Mega Chinese

Mega Chinese — CS2 Stats

GB76561198066624185[U:1:106358457]Steam profile ↗✓ No bans

2,220Tracked matches57%Win rate2021Tracked since
3,703Hours in CS64Hrs last 2 wks
CSDB Rating6.5 SolidAll-Rounder
Premier CS Rating23,236Top 25% of 204,412 CSDB-tracked playersPink band · top ~4.9% of ranked players (population est.)
CSDB Leaderboard#39371 of 251770 tracked
FaceitLevel 8 · 1,659 ELOTop 31.2% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 10 Oct 2026 (4 days ago). Ranks are recorded once per day this page is viewed.

0Premier CS Rating · 23,236 → 23,236
0Faceit ELO · 1,659 → 1,659
+30Tracked matches · now 2,220
−2.0ppWin rate · 58.6% → 56.7%

Rating over time

Premier CS Rating: 23,236 +2,591 26 Aug – 10 Oct · 24 days played
20,64525,282peak 25,28226 Aug10 Oct
Faceit ELO: 1,659 +0 18 Sept – 10 Oct · 3 observations
1,6591,659peak 1,65918 Sept10 Oct
25,655Peak Premier in tracked matches
1,659Highest Faceit ELO seen on CSDB
35Days played since 2026-08-26

Faceit ELO

  • At peak — 1,659
  • Next: Level 9 at 1,751 — 92 to go
  • Reached: Level 8 · Level 7 · Level 6 · Level 5
  • Level 8 first seen 2026-09-18
  • Level 7 first seen 2026-09-18

Premier CS Rating

  • 2,046 below peak (25,282)
  • -1,245 over 30 days · declining
  • Next: Red band at 25,000 — 1,764 to go
  • Reached: Red band · Pink band · Purple band · Blue band
  • Pink band first seen 2026-09-18
  • Purple band first seen 2026-09-18

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches75——
Win rate51%——
K/D1.93——
Headshot %72%——

Measured 18 Sep 2026 → 14 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 Level 8 among CSDB-tracked players (n=15,030), 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 playerLevel 8 medianLevel 9 medianvs Level 9
Headshot rate68.5%46.8%48.2%above
Shot accuracy5.3%13.0%13.3%8.0% short
Kill/death ratio1.951.061.07above
Match win rate45.3%46.3%46.9%1.6% short

This profile matches the typical Level 9 player on 2 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 9 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGMega ChineseFACEITLevel 8 · 1,659 ELOSTANDINGTop 31.2% of rankedPREMIER23,236 · Pink bandPEAK ELO1,659csdb.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

Aim76
Positioning51
Utility47

0–100 skill scores via Leetify.

Recent form

STEADY59–40–1Last 10059%Win rateWWLLLWLLLW

Last 10 vs previous 10: −10pp win rate · +0.01 avg rating · −1.1pp headshot accuracy · +20ms reaction

Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 2–3 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 20%
  • Avg reaction 594ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 20%
  • Avg reaction 587ms

Last 20

  • 9–11 · 45% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 20%
  • Avg reaction 577ms

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: All-Rounder — No style dimension stands clear of the others in this profile.

Aim7.6
Utility4.7
Positioning5.1
Opening Duels4.6
Clutch3.8

Strong CT-side opener

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

m0NESY

Plays most like m0NESY 98% playstyle similarity

Most alike: utility contribution, aim profile.

Where you differ: lower positioning 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

CT openings. 61% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 61% on CT to 40% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 570ms 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

Aim7.6
Positioning5.1
Utility4.7
Mechanics7.3
Opening Duels5.2
Win Impact7.2

Composite 6.5/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01−0.00
first ⅓ avg 0.01 → last ⅓ avg 0.01
Reaction time570ms+20ms
first ⅓ avg 550ms → last ⅓ avg 570ms
Headshot accuracy21.5%−4.1%
first ⅓ avg 25.5% → last ⅓ avg 21.5%

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

0.12Best match rating · 13–4 · cache, 10 Oct →
45%Best headshot accuracy · 12–4 · mirage, 1 Sept →
430msFastest reaction time · 13–8 · ancient, 30 Aug →
13–2Biggest win · ancient, 7 Sept →

Across the last 100 tracked matches.

Highlights

8Longest win streak
W2Current streak
10–8In matches decided by ≤2 rounds
15Overtime games

Map breakdown

cacheBest map · 83% over 6dust2Weakest map · 46% over 13
MapGradePlayedRecordWin rateAvg rating
mirageA2213–959%0.00
infernoA2012–860%0.01
anubisB158–753%-0.00
nukeB147–750%0.01
dust2B136–746%0.00
ancientS108–280%0.04
cacheS65–183%0.05

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (46% over 13). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

181,256Lifetime kills
1.95K/D · Top 5% of Level 8 players
4,244Matches
45.3%Match win rate
68.5%Headshot % · Top 5% of Level 8 players
5.3%Shot accuracy
9,504MVPs
1,721Hours (in match)
4,078Bombs planted
1,600Bombs defused

Most-used weapons

AK-47111,279
AWP6,100
FAMAS3,968
SG 5532,136
MP91,619

Lifetime map wins

8,082inferno
3,484nuke
3,167dust2
1,115vertigo
1,057train
148cbble
83office
17ar_shoots

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

Faceit stats

Combat

110Matches
58%Win rate
1.14Avg K/D
85.1ADR
56%Headshot %

Clutches & streaks

39%1v1 clutch win
26%1v2 clutch win
11Longest win streak

Recent Faceit resultsWWWWW

MapMatchesWin rateAvg K/DAvg kills
Mirage2959%1.0816.2
Inferno1968%1.1518.6
Dust21573%1.2119.8
Nuke1450%1.2819.8
Anubis1443%1.0116.9
Ancient1040%0.9916.3
Train333%0.9815.0
Overpass367%1.7321.3

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.

21.7%Headshot accuracy
35.5%Accuracy (enemy spotted)
36.3%Spray accuracy
82.7%Counter-strafing
10.3°Preaim
570msReaction time
40.5%T opening success
61.0%CT opening success
0.38Enemies flashed / flash
4.3%Flash assists
7.12HE damage / grenade
7.30Flashes / 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 0.3806 — below the 0.5 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.

46% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno16–140.0615%14 Oct →
inferno16–130.0530%13 Oct →
nuke23–250.0721%12 Oct →
ancient8–13-0.0515%11 Oct →
anubis12–16-0.0218%11 Oct →
cache13–40.1217%10 Oct →
anubis10–13-0.0926%10 Oct →
anubis11–13-0.039%10 Oct →
dust29–13-0.0430%10 Oct →
nuke13–6-0.0116%6 Oct →
inferno16–12-0.0226%3 Oct →
nuke10–130.0118%3 Oct →
dust211–13-0.0028%2 Oct →
mirage8–130.0111%2 Oct →
mirage5–13-0.0319%30 Sept →
dust27–13-0.0122%29 Sept →
ancient13–90.0323%29 Sept →
dust213–7-0.0224%29 Sept →
mirage13–100.0320%28 Sept →
mirage16–140.0217%26 Sept →
ancient11–130.0319%26 Sept →
dust213–30.0625%26 Sept →
mirage8–13-0.0710%24 Sept →
inferno13–40.0226%24 Sept →
mirage13–30.0835%24 Sept →
mirage13–10-0.0122%24 Sept →
ancient13–60.0322%24 Sept →
cache16–130.1029%22 Sept →
ancient16–130.0331%22 Sept →
dust213–70.1129%22 Sept →
nuke13–60.0522%22 Sept →
inferno15–15-0.0417%21 Sept →
nuke8–13-0.0219%21 Sept →
cache10–13-0.0425%21 Sept →
anubis11–130.0128%21 Sept →
mirage13–50.0126%21 Sept →
mirage4–13-0.1023%19 Sept →
dust213–9-0.0430%19 Sept →
anubis0–80.0311%19 Sept →
inferno13–11-0.0323%18 Sept →
inferno13–10-0.0322%18 Sept →
nuke13–50.0925%17 Sept →
anubis13–60.0121%17 Sept →
mirage13–60.0221%17 Sept →
inferno8–13-0.0029%17 Sept →
anubis13–7-0.0114%17 Sept →
mirage8–130.0235%16 Sept →
dust22–13-0.0138%16 Sept →
cache13–110.0943%15 Sept →
anubis13–60.0315%15 Sept →
inferno16–140.0324%15 Sept →
mirage11–13-0.0126%15 Sept →
inferno14–16-0.0226%14 Sept →
mirage13–8-0.0230%14 Sept →
dust25–130.0529%14 Sept →
mirage13–9-0.0125%14 Sept →
nuke7–130.0124%12 Sept →
inferno16–12-0.0319%12 Sept →
nuke13–60.019%9 Sept →
nuke6–13-0.0517%9 Sept →
dust23–13-0.0424%9 Sept →
anubis13–110.0216%7 Sept →
ancient13–20.1132%7 Sept →
mirage13–110.0122%7 Sept →
dust213–80.0040%6 Sept →
ancient13–70.0725%6 Sept →
inferno13–30.0617%6 Sept →
mirage10–130.0823%5 Sept →
ancient13–90.0422%5 Sept →
anubis13–90.0726%5 Sept →
anubis13–8-0.0616%4 Sept →
inferno11–13-0.0119%4 Sept →
dust213–90.0221%4 Sept →
dust24–13-0.0121%4 Sept →
anubis5–130.0233%4 Sept →
anubis13–90.0218%3 Sept →
cache13–110.0022%3 Sept →
nuke6–13-0.0817%2 Sept →
inferno7–13-0.0328%2 Sept →
mirage12–40.0245%1 Sept →
mirage13–90.0119%1 Sept →
mirage13–160.0137%1 Sept →
mirage8–130.0016%31 Aug →
mirage16–140.0233%31 Aug →
mirage13–20.0119%30 Aug →
ancient13–80.0727%30 Aug →
anubis13–60.0130%30 Aug →
inferno13–110.0834%30 Aug →
cache13–80.0536%28 Aug →
inferno1–13-0.0135%28 Aug →
inferno13–90.1029%28 Aug →
anubis10–13-0.0119%28 Aug →
inferno13–100.0115%27 Aug →
nuke13–90.1024%27 Aug →
ancient13–70.0124%27 Aug →
nuke13–8-0.0028%27 Aug →
inferno8–13-0.0429%27 Aug →
nuke13–70.0417%27 Aug →
inferno9–13-0.0029%26 Aug →
nuke13–16-0.0335%26 Aug →

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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