MarcJunior

MarcJunior — CS2 Stats

NL76561198791510906[U:1:831245178]Steam profile ↗✓ No bans

326Tracked matches64%Win rate2025Tracked since
768Hours in CS32Hrs last 2 wks
CSDB Rating7.1 StrongClutch Specialist
Premier CS Rating15,456Purple band · top ~26.6% of ranked players (population est.)
WingmanGold Nova II
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 25 Sep 2026 (6 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

15,577Peak Premier in tracked matches
28Days played since 2026-08-01

Premier CS Rating

  • At peak — 15,456
  • Next: Pink band at 20,000 — 4,544 to go
  • Reached: 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
Matches66——
Win rate59%——
K/D1.16——
Headshot %42%——

Measured 30 Aug 2026 → 1 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 Purple band among CSDB-tracked players (n=37,767), 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 playerPurple band medianPink band medianvs Pink band
Headshot rate39.2%44.3%46.9%7.7% short
Shot accuracy0.0%11.9%13.0%13.0% short
Kill/death ratio1.061.031.08meets
Match win rate54.3%45.2%46.7%above

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

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

Share this profile

CSDB.GGMarcJuniorPREMIER15,456 · Purple bandcsdb.gg/stats

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Performance scores

Aim83
Positioning63
Utility51

0–100 skill scores via Leetify.

Recent form

STEADY59–29–12Last 10059%Win rateLLLWLLWWWT

Last 10 vs previous 10: −30pp win rate · −0.06 avg rating · +1.4pp headshot accuracy · +88ms reaction

Win rate down 30pp 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

  • 1–4 · 20% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 15%
  • Avg reaction 578ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 16%
  • Avg reaction 588ms

Last 20

  • 11–7–2 · 55% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 15%
  • Avg reaction 544ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+3.6 against its own average).

Aim8.3
Utility5.1
Positioning6.3
Opening Duels4.3
Clutch10.0

Reliable 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.

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

iM

Plays most like iM 98% playstyle similarity

Most alike: positioning profile, 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

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

Reaction time. 572ms 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

Aim8.3
Positioning6.3
Utility5.1
Mechanics7.2
Opening Duels5.1
Win Impact9.8

Composite 7.1/10 (Strong), 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 rating0.01−0.01
first ⅓ avg 0.03 → last ⅓ avg 0.01
Reaction time574ms−45ms
first ⅓ avg 619ms → last ⅓ avg 574ms
Headshot accuracy14.1%−1.6%
first ⅓ avg 15.7% → last ⅓ avg 14.1%

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

0.30Best match rating · 9–4 · inferno, 15 Sept →
30%Best headshot accuracy · 13–2 · dust2, 22 Aug →
359msFastest reaction time · 13–4 · ancient, 26 Sept →
13–1Biggest win · mirage, 20 Aug →

Across the last 100 tracked matches.

Highlights

6Longest win streak
L3Current streak
6–2In matches decided by ≤2 rounds

Map breakdown

cacheBest map · 92% over 12nukeWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
dust2C219–1243%0.02
infernoB2111–1052%0.03
mirageS1814–478%0.03
cacheS1211–192%0.03
vertigoB63–350%-0.00
ancientA53–260%0.01
nukeD51–420%0.01
train—42–250%0.11
anubis—42–250%-0.03
debris—21–150%0.13
boulder—22–0100%0.06

Across the last 100 tracked matches.

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

Lifetime stats

14,095Lifetime kills
1.06K/D · Top 50% of Purple band
748Matches
54.3%Match win rate · Top 5% of Purple band
39.2%Headshot %
0.0%Shot accuracy
2,180MVPs
302Hours (in match)
932Bombs planted
157Bombs defused

Most-used weapons

Lifetime map wins

1,621dust2
832inferno
440nuke
265vertigo
217train
48office

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

Faceit stats

Combat

2Matches
0%Win rate
0.94Avg K/D
87.1ADR
48%Headshot %

Clutches & streaks

100%1v1 clutch win
33%1v2 clutch win
0Longest win streak

Recent Faceit resultsLLLLL

MapMatchesWin rateAvg K/DAvg kills
Mirage10%1.2431.0
Dust210%0.6511.0

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.

14.9%Headshot accuracy
41.2%Accuracy (enemy spotted)
41.8%Spray accuracy
82.5%Counter-strafing
8.8°Preaim
572msReaction time
55.6%T opening success
45.2%CT opening success
0.54Enemies flashed / flash
8.4%Flash assists
11.00HE damage / grenade
5.72Flashes / 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 14.9293% — below the 15% mark we flag

    Aim Training →
Spend your practice time on Nuke

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.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
vertigo8–13-0.0516%1 Oct →
dust27–13-0.0014%30 Sept →
dust27–130.0323%29 Sept →
inferno13–10-0.0113%29 Sept →
inferno5–13-0.0510%28 Sept →
dust27–13-0.0612%28 Sept →
cache13–11-0.0819%28 Sept →
inferno13–10-0.0511%28 Sept →
vertigo13–100.0122%28 Sept →
dust212–12-0.0519%27 Sept →
inferno13–90.0915%27 Sept →
ancient1–13-0.0220%27 Sept →
inferno12–120.0923%27 Sept →
dust213–80.0614%27 Sept →
vertigo13–90.119%27 Sept →
ancient13–40.0511%26 Sept →
dust213–8-0.0114%26 Sept →
mirage13–4-0.026%26 Sept →
dust213–70.0023%26 Sept →
mirage8–13-0.0510%25 Sept →
dust213–7-0.0216%25 Sept →
inferno13–9-0.0518%24 Sept →
vertigo4–13-0.0616%24 Sept →
dust213–20.1411%24 Sept →
vertigo13–10-0.0411%23 Sept →
cache13–80.1012%23 Sept →
ancient0–7-0.030%21 Sept →
dust211–130.1220%21 Sept →
mirage13–6-0.0314%21 Sept →
cache13–90.1414%21 Sept →
mirage13–110.0316%21 Sept →
mirage13–100.134%21 Sept →
nuke4–13-0.0212%21 Sept →
debris9–40.2427%16 Sept →
cache13–60.0615%15 Sept →
dust210–130.018%15 Sept →
cache13–8-0.0310%15 Sept →
dust213–30.1417%15 Sept →
inferno9–40.3018%15 Sept →
debris7–90.0116%14 Sept →
inferno9–40.2422%14 Sept →
cache13–70.0319%14 Sept →
inferno9–30.0716%24 Aug →
inferno8–8-0.0822%24 Aug →
vertigo12–120.0116%23 Aug →
mirage7–13-0.0414%23 Aug →
dust28–13-0.0511%23 Aug →
dust213–20.0330%22 Aug →
mirage13–10.0517%20 Aug →
ancient13–60.0322%17 Aug →
train13–80.0716%13 Aug →
mirage13–60.0814%11 Aug →
boulder13–70.089%11 Aug →
dust26–130.039%11 Aug →
inferno7–13-0.0612%11 Aug →
anubis4–13-0.107%10 Aug →
inferno4–13-0.0512%8 Aug →
mirage13–110.0013%8 Aug →
nuke8–130.0223%8 Aug →
inferno12–120.1119%8 Aug →
inferno7–130.0222%8 Aug →
mirage13–30.0917%8 Aug →
nuke13–6-0.0018%8 Aug →
mirage13–100.0714%8 Aug →
anubis13–100.0514%8 Aug →
ancient13–40.0513%7 Aug →
mirage8–130.0529%7 Aug →
cache13–10-0.0315%7 Aug →
inferno9–13-0.0423%7 Aug →
mirage1–13-0.0420%7 Aug →
dust213–3-0.0613%7 Aug →
inferno13–30.0217%7 Aug →
mirage13–100.0913%7 Aug →
dust212–120.0121%7 Aug →
inferno13–110.0129%7 Aug →
mirage13–40.049%7 Aug →
boulder13–80.0522%6 Aug →
dust29–00.094%6 Aug →
dust210–13-0.0415%6 Aug →
mirage13–110.0417%5 Aug →
inferno13–60.0315%5 Aug →
cache13–70.0516%5 Aug →
dust212–12-0.009%5 Aug →
dust212–12-0.0220%5 Aug →
inferno10–13-0.0212%4 Aug →
inferno13–100.0611%4 Aug →
mirage13–110.0613%4 Aug →
cache4–13-0.037%4 Aug →
inferno12–120.0513%4 Aug →
cache13–3-0.038%4 Aug →
train12–120.1115%4 Aug →
mirage13–90.0814%4 Aug →
train12–120.0612%4 Aug →
anubis13–60.027%3 Aug →
anubis2–13-0.079%1 Aug →
cache13–70.0218%1 Aug →
nuke12–12-0.0223%1 Aug →
cache13–60.1225%1 Aug →
train13–20.2130%1 Aug →
nuke7–130.0719%1 Aug →

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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