Miku was supposed to win

Miku was supposed to win — CS2 Stats

JP76561199378948957[U:1:1418683229]Steam profile ↗✓ No bans

2,099Tracked matches27%Win rate2024Tracked since
1,856Hours in CS
CSDB Rating4.5 DevelopingPassive Rifler
FaceitLevel 7 · 1,764 ELOTop 42.3% of ranked FACEIT players
WingmanGold Nova Master
Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 7 among CSDB-tracked players (n=2,670), 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 7 medianLevel 8 medianvs Level 8
Headshot rate54.7%46.0%47.0%above
Shot accuracy0.7%12.6%12.8%12.1% short
Kill/death ratio0.941.061.070.14 short
Match win rate45.0%45.8%46.4%1.4% short

This profile matches the typical Level 8 player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 8 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGMiku was supposed to winFACEITLevel 7 · 1,764 ELOSTANDINGTop 42.3% of rankedcsdb.gg/stats

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Performance scores

Aim64
Positioning44
Utility55

0–100 skill scores via Leetify.

Recent form

COLD4258Last 10042%Win rateLWLLLLLLLL

Last 10 vs previous 10: +0pp win rate · +0.02 avg rating

Player DNA

Primary style: Passive RiflerAim-led profile without a single dominant tendency.

Aim6.4
Aggression4.0
Utility5.5
Positioning4.4
Opening Duels0.7
Clutch3.6

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

b1t

Plays most like b1t 82% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-fight frequency; 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. 635ms 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

Aim6.4
Positioning4.4
Utility5.5
Mechanics6.6
Opening Duels0.9
Win Impact0.0

Composite 4.5/10 (Developing), 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 rating-0.01−0.02
first ⅓ avg 0.00 → last ⅓ avg -0.01
Reaction time646ms−42ms
first ⅓ avg 687ms → last ⅓ avg 646ms
Headshot accuracy25.6%−5.0%
first ⅓ avg 30.6% → last ⅓ avg 25.6%

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.

Highlights

0.13Best rating — dust2 13–2
131Biggest win — train
4Longest win streak
98In matches decided by ≤2 rounds
10Overtime games

Map breakdown

trainBest map · 67% over 6nukeWeakest map · 22% over 23
MapGradePlayedRecordWin rateAvg rating
nukeD2351822%-0.02
ancientB1910953%0.00
mirageB189950%-0.00
dust2B126650%-0.00
anubisD93633%-0.03
trainS64267%0.03
infernoD62433%-0.02
cache43175%-0.01
overpass3030%-0.01

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (22% over 23). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

76,950Lifetime kills
0.94K/D
4,063Matches
45.0%Match win rate
54.7%Headshot % · Top 25% of Level 7 players
0.7%Shot accuracy
10,071MVPs
1,856Hours (in match)
3,490Bombs planted
890Bombs defused

Most-used weapons

AK-4731,747
AWP4,408
Knife2,166
MP92,072
MAC-101,799

Lifetime map wins

5,432nuke
4,659dust2
2,449inferno
2,320vertigo
1,338train
242office
40lake
22cbble

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

Faceit stats

Combat

2,378Matches
49%Win rate
1.02Avg K/D
80.2ADR
55%Headshot %

Clutches & streaks

38%1v1 clutch win
20%1v2 clutch win
12Longest win streak

Recent Faceit resultsWWLLL

MapMatchesWin rateAvg K/DAvg kills
Mirage62749%1.0116.0
Ancient46453%1.0316.3
Nuke33252%1.0616.3
Dust233046%1.0216.0
Anubis28248%1.0015.7
Inferno10547%1.1216.3
Train9647%0.9816.5
Overpass6635%0.9214.6

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.

24.1%Headshot accuracy
31.4%Accuracy (enemy spotted)
34.4%Spray accuracy
79.7%Counter-strafing
10.5°Preaim
635msReaction time
28.7%T opening success
37.1%CT opening success
0.43Enemies flashed / flash
4.9%Flash assists
7.44HE damage / grenade
14.41Flashes / 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 0.4274 — below the 0.5 mark we flag

    Grenade Lineups
  2. 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 28.6898% — below the 40% mark we flag

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.

22% win rate across 23 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategyNuke grenade lineups

Recent matches

MapScoreRatingHS%Date
anubis9–13-0.0428%19 Aug
ancient13–11-0.0320%18 Aug
mirage2–130.0132%18 Aug
dust217–190.0228%17 Aug
dust28–13-0.0421%16 Aug
train1–130.1060%9 Aug
dust20–13-0.0250%9 Aug
ancient11–13-0.0222%3 Aug
nuke8–13-0.0414%31 Jul
nuke13–16-0.0418%31 Jul
mirage9–13-0.0216%30 Jul
anubis7–13-0.0437%28 Jul
anubis11–13-0.0021%26 Jul
dust213–110.0223%26 Jul
nuke7–13-0.0719%26 Jul
nuke8–13-0.0218%25 Jul
cache11–13-0.0524%25 Jul
ancient11–13-0.0430%24 Jul
nuke11–13-0.0320%19 Jul
nuke10–13-0.0744%17 Jul
cache13–70.0129%16 Jul
cache13–110.0118%16 Jul
anubis10–13-0.0320%16 Jul
ancient8–130.0125%15 Jul
nuke8–130.0925%14 Jul
cache13–8-0.0319%13 Jul
ancient13–11-0.0223%12 Jul
anubis13–8-0.0326%9 Jul
mirage13–9-0.0126%25 Jun
inferno10–13-0.0615%19 Jun
nuke13–60.0331%29 May
ancient9–130.0219%23 May
ancient13–110.0225%26 Apr
dust26–13-0.0219%24 Apr
ancient11–13-0.0134%21 Apr
overpass8–13-0.0525%20 Apr
nuke10–13-0.0713%12 Apr
nuke2–13-0.0553%28 Mar
ancient13–9-0.0119%25 Mar
anubis13–3-0.0632%16 Mar
mirage13–70.0028%13 Mar
inferno4–13-0.0434%1 Mar
nuke7–13-0.0022%28 Feb
dust213–4-0.0435%24 Feb
nuke8–13-0.0223%22 Feb
ancient13–80.0133%21 Feb
mirage9–130.0314%21 Feb
nuke13–60.0836%20 Feb
anubis7–13-0.0615%20 Feb
nuke13–50.0125%18 Feb
anubis10–130.0620%17 Feb
inferno8–13-0.0221%9 Feb
mirage4–13-0.069%7 Feb
mirage7–13-0.0317%6 Feb
mirage13–80.0319%2 Feb
anubis13–10-0.0512%29 Jan
mirage4–13-0.0214%24 Jan
overpass11–130.0423%16 Jan
mirage8–130.0114%10 Jan
dust27–13-0.0428%31 Dec
mirage4–13-0.0526%31 Dec
ancient13–110.0527%30 Dec
ancient8–13-0.0615%21 Dec
ancient19–170.0427%14 Dec
train9–13-0.0320%7 Dec
mirage16–13-0.0328%5 Dec
mirage13–30.0924%4 Dec
train13–5-0.0127%29 Nov
ancient13–100.0315%26 Nov
nuke4–130.0048%21 Nov
train13–60.0133%19 Nov
nuke13–16-0.0518%19 Nov
nuke13–11-0.0326%18 Nov
overpass8–13-0.0429%16 Nov
nuke10–130.0627%10 Nov
dust213–10-0.0431%10 Nov
ancient4–13-0.0337%3 Nov
train13–1-0.0042%31 Oct
nuke6–13-0.0717%29 Oct
mirage16–130.0026%23 Oct
nuke8–13-0.0120%19 Oct
dust29–13-0.0337%19 Oct
ancient8–13-0.0220%19 Oct
mirage13–70.0124%19 Oct
dust213–10-0.0238%18 Oct
dust213–60.0424%17 Oct
inferno7–130.0347%14 Oct
inferno16–13-0.0227%11 Oct
mirage13–5-0.0429%11 Oct
dust213–20.1347%11 Oct
mirage6–130.0046%7 Oct
nuke16–13-0.0232%6 Oct
mirage13–50.0430%5 Oct
train10–50.1130%5 Oct
nuke1–13-0.0533%4 Oct
ancient16–140.0038%4 Oct
nuke13–16-0.0025%2 Oct
ancient13–80.0732%30 Sept
inferno13–8-0.0024%29 Sept
ancient4–130.0130%27 Sept

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 →