MMS

MMS — CS2 Stats

76561199575169874[U:1:1614904146]Steam profile ↗✓ No bans

102Tracked matches40%Win rate2024Tracked since
CSDB Rating3.2 LearningPositional Player
Premier CS Rating5,107Light Blue band · top ~78.3% of ranked players (population est.)
FaceitLevel 2Top 97.9% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 13 Nov 2026 (yesterday). Ranks are recorded once per day this page is viewed.

No change since then — still 102 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 5,107 +739 7 Feb – 13 Nov · 20 days played
3,8785,717peak 5,7177 Feb13 Nov
6,061Peak Premier in tracked matches
39Days played since 2024-10-25

Premier CS Rating

  • 610 below peak (5,717)
  • Next: Blue band at 10,000 — 4,893 to go
  • Reached: Light Blue band
  • Light Blue band first seen 2026-11-13

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Share this profile

CSDB.GGMMSFACEITLevel 2STANDINGTop 97.9% of rankedPREMIER5,107 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim36
Positioning34
Utility25

0–100 skill scores via Leetify.

Recent form

STEADY38–60–1Last 9938%Win rateWLLWWLWLWW

Last 10 vs previous 10: +10pp win rate · +0.04 avg rating · +3.8pp headshot accuracy · −5ms 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

  • 3–2 · 60% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 14%
  • Avg reaction 691ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 14%
  • Avg reaction 778ms

Last 20

  • 11–9 · 55% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 12%
  • Avg reaction 780ms

Newest first, from the last 99 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Positional Player — Positioning stands above the rest of this profile (+1.2 against its own average).

Aim3.6
Utility2.5
Positioning3.4
Opening Duels0.9
Clutch2.0

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.

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

ZywOo

Plays most like ZywOo 82% playstyle similarity

Most alike: positioning profile, utility contribution.

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

T-side openings. Opening success drops from 43% on CT to 21% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 776ms 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

Aim3.6
Positioning3.4
Utility2.5
Mechanics7.3
Opening Duels1.6
Win Impact1.7

Composite 3.2/10 (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-0.04+0.01
first ⅓ avg -0.05 → last ⅓ avg -0.04
Reaction time775ms−11ms
first ⅓ avg 786ms → last ⅓ avg 775ms
Headshot accuracy12.9%+1.1%
first ⅓ avg 11.8% → last ⅓ avg 12.9%

Rolling 5-match average across the last 99 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.12Best match rating · 13–3 · anubis, 20 Jan →
41%Best headshot accuracy · 2–13 · inferno, 20 Feb →
453msFastest reaction time · 13–3 · anubis, 20 Jan →
13–0Biggest win · dust2, 18 May →

Across the last 99 tracked matches.

Highlights

6Longest win streak
2–8In matches decided by ≤2 rounds
5Overtime games

Map breakdown

anubisBest map · 50% over 18mirageWeakest map · 32% over 22
MapGradePlayedRecordWin rateAvg rating
infernoB2411–1346%-0.03
dust2C2410–1442%-0.05
mirageD227–1532%-0.05
anubisB189–950%-0.04
ancient—40–40%-0.06
nuke—30–30%-0.06
train—31–233%-0.03
italy—10–10%-0.06

Across the last 99 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (32% over 22). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

33Matches
39%Win rate
0.59Avg K/D
56.1ADR
38%Headshot %

Clutches & streaks

30%1v1 clutch win
12%1v2 clutch win
3Longest win streak

Recent Faceit resultsWWLLW

MapMatchesWin rateAvg K/DAvg kills
Mirage1233%0.6010.1
Inferno862%0.598.4
Dust2838%0.659.8
Anubis333%0.479.0
Nuke10%0.507.0
Ancient10%0.459.0

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.

12.6%Headshot accuracy
32.8%Accuracy (enemy spotted)
33.6%Spray accuracy
83.0%Counter-strafing
11.4°Preaim
776msReaction time
20.6%T opening success
43.0%CT opening success
0.24Enemies flashed / flash
6.3%Flash assists
8.76HE damage / grenade
0.95Flashes / 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 12.6176% — 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 775.5493ms — 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 0.2436 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Mirage

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

32% win rate across 22 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno13–11-0.0619%25 May →
mirage7–13-0.0513%25 May →
inferno4–13-0.0319%22 May →
mirage13–5-0.048%22 May →
inferno13–5-0.0114%19 May →
mirage11–13-0.0512%18 May →
inferno13–8-0.0518%18 May →
dust28–13-0.037%18 May →
dust213–00.0520%18 May →
inferno13–50.019%18 May →
ancient11–13-0.0312%18 May →
anubis7–13-0.0710%18 May →
mirage16–13-0.0912%14 May →
inferno4–13-0.058%14 May →
anubis13–10-0.0813%14 May →
mirage8–13-0.0313%14 May →
dust213–8-0.085%14 May →
mirage8–13-0.103%21 Apr →
inferno16–13-0.0125%15 Apr →
inferno13–10-0.080%12 Apr →
anubis13–10-0.0315%7 Apr →
mirage7–13-0.0622%23 Mar →
mirage9–13-0.096%22 Mar →
dust28–13-0.0512%22 Mar →
anubis13–16-0.0621%21 Mar →
inferno7–13-0.066%20 Mar →
mirage8–13-0.0210%20 Mar →
inferno5–13-0.0118%17 Mar →
anubis7–13-0.0214%16 Mar →
nuke10–13-0.0114%16 Mar →
anubis13–9-0.044%16 Mar →
inferno11–13-0.0340%5 Mar →
inferno13–30.039%5 Mar →
anubis13–6-0.0619%5 Mar →
dust216–14-0.0217%5 Mar →
dust213–8-0.0710%4 Mar →
anubis10–130.0213%3 Mar →
dust29–13-0.0826%3 Mar →
inferno13–5-0.022%3 Mar →
inferno11–13-0.0725%3 Mar →
mirage13–4-0.0515%3 Mar →
dust26–13-0.0612%3 Mar →
mirage11–13-0.0625%27 Feb →
train5–130.0219%26 Feb →
dust23–13-0.055%25 Feb →
ancient6–13-0.078%25 Feb →
dust213–9-0.039%25 Feb →
inferno13–60.0516%25 Feb →
anubis9–13-0.0313%25 Feb →
mirage13–80.0010%25 Feb →
train8–13-0.0730%25 Feb →
inferno9–13-0.0413%24 Feb →
dust213–6-0.0421%21 Feb →
inferno2–13-0.0741%20 Feb →
anubis13–80.0220%20 Feb →
dust28–13-0.0214%20 Feb →
anubis13–6-0.0610%19 Feb →
dust213–6-0.0311%15 Feb →
ancient7–13-0.065%9 Feb →
dust24–13-0.1021%9 Feb →
mirage13–40.058%8 Feb →
anubis8–13-0.076%8 Feb →
mirage9–13-0.068%8 Feb →
anubis4–13-0.0915%7 Feb →
mirage11–13-0.079%2 Feb →
ancient11–13-0.0914%2 Feb →
inferno10–13-0.0312%1 Feb →
train13–9-0.044%1 Feb →
mirage6–13-0.0810%1 Feb →
inferno10–13-0.0917%1 Feb →
dust24–13-0.0711%31 Jan →
inferno10–13-0.108%31 Jan →
inferno11–13-0.069%31 Jan →
dust210–130.0118%31 Jan →
mirage5–13-0.0722%31 Jan →
anubis13–9-0.0112%31 Jan →
nuke3–13-0.094%30 Jan →
anubis3–13-0.0624%30 Jan →
inferno5–13-0.029%30 Jan →
mirage13–70.027%30 Jan →
dust22–13-0.093%30 Jan →
dust26–13-0.047%30 Jan →
nuke2–13-0.070%26 Jan →
dust213–5-0.085%26 Jan →
mirage13–10-0.0914%24 Jan →
anubis4–13-0.106%20 Jan →
mirage7–130.0312%20 Jan →
dust29–130.0222%20 Jan →
anubis13–30.126%20 Jan →
inferno13–70.0618%20 Jan →
anubis16–13-0.0910%17 Jan →
dust213–50.0238%17 Jan →
inferno13–9-0.0714%17 Jan →
dust213–3-0.0110%17 Jan →
mirage12–12-0.0510%15 Jan →
dust27–13-0.0917%25 Oct →
dust21–13-0.1218%25 Oct →
mirage6–13-0.123%25 Oct →
italy7–13-0.0611%25 Oct →

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 →

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