[Mysterious] NEROCORLEON

[Mysterious] NEROCORLEON — CS2 Stats

DE76561198963349888[U:1:1003084160]Steam profile ↗✓ No bans

699Tracked matches43%Win rate2021Tracked since
1,308Hours in CS14Hrs last 2 wks
CSDB Rating3.6 LearningSupport
Premier CS Rating9,962Light Blue band · top ~55.1% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 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: 9,962 -2,073 19 Aug – 30 Oct · 20 days played
7,44812,035peak 12,03519 Aug30 Oct
12,035Peak Premier in tracked matches
21Days played since 2026-08-19

Premier CS Rating

  • 2,073 below peak (12,035)
  • Next: Blue band at 10,000 — 38 to go
  • Reached: Blue band · Light Blue band
  • Light Blue band first seen 2026-09-06

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 Light Blue band among CSDB-tracked players (n=8,820), 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 playerLight Blue band medianBlue band medianvs Blue band
Headshot rate35.4%39.9%42.0%6.5% short
Shot accuracy6.6%7.0%9.6%3.1% short
Kill/death ratio0.870.920.980.11 short
Match win rate39.3%42.3%43.8%4.5% short

This profile sits below the typical Blue band player on every metric we can compare.

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

Share this profile

CSDB.GG[Mysterious] NEROCORLEONPREMIER9,962 · Light Blue bandcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim28
Positioning52
Utility59

0–100 skill scores via Leetify.

Recent form

STEADY36–64Last 10036%Win rateWWLWLLLWWW

Last 10 vs previous 10: +40pp win rate · −0.03 avg rating · −1.3pp headshot accuracy · −18ms reaction

Win rate up 40pp 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 (−0.03), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 9%
  • Avg reaction 722ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 12%
  • Avg reaction 701ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 13%
  • Avg reaction 710ms

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: Support — Utility contribution stands above the rest of this profile (+1.6 against its own average).

Aim2.8
Utility5.9
Positioning5.2
Opening Duels1.8

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

jL

Plays most like jL 55% playstyle similarity

Most alike: utility contribution, positioning profile.

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. 695ms 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

Aim2.8
Positioning5.2
Utility5.9
Mechanics3.9
Opening Duels3.2
Win Impact2.8

Composite 3.6/10 (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-0.01+0.03
first ⅓ avg -0.04 → last ⅓ avg -0.01
Reaction time684ms+24ms
first ⅓ avg 660ms → last ⅓ avg 684ms
Headshot accuracy13.9%+1.1%
first ⅓ avg 12.8% → last ⅓ avg 13.9%

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

0.10Best match rating · 13–9 · cache, 11 Sept →
34%Best headshot accuracy · 13–7 · nuke, 6 Sept →
453msFastest reaction time · 3–13 · office, 23 Oct →
13–0Biggest win · train, 20 Aug →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W2Current streak
4–10In matches decided by ≤2 rounds
6Overtime games

Map breakdown

infernoBest map · 64% over 14ancientWeakest map · 0% over 8
MapGradePlayedRecordWin rateAvg rating
nukeB2411–1346%-0.01
dust2D234–1917%-0.01
infernoA149–564%-0.03
mirageD144–1029%-0.01
cacheB84–450%0.01
ancientD80–80%-0.07
anubisA53–260%-0.03
overpass—10–10%0.01
office—10–10%-0.07
train—11–0100%-0.04
vertigo—10–10%0.04

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (0% over 8). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

29,575Lifetime kills
0.87K/D
1,977Matches
39.3%Match win rate
35.4%Headshot %
6.6%Shot accuracy
3,265MVPs
783Hours (in match)
2,337Bombs planted
517Bombs defused

Most-used weapons

AK-475,099
MP91,914
MAC-101,862
SG 5531,583
AWP1,191
AUG1,058

Lifetime map wins

5,215dust2
2,741inferno
2,430nuke
515train
249vertigo
127office
24lake
19safehouse

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.

14.5%Headshot accuracy
34.6%Accuracy (enemy spotted)
36.0%Spray accuracy
67.7%Counter-strafing
15.1°Preaim
695msReaction time
43.6%T opening success
42.3%CT opening success
0.63Enemies flashed / flash
7.0%Flash assists
13.23HE damage / grenade
5.90Flashes / 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. Advanced Mechanics

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 15.1196° — above the 12° mark we flag

    Aim Training →
  2. 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 14.4705% — below the 15% mark we flag

    Aim Training →
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.

0% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache13–100.037%30 Oct →
inferno13–3-0.036%30 Oct →
nuke3–13-0.094%29 Oct →
nuke13–8-0.0512%29 Oct →
inferno4–13-0.0416%29 Oct →
mirage6–13-0.0316%25 Oct →
dust22–13-0.0612%25 Oct →
nuke13–8-0.0313%25 Oct →
cache3–2-0.0322%25 Oct →
nuke13–20.0012%24 Oct →
inferno13–70.0219%24 Oct →
overpass8–130.0116%23 Oct →
anubis13–5-0.023%23 Oct →
nuke9–130.0713%23 Oct →
mirage4–13-0.0411%23 Oct →
office3–13-0.0711%23 Oct →
dust26–13-0.0417%18 Oct →
dust27–130.0513%18 Oct →
dust28–130.0413%18 Oct →
dust210–13-0.0117%16 Oct →
nuke11–13-0.0119%16 Oct →
nuke13–10-0.0219%16 Oct →
mirage8–13-0.0224%16 Oct →
nuke7–1-0.007%16 Oct →
dust213–50.0722%20 Sept →
mirage9–130.0519%20 Sept →
nuke11–130.0320%20 Sept →
dust213–8-0.0515%20 Sept →
inferno13–60.0217%20 Sept →
mirage11–13-0.0713%20 Sept →
anubis6–13-0.0110%20 Sept →
dust26–13-0.0215%20 Sept →
nuke6–13-0.026%13 Sept →
ancient10–13-0.0210%13 Sept →
mirage11–130.019%13 Sept →
ancient9–13-0.0511%13 Sept →
mirage13–70.1016%13 Sept →
nuke16–130.0510%12 Sept →
mirage16–12-0.0113%12 Sept →
ancient3–13-0.045%12 Sept →
dust211–13-0.0417%12 Sept →
cache13–90.1014%11 Sept →
nuke13–60.0313%11 Sept →
inferno5–13-0.048%11 Sept →
inferno13–50.0315%6 Sept →
cache13–110.0315%6 Sept →
nuke13–70.0234%6 Sept →
inferno13–50.0418%6 Sept →
dust211–130.0311%6 Sept →
nuke10–13-0.028%6 Sept →
inferno13–8-0.037%4 Sept →
mirage12–16-0.0717%4 Sept →
dust213–60.0718%4 Sept →
dust29–13-0.0115%4 Sept →
cache7–130.0417%3 Sept →
ancient11–13-0.075%3 Sept →
mirage6–13-0.0219%3 Sept →
nuke9–13-0.0317%3 Sept →
dust211–13-0.019%30 Aug →
mirage13–11-0.0510%30 Aug →
dust29–130.0216%30 Aug →
nuke4–130.0117%30 Aug →
mirage13–90.0811%30 Aug →
nuke6–130.038%30 Aug →
cache5–13-0.007%30 Aug →
mirage2–13-0.0618%30 Aug →
ancient7–13-0.0610%30 Aug →
dust25–13-0.0611%30 Aug →
cache8–13-0.099%30 Aug →
dust213–7-0.0214%29 Aug →
anubis13–7-0.075%29 Aug →
inferno3–13-0.084%29 Aug →
nuke9–13-0.0511%29 Aug →
nuke14–16-0.0012%29 Aug →
ancient8–13-0.0911%28 Aug →
dust24–13-0.0219%28 Aug →
anubis16–13-0.0218%28 Aug →
nuke5–130.0018%28 Aug →
nuke13–11-0.0222%28 Aug →
nuke13–8-0.0416%28 Aug →
inferno13–7-0.0411%28 Aug →
ancient4–13-0.1225%28 Aug →
dust24–13-0.0518%28 Aug →
cache5–13-0.0312%28 Aug →
dust211–130.0116%28 Aug →
dust25–13-0.0414%28 Aug →
inferno7–13-0.068%24 Aug →
anubis8–13-0.0112%24 Aug →
nuke3–9-0.103%24 Aug →
dust210–13-0.0713%24 Aug →
nuke16–12-0.0116%23 Aug →
ancient4–13-0.099%23 Aug →
train13–0-0.0412%20 Aug →
mirage5–13-0.0114%20 Aug →
vertigo10–130.0411%20 Aug →
dust26–13-0.0124%20 Aug →
inferno6–13-0.064%20 Aug →
dust23–13-0.035%20 Aug →
inferno13–6-0.056%19 Aug →
inferno13–4-0.0419%19 Aug →

Match data via Leetify.

Recent teammates

Milestones

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

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