MuNaKKa — CS2 Stats

76561198077158846[U:1:116893118]

2,241Tracked matches43%Win rate2023Tracked since
3,579Hours in CS40Hrs last 2 wks
CSDB Rating4.4 DevelopingHybrid Rifler
Premier CS Rating15,361Purple band · top ~27% of ranked players (population est.)
CSDB Leaderboard#13688 of 21867 tracked
Ladder ranks via Leetify

How this compares with the same rank

Median values for Pink band among CSDB-tracked players (n=201), 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 playerPink band medianvs Pink band
Headshot rate35.5%48.1%12.6% short
Shot accuracy9.2%12.9%3.6% short
Kill/death ratio1.021.080.07 short
Match win rate30.4%46.5%16.1% short

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

Widest gap: Match win rate. 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.

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CSDB.GGMuNaKKaPREMIER15,361 · Purple bandcsdb.gg/stats

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Performance scores

Aim60
Positioning56
Utility33

0–100 skill scores via Leetify.

Recent form

STEADY47503Last 10047%Win rateLWWLLLLWWL

Last 10 vs previous 10: +0pp win rate · -0.03 avg rating

Player DNA

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

Aim6.0
Aggression8.4
Utility3.3
Positioning5.6
Opening Duels2.9
Clutch3.0

Strong CT-side openerLimited utility dependence

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 83% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: lower utility contribution; 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

T-side openings. Opening success drops from 51% on CT to 32% on T — the same duels are being taken with worse setups on the attacking side.

Counter-strafing. Only 63% 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

Aim6.0
Positioning5.6
Utility3.3
Mechanics2.8
Opening Duels2.9
Win Impact2.8

Composite 4.4/10 (Developing), 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 rating-0.01−0.01
first ⅓ avg 0.00 → last ⅓ avg -0.01
Reaction time531ms−32ms
first ⅓ avg 563ms → last ⅓ avg 531ms
Headshot accuracy18.8%−1.2%
first ⅓ avg 20.0% → last ⅓ avg 18.8%

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

0.18Best rating — nuke 13–5
132Biggest win — inferno
5Longest win streak
1114In matches decided by ≤2 rounds
15Overtime games

Map breakdown

cacheBest map · 64% over 11infernoWeakest map · 33% over 18
MapGradePlayedRecordWin rateAvg rating
nukeB24121250%0.00
infernoD1861233%-0.01
mirageC145936%-0.01
ancientA138562%0.01
cacheA117464%0.02
dust2B115645%-0.02
anubisC94544%-0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 18). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

96,231Lifetime kills
1.02K/D
6,263Matches
30.4%Match win rate
35.5%Headshot %
9.2%Shot accuracy
6,388MVPs
1,867Hours (in match)
4,988Bombs planted
793Bombs defused

Most-used weapons

AK-4715,139
AWP7,560
FAMAS3,820
P903,809
MP72,822
AUG2,330

Lifetime map wins

9,087nuke
5,716inferno
5,551dust2
1,113train
467vertigo
465cbble
325ar_shoots
267office

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

Faceit stats

Combat

196Matches
51%Win rate
0.96Avg K/D
79.1ADR
39%Headshot %

Clutches & streaks

35%1v1 clutch win
14%1v2 clutch win
9Longest win streak

Recent Faceit resultsLWWLW

MapMatchesWin rateAvg K/DAvg kills
Ancient2454%1.1516.0
Inferno2467%1.1315.7
Nuke2060%1.1213.3
Mirage1547%1.4312.5
Overpass771%1.2514.3
Anubis633%0.8211.5
Dust2633%0.7311.2
Vertigo20%0.7011.5

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.

18.0%Headshot accuracy
32.8%Accuracy (enemy spotted)
32.0%Spray accuracy
62.6%Counter-strafing
8.4°Preaim
527msReaction time
32.4%T opening success
50.5%CT opening success
0.24Enemies flashed / flash
8.8%Flash assists
8.68HE damage / grenade
4.13Flashes / 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 0.2358 — 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 32.3553% — below the 40% mark we flag

Spend your practice time on Inferno

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

33% win rate across 18 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
inferno5–13-0.044%28 Aug
ancient16–130.0517%28 Aug
inferno13–10-0.019%28 Aug
mirage0–13-0.1022%28 Aug
cache10–130.0112%27 Aug
mirage3–13-0.0520%27 Aug
mirage5–130.0114%27 Aug
inferno16–14-0.0220%26 Aug
nuke13–60.0110%26 Aug
mirage8–13-0.0117%26 Aug
nuke11–13-0.0413%26 Aug
nuke13–50.1813%25 Aug
nuke11–13-0.068%25 Aug
cache13–100.0322%25 Aug
mirage13–80.0526%25 Aug
cache13–50.0719%24 Aug
inferno8–130.0010%24 Aug
anubis11–13-0.0310%24 Aug
ancient7–13-0.0510%24 Aug
dust23–13-0.0326%24 Aug
nuke13–60.0129%22 Aug
anubis13–60.0247%22 Aug
ancient13–16-0.0328%22 Aug
dust213–9-0.0826%22 Aug
anubis13–80.0019%22 Aug
nuke13–90.0317%21 Aug
dust25–13-0.0710%21 Aug
inferno11–130.1028%21 Aug
ancient9–130.0318%21 Aug
nuke11–13-0.0218%21 Aug
ancient13–5-0.039%21 Aug
ancient13–80.0120%21 Aug
inferno2–9-0.2050%21 Aug
nuke13–8-0.0112%21 Aug
nuke11–13-0.0115%20 Aug
ancient13–50.0229%20 Aug
nuke6–13-0.086%20 Aug
anubis3–13-0.1111%20 Aug
nuke13–110.0419%20 Aug
ancient16–140.0615%19 Aug
mirage13–8-0.0419%19 Aug
nuke15–150.0118%19 Aug
cache13–30.0815%18 Aug
dust213–5-0.0113%18 Aug
mirage9–13-0.0312%18 Aug
mirage7–130.087%13 Aug
nuke13–11-0.0225%13 Aug
anubis9–130.0224%13 Aug
inferno10–13-0.0424%13 Aug
inferno3–9-0.0920%13 Aug
anubis13–110.0319%12 Aug
cache13–11-0.0515%12 Aug
mirage13–5-0.0419%12 Aug
nuke11–130.0111%12 Aug
dust215–150.0126%12 Aug
mirage11–130.0326%12 Aug
inferno13–30.0321%12 Aug
dust213–10-0.0228%11 Aug
cache6–130.035%11 Aug
nuke13–9-0.0121%11 Aug
nuke7–13-0.0311%11 Aug
ancient13–16-0.0426%11 Aug
inferno13–80.0215%11 Aug
ancient16–140.0222%4 Aug
mirage5–13-0.0313%4 Aug
cache11–130.0513%4 Aug
dust20–7-0.0222%4 Aug
cache6–13-0.0218%3 Aug
anubis13–40.1017%3 Aug
nuke13–70.0716%3 Aug
nuke13–70.1718%3 Aug
dust28–13-0.0541%3 Aug
dust216–140.0322%31 Jul
nuke14–16-0.0712%31 Jul
nuke7–13-0.0212%31 Jul
nuke5–13-0.0118%31 Jul
inferno13–8-0.0413%31 Jul
anubis10–13-0.0014%31 Jul
mirage13–50.0115%31 Jul
nuke13–11-0.0714%30 Jul
inferno7–130.0119%30 Jul
inferno7–130.0316%30 Jul
inferno12–160.0131%29 Jul
ancient10–130.0318%29 Jul
cache13–8-0.0725%29 Jul
anubis14–16-0.0539%28 Jul
nuke8–130.0124%27 Jul
dust213–70.0114%27 Jul
mirage11–13-0.0319%26 Jul
inferno11–13-0.0026%26 Jul
dust27–130.0333%26 Jul
inferno13–20.0028%26 Jul
nuke13–2-0.077%26 Jul
inferno14–160.0023%26 Jul
inferno15–150.0218%25 Jul
mirage16–140.0419%25 Jul
ancient13–9-0.0222%25 Jul
ancient13–110.0513%25 Jul
cache13–50.0620%25 Jul
cache13–40.0019%25 Jul

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 →