Mirtze

Mirtze — CS2 Stats

FI76561198316741161[U:1:356475433]Steam profile ↗✓ No bans

493Tracked matches28%Win rate2024Tracked since
991Hours in CS0Hrs last 2 wks
CSDB Rating1.0 LearningPositional Player
Premier CS Rating1,869Grey band · top ~92.1% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 5 Jul 2026 (123 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 1,869 +467 1 Mar – 5 Jul · 24 days played
1,0002,196peak 2,1961 Mar5 Jul
2,267Peak Premier in tracked matches
46Days played since 2026-01-17

Premier CS Rating

  • 327 below peak (2,196)
  • +524 over 30 days · improving
  • +197 over 90 days
  • Next: Light Blue band at 5,000 — 3,131 to go

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

How this compares with the same rank

Median values for Grey band among CSDB-tracked players (n=3,645), 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 rate34.2%38.2%39.9%5.8% short
Shot accuracy0.0%3.6%7.0%7.0% short
Kill/death ratio0.430.830.920.48 short
Match win rate39.4%40.2%42.3%2.8% short

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

Widest gap: Shot accuracy. 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.GGMirtzePREMIER1,869 · Grey bandcsdb.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

Aim4
Positioning30
Utility28

0–100 skill scores via Leetify.

Recent form

STEADY28–69–3Last 10028%Win rateWLLLLLWWWL

Last 10 vs previous 10: +10pp win rate · −0.02 avg rating · −1.0pp headshot accuracy · −28ms 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

  • 1–4 · 20% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 11%
  • Avg reaction 762ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 10%
  • Avg reaction 725ms

Last 20

  • 7–12–1 · 35% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 11%
  • Avg reaction 739ms

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: Positional Player — Positioning stands above the rest of this profile (+0.9 against its own average).

Aim0.4
Utility2.8
Positioning3.0
Opening Duels0.4

Limited 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

m0NESY

Plays most like m0NESY 58% playstyle similarity

Most alike: utility contribution, positioning profile.

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

Reaction time. 735ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 49% 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

Aim0.4
Positioning3.0
Utility2.8
Mechanics0.0
Opening Duels0.2
Win Impact0.0

Composite 1.0/10 (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-0.07+0.00
first ⅓ avg -0.07 → last ⅓ avg -0.07
Reaction time736ms−41ms
first ⅓ avg 777ms → last ⅓ avg 736ms
Headshot accuracy10.9%+1.2%
first ⅓ avg 9.7% → last ⅓ avg 10.9%

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.

Personal bests

0.05Best match rating · 13–3 · anubis, 11 Oct →
22%Best headshot accuracy · 13–10 · nuke, 21 Feb →
469msFastest reaction time · 13–3 · anubis, 11 Oct →
13–3Biggest win · anubis, 11 Oct →

Across the last 100 tracked matches.

Highlights

4Longest win streak
6–4In matches decided by ≤2 rounds
4Overtime games

Map breakdown

vertigoBest map · 50% over 10ancientWeakest map · 18% over 11
MapGradePlayedRecordWin rateAvg rating
nukeD214–1719%-0.07
anubisD175–1229%-0.06
infernoD164–1225%-0.08
ancientD112–918%-0.09
vertigoB105–550%-0.07
dust2D103–730%-0.05
overpassC83–538%-0.08
mirageC52–340%-0.06
cache—10–10%-0.09
train—10–10%-0.10

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (18% over 11). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

11,372Lifetime kills
0.43K/D
1,522Matches
39.4%Match win rate
34.2%Headshot %
0.0%Shot accuracy
1,072MVPs
571Hours (in match)
848Bombs planted
92Bombs defused

Most-used weapons

Lifetime map wins

2,460inferno
2,423nuke
1,759vertigo
1,307dust2
341office
96train
90italy

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

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

11.0%Headshot accuracy
24.7%Accuracy (enemy spotted)
24.1%Spray accuracy
49.5%Counter-strafing
14.3°Preaim
735msReaction time
20.4%T opening success
31.8%CT opening success
0.41Enemies flashed / flash
1.2%Flash assists
7.13HE damage / grenade
3.38Flashes / 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. Advanced Mechanics

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 14.2561° — above the 12° mark we flag

    Aim Training →
  2. 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 11.0093% — below the 15% mark we flag

    Aim Training →
  3. 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 735.0987ms — above the 700ms mark we flag

    Aim Training →
Spend your practice time on Ancient

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

18% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis13–30.059%11 Oct →
vertigo7–13-0.0510%2 Oct →
cache7–13-0.097%25 Jul →
inferno8–13-0.1113%7 Jul →
vertigo5–13-0.0815%7 Jul →
nuke5–13-0.100%5 Jul →
ancient13–6-0.1011%5 Jul →
overpass13–10-0.0812%5 Jul →
anubis13–10-0.0914%5 Jul →
nuke3–13-0.0912%29 Jun →
vertigo13–3-0.0214%29 Jun →
vertigo4–13-0.0710%8 Jun →
nuke13–9-0.0011%8 Jun →
mirage7–13-0.0913%22 May →
nuke12–12-0.0411%21 May →
nuke10–13-0.098%20 May →
inferno13–7-0.045%20 May →
anubis13–16-0.1016%20 May →
inferno7–13-0.048%20 May →
nuke9–13-0.0916%15 May →
anubis7–13-0.0511%15 May →
dust29–13-0.0211%14 May →
nuke16–14-0.037%14 May →
ancient7–13-0.1415%14 May →
anubis11–13-0.0213%14 May →
nuke4–13-0.0511%14 May →
inferno11–13-0.098%14 May →
inferno7–13-0.137%14 May →
dust25–13-0.0321%14 May →
anubis3–13-0.0715%13 May →
dust213–9-0.0810%27 Apr →
ancient4–13-0.0912%27 Apr →
inferno3–13-0.086%27 Apr →
dust26–13-0.0912%27 Apr →
overpass13–9-0.066%26 Apr →
anubis9–13-0.047%26 Apr →
nuke12–12-0.0616%20 Apr →
inferno10–13-0.098%18 Apr →
anubis11–13-0.0414%18 Apr →
mirage13–11-0.046%18 Apr →
dust23–13-0.055%11 Apr →
vertigo9–13-0.106%10 Apr →
nuke1–13-0.095%10 Apr →
dust24–13-0.0518%10 Apr →
dust23–13-0.099%9 Apr →
ancient2–13-0.1214%6 Apr →
ancient1–13-0.0915%3 Apr →
nuke5–13-0.0911%31 Mar →
anubis10–13-0.098%24 Mar →
nuke3–13-0.085%23 Mar →
vertigo13–8-0.0417%21 Mar →
overpass4–13-0.107%21 Mar →
mirage13–4-0.028%19 Mar →
inferno8–13-0.113%18 Mar →
inferno9–13-0.065%16 Mar →
nuke4–13-0.065%16 Mar →
ancient3–13-0.0812%16 Mar →
anubis13–11-0.0615%16 Mar →
nuke10–13-0.0312%12 Mar →
ancient7–13-0.047%12 Mar →
overpass12–16-0.104%11 Mar →
inferno9–13-0.0510%11 Mar →
mirage8–13-0.108%9 Mar →
dust213–7-0.0715%9 Mar →
inferno13–11-0.0717%8 Mar →
nuke7–13-0.1211%7 Mar →
anubis5–13-0.1014%7 Mar →
overpass2–13-0.0912%7 Mar →
overpass9–13-0.109%1 Mar →
dust213–10-0.0319%1 Mar →
mirage9–13-0.0517%1 Mar →
ancient7–13-0.130%28 Feb →
ancient6–13-0.120%27 Feb →
dust29–13-0.029%27 Feb →
anubis13–4-0.067%27 Feb →
nuke2–13-0.083%27 Feb →
inferno13–8-0.0710%27 Feb →
vertigo11–13-0.105%27 Feb →
nuke8–13-0.1013%27 Feb →
inferno9–13-0.0810%22 Feb →
ancient13–11-0.106%22 Feb →
anubis2–13-0.0710%22 Feb →
anubis16–13-0.0610%22 Feb →
overpass13–9-0.049%21 Feb →
nuke13–10-0.0322%21 Feb →
inferno13–7-0.1010%21 Feb →
nuke7–13-0.1113%21 Feb →
vertigo13–9-0.069%20 Feb →
vertigo13–11-0.0818%10 Feb →
inferno8–13-0.106%10 Feb →
ancient6–13-0.026%10 Feb →
anubis10–13-0.0111%8 Feb →
nuke6–13-0.0210%8 Feb →
vertigo13–10-0.0611%8 Feb →
anubis10–13-0.0615%3 Feb →
anubis10–13-0.0911%2 Feb →
overpass0–13-0.108%30 Jan →
nuke13–10-0.116%30 Jan →
train3–13-0.108%30 Jan →
inferno12–120.008%17 Jan →

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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