MrMeow

MrMeow — CS2 Stats

76561198851258574[U:1:890992846]Steam profile ↗✓ No bans

159Tracked matches48%Win rate2024Tracked since
318Hours in CS24Hrs last 2 wks
CSDB Rating2.3 Learning
Premier CS Rating1,429Grey band · top ~93.9% of ranked players (population est.)
CSDB Leaderboard#40338 of 51452 tracked
Ladder ranks via Leetify

How this compares with the same rank

Median values for Grey band among CSDB-tracked players (n=369), 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 playerGrey band medianLight Blue band medianvs Light Blue band
Headshot rate37.7%37.5%39.7%2.0% short
Shot accuracy8.3%4.5%6.7%above
Kill/death ratio0.790.820.910.12 short
Match win rate31.0%39.1%42.1%11.1% short

This profile matches the typical Light Blue band player on 1 of 4 comparable metrics.

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

Share this profile

CSDB.GGMrMeowPREMIER1,429 · Grey bandcsdb.gg/stats

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Performance scores

Aim17
Positioning32
Utility20

0–100 skill scores via Leetify.

Recent form

HOT45514Last 10045%Win rateLWWWWLWLWW

Last 10 vs previous 10: +50pp win rate · +0.00 avg rating

Player DNA

Aim1.7
Aggression1.1
Utility2.0
Positioning3.2
Opening Duels0.0
Clutch0.0

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

NiKo

Plays most like NiKo 55% 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

Reaction time. 771ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% 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

Aim1.7
Positioning3.2
Utility2.0
Mechanics4.1
Opening Duels0.0
Win Impact4.4

Composite 2.3/10 (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-0.03+0.02
first ⅓ avg -0.05 → last ⅓ avg -0.03
Reaction time778ms+13ms
first ⅓ avg 765ms → last ⅓ avg 778ms
Headshot accuracy14.9%+2.7%
first ⅓ avg 12.2% → last ⅓ avg 14.9%

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.

Highlights

0.08Best rating — dust2 7–13
130Biggest win — ancient
4Longest win streak
75In matches decided by ≤2 rounds
4Overtime games

Map breakdown

ancientBest map · 67% over 9infernoWeakest map · 13% over 8
MapGradePlayedRecordWin rateAvg rating
dust2B29131645%-0.04
mirageC2081240%-0.02
nukeC135838%-0.03
ancientS96367%-0.03
cacheS96367%-0.03
infernoD81713%-0.08
anubisC73443%-0.03
vertigo31233%-0.10
train220100%-0.06

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (13% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

8,435Lifetime kills
0.79K/D
733Matches
31.0%Match win rate
37.7%Headshot % · Top 50% of Grey band
8.3%Shot accuracy · Top 50% of Grey band
650MVPs
196Hours (in match)
369Bombs planted
89Bombs defused

Most-used weapons

Lifetime map wins

1,118dust2
315nuke
296inferno
200vertigo
106office
73train
26sugarcane
23cbble

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

Faceit stats

Combat

3Matches
67%Win rate
0.17Avg K/D
1.6ADR
33%Headshot %

Clutches & streaks

0%1v1 clutch win
0%1v2 clutch win
2Longest win streak

Recent Faceit resultsLLWWL

MapMatchesWin rateAvg K/DAvg kills
Nuke1100%0.000.0
Dust210%0.000.0
Cache1100%0.501.0

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.

14.4%Headshot accuracy
27.4%Accuracy (enemy spotted)
26.0%Spray accuracy
68.5%Counter-strafing
11.4°Preaim
771msReaction time
16.9%T opening success
23.4%CT opening success
0.37Enemies flashed / flash
0.0%Flash assists
7.54HE damage / grenade
1.14Flashes / 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 14.4305% — below the 15% mark we flag

    Aim Training
  2. Best CS2 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 770.9481ms — above the 700ms mark we flag

    Aim Training
  3. 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 0.3659 — below the 0.5 mark we flag

    Grenade Lineups
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.

13% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
nuke11–13-0.1217%29 Aug
ancient13–11-0.0014%29 Aug
cache13–9-0.0316%29 Aug
dust211–4-0.0821%29 Aug
dust213–20.0211%28 Aug
nuke8–130.0316%28 Aug
nuke13–9-0.045%28 Aug
inferno7–13-0.0821%27 Aug
ancient13–00.0419%27 Aug
dust213–3-0.0221%27 Aug
dust25–10-0.0530%26 Aug
anubis9–13-0.0118%26 Aug
mirage2–13-0.109%26 Aug
cache8–13-0.0415%26 Aug
cache6–13-0.0518%26 Aug
cache7–0-0.0420%26 Aug
mirage11–130.027%25 Aug
cache8–13-0.0515%25 Aug
nuke13–11-0.056%25 Aug
dust27–130.0821%24 Aug
mirage0–11-0.0611%22 Aug
mirage13–4-0.0413%22 Aug
mirage15–15-0.0212%22 Aug
nuke7–13-0.0211%22 Aug
ancient13–11-0.0911%21 Aug
mirage13–6-0.0013%21 Aug
ancient13–6-0.0228%21 Aug
nuke9–3-0.0710%20 Aug
mirage14–16-0.027%20 Aug
dust24–13-0.0811%20 Aug
dust213–40.013%20 Aug
mirage7–130.0719%18 Aug
dust26–130.0123%18 Aug
mirage13–11-0.0619%18 Aug
inferno16–13-0.0212%18 Aug
ancient13–6-0.0315%17 Aug
inferno3–13-0.0420%17 Aug
anubis12–160.0212%16 Aug
mirage6–130.0110%16 Aug
mirage9–13-0.0416%15 Aug
dust27–2-0.060%15 Aug
nuke8–13-0.0710%15 Aug
dust21–13-0.056%15 Aug
cache13–7-0.0221%15 Aug
inferno1–7-0.1118%14 Aug
dust27–0-0.0138%14 Aug
ancient2–13-0.1022%14 Aug
dust213–8-0.0221%14 Aug
inferno7–13-0.0815%13 Aug
dust24–13-0.0718%13 Aug
dust26–13-0.0416%12 Aug
train13–9-0.0610%12 Aug
train13–7-0.0722%12 Aug
dust24–10-0.1013%11 Aug
nuke9–40.0417%11 Aug
dust213–5-0.0810%10 Aug
dust210–13-0.1210%8 Aug
dust24–13-0.1210%8 Aug
dust213–20.0421%8 Aug
mirage13–2-0.0514%7 Aug
nuke12–120.0719%7 Aug
mirage13–3-0.0119%6 Aug
mirage7–13-0.0714%6 Aug
ancient13–00.036%5 Aug
mirage9–13-0.0311%5 Aug
nuke5–6-0.039%4 Aug
inferno10–13-0.0517%4 Aug
dust211–13-0.0014%3 Aug
ancient6–13-0.0513%3 Aug
mirage11–13-0.038%2 Aug
mirage3–13-0.027%2 Aug
cache13–10.0711%2 Aug
cache13–8-0.079%2 Aug
nuke12–12-0.0612%2 Aug
anubis13–4-0.077%2 Aug
dust213–9-0.065%1 Aug
inferno8–13-0.135%1 Aug
ancient1–12-0.1027%30 Jul
dust20–13-0.0825%30 Jul
dust29–130.0220%29 Jul
anubis2–13-0.1120%29 Jul
vertigo13–11-0.1316%29 Jul
vertigo0–13-0.1110%29 Jul
vertigo12–12-0.077%29 Jul
dust26–13-0.1217%28 Jul
nuke10–130.0116%28 Jul
anubis13–70.004%27 Jul
dust213–7-0.0911%27 Jul
dust213–9-0.0411%26 Jul
mirage13–10.0316%25 Jul
dust21–50.0511%25 Jul
anubis6–13-0.0312%24 Jul
anubis13–50.0213%23 Jul
nuke10–13-0.1116%17 Jul
dust213–60.0211%14 Jul
mirage13–4-0.0513%14 Jul
mirage13–80.017%14 Jul
dust20–3-0.040%14 Jul
inferno2–13-0.1010%14 Jul
cache13–11-0.0719%14 Jul

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 →