

T openings. 68% T opening-duel success — entries that actually open the round.

Areas to improve

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

Reaction time. 564ms 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

Aim8.0
Positioning7.4
Utility4.4
Mechanics6.3
Opening Duels7.7
Win Impact2.6

Composite 6.2/10 (Solid), 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 rating0.02−0.02
first ⅓ avg 0.04 → last ⅓ avg 0.02
Reaction time560ms−64ms
first ⅓ avg 624ms → last ⅓ avg 560ms
Headshot accuracy17.1%+2.5%
first ⅓ avg 14.6% → last ⅓ avg 17.1%

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

0.21Best match rating · 13–4 · overpass, 5 Jul →
38%Best headshot accuracy · 9–13 · dust2, 28 Sept →
422msFastest reaction time · 13–4 · inferno, 30 Sept →
13–2Biggest win · dust2, 26 Jul →

Across the last 100 tracked matches.

Highlights

5Longest win streak
8–13In matches decided by ≤2 rounds
17Overtime games

Map breakdown

nukeBest map · 53% over 15ancientWeakest map · 14% over 7
MapGradePlayedRecordWin rateAvg rating
dust2C2810–1836%0.04
anubisC207–1335%0.04
infernoC167–944%0.02
nukeB158–753%0.02
ancientD71–614%0.00
cacheD62–433%-0.02
mirageD61–517%0.02
overpass—21–150%0.11

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

45,095Lifetime kills
1.21K/D · Top 25% of Blue band
2,221Matches
44.3%Match win rate · Top 50% of Blue band
41.0%Headshot %
4.8%Shot accuracy
6,475MVPs
927Hours (in match)
2,782Bombs planted
668Bombs defused

Most-used weapons

AK-4713,689
AWP2,718
MP91,731
MAC-101,252
P901,081
P250949

Lifetime map wins

6,479dust2
6,105inferno
3,449nuke
99vertigo
76train
13office
5italy

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

Skill profile

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

16.4%Headshot accuracy
39.4%Accuracy (enemy spotted)
42.4%Spray accuracy
78.5%Counter-strafing
9.1°Preaim
564msReaction time
67.7%T opening success
54.2%CT opening success
0.44Enemies flashed / flash
4.4%Flash assists
6.75HE damage / grenade
5.51Flashes / 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. 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 0.436 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Ancient

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

14% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient15–150.0613%2 Oct →
inferno13–40.0523%2 Oct →
cache11–130.0323%1 Oct →
anubis7–130.1211%1 Oct →
cache13–11-0.0013%1 Oct →
dust213–80.0014%30 Sept →
dust27–130.0213%30 Sept →
nuke13–11-0.0111%30 Sept →
dust210–130.0223%30 Sept →
inferno13–40.0118%30 Sept →
nuke5–13-0.0615%30 Sept →
cache13–8-0.0710%30 Sept →
inferno13–90.0311%29 Sept →
mirage3–13-0.0130%29 Sept →
anubis14–160.0218%29 Sept →
inferno13–80.1120%28 Sept →
mirage5–13-0.0314%28 Sept →
dust29–130.0638%28 Sept →
mirage9–130.0315%28 Sept →
dust23–13-0.0410%28 Sept →
inferno13–100.0414%28 Sept →
mirage15–150.0110%28 Sept →
inferno6–130.0115%28 Sept →
ancient10–130.0415%28 Sept →
anubis9–130.0614%28 Sept →
nuke8–13-0.049%27 Sept →
nuke13–50.0524%27 Sept →
dust26–13-0.0219%27 Sept →
nuke13–90.0419%27 Sept →
dust213–70.0817%27 Sept →
inferno6–13-0.0431%27 Sept →
dust213–110.0314%27 Sept →
anubis13–80.0521%27 Sept →
anubis10–130.068%26 Sept →
dust211–130.1012%26 Sept →
anubis13–70.0623%26 Sept →
mirage13–50.1211%26 Sept →
anubis8–13-0.0624%26 Sept →
ancient15–15-0.0322%25 Sept →
mirage7–13-0.029%23 Sept →
cache12–16-0.067%23 Sept →
ancient7–130.0110%23 Sept →
cache5–13-0.0422%22 Sept →
anubis4–13-0.0433%22 Sept →
dust29–130.0022%22 Sept →
ancient13–100.0310%21 Sept →
inferno4–130.018%21 Sept →
nuke5–130.0520%21 Sept →
anubis15–150.0513%21 Sept →
dust29–130.0418%21 Sept →
anubis15–15-0.0213%21 Sept →
ancient9–13-0.0314%20 Sept →
nuke15–150.0419%20 Sept →
dust213–6-0.0018%20 Sept →
nuke13–4-0.0425%20 Sept →
anubis9–13-0.0015%19 Sept →
inferno13–110.0225%19 Sept →
anubis13–70.0610%19 Sept →
nuke11–130.0914%19 Sept →
dust28–13-0.0014%19 Sept →
dust216–140.0915%19 Sept →
inferno11–130.0317%23 Aug →
nuke13–6-0.0124%23 Aug →
dust213–110.0517%23 Aug →
dust213–70.0613%23 Aug →
inferno14–160.0214%30 Jul →
nuke13–50.0712%30 Jul →
dust211–130.0820%27 Jul →
nuke9–130.0823%26 Jul →
dust211–130.0410%26 Jul →
dust210–130.048%26 Jul →
anubis11–130.0414%26 Jul →
dust213–20.1020%26 Jul →
inferno13–30.0221%22 Jul →
anubis13–110.038%22 Jul →
dust213–90.0711%22 Jul →
anubis13–110.0210%21 Jul →
ancient10–13-0.057%21 Jul →
dust213–50.019%21 Jul →
inferno13–160.0315%21 Jul →
dust29–130.048%21 Jul →
anubis16–130.0410%20 Jul →
nuke13–70.0415%20 Jul →
anubis10–130.0910%20 Jul →
dust211–130.0410%20 Jul →
inferno11–130.0410%12 Jul →
cache13–160.0518%12 Jul →
dust25–130.0419%11 Jul →
nuke10–130.0128%9 Jul →
dust214–160.0215%9 Jul →
overpass13–40.2119%5 Jul →
overpass15–150.0216%8 Apr →
anubis10–130.0220%8 Apr →
inferno15–150.0219%8 Apr →
dust210–130.0312%8 Apr →
dust214–160.0314%7 Apr →
anubis2–13-0.0315%7 Apr →
nuke13–30.0813%7 Apr →
inferno9–13-0.0214%7 Apr →
anubis13–20.1521%7 Apr →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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