MiQuli_

MiQuli_ — CS2 Stats

76561198068952282[U:1:108686554]Steam profile ↗✓ No bans

632Tracked matches37%Win rate2020Tracked since
917Hours in CS1Hrs last 2 wks
CSDB Rating2.9 LearningSupport
FaceitLevel 3Top 90.6% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 2 Sep 2026 (64 days ago). Ranks are recorded once per day this page is viewed.

+17Tracked matches · now 632
−6.7ppWin rate · 43.3% → 36.7%

Rating over time

Premier CS Rating: 16,574 +8,818 9 Jul – 29 Jun · 5 days played
7,75616,574peak 16,5749 Jul29 Jun
16,574Peak Premier in tracked matches
861Highest Faceit ELO seen on CSDB
67Days played since 2025-07-09

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

How this compares with the same rank

Median values for Level 3 among CSDB-tracked players (n=10,505), 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 3 medianLevel 4 medianvs Level 4
Headshot rate39.7%41.8%42.7%3.0% short
Shot accuracy7.8%12.2%11.2%3.5% short
Kill/death ratio0.620.980.990.37 short
Match win rate39.7%43.3%43.9%4.2% short

This profile sits below the typical Level 4 player on every metric we can compare.

Widest gap: Kill/death ratio. That is the metric furthest from the Level 4 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGMiQuli_FACEITLevel 3STANDINGTop 90.6% of rankedPEAK ELO861csdb.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

Aim27
Positioning44
Utility44

0–100 skill scores via Leetify.

Recent form

STEADY43–55–2Last 10043%Win rateWWLLWLWWWL

Last 10 vs previous 10: +50pp win rate · +0.03 avg rating · +2.5pp headshot accuracy · +15ms reaction

Win rate up 50pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 19%
  • Avg reaction 597ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 17%
  • Avg reaction 573ms

Last 20

  • 7–13 · 35% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 16%
  • Avg reaction 565ms

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: Support — Utility contribution stands above the rest of this profile (+1.2 against its own average).

Aim2.7
Utility4.4
Positioning4.4
Opening Duels0.7
Clutch3.2

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

iM

Plays most like iM 65% 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. 571ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 58% 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

Aim2.7
Positioning4.4
Utility4.4
Mechanics1.8
Opening Duels1.9
Win Impact0.6

Composite 2.9/10 (Learning), 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-0.04+0.01
first ⅓ avg -0.05 → last ⅓ avg -0.04
Reaction time575ms−73ms
first ⅓ avg 648ms → last ⅓ avg 575ms
Headshot accuracy16.7%+3.5%
first ⅓ avg 13.1% → last ⅓ avg 16.7%

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

0.10Best match rating · 9–13 · ancient, 17 Apr →
35%Best headshot accuracy · 8–13 · ancient, 27 Jan →
406msFastest reaction time · 7–13 · ancient, 19 Sept →
13–3Biggest win · cache, 29 Apr →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W2Current streak
9–9In matches decided by ≤2 rounds
13Overtime games

Map breakdown

infernoBest map · 67% over 6ancientWeakest map · 31% over 36
MapGradePlayedRecordWin rateAvg rating
ancientD3611–2531%-0.04
nukeS2013–765%-0.04
anubisC187–1139%-0.02
cacheA74–357%-0.04
infernoS64–267%-0.03
overpassA53–260%-0.04
mirage—30–30%-0.07
train—31–233%-0.01
cache_b—20–20%-0.03

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (31% over 36). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

16,159Lifetime kills
0.62K/D
1,325Matches
39.7%Match win rate
39.7%Headshot %
7.8%Shot accuracy
2,184MVPs
545Hours (in match)
1,497Bombs planted
821Bombs defused

Most-used weapons

Lifetime map wins

4,360nuke
683inferno
619vertigo
413train
220dust2
31lake
20italy
18cbble

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

Faceit stats

Combat

128Matches
41%Win rate
0.70Avg K/D
55.5ADR
40%Headshot %

Clutches & streaks

36%1v1 clutch win
12%1v2 clutch win
3Longest win streak

Recent Faceit resultsWLLLW

MapMatchesWin rateAvg K/DAvg kills
Ancient4432%0.7110.6
Nuke3358%0.6810.7
Anubis2544%0.8012.3
Cache617%0.629.8
Overpass633%0.437.5
Mirage450%0.6310.0
Train450%0.8812.3
Vertigo333%0.629.7

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.

16.1%Headshot accuracy
26.6%Accuracy (enemy spotted)
27.5%Spray accuracy
58.1%Counter-strafing
11.7°Preaim
571msReaction time
41.5%T opening success
33.7%CT opening success
0.41Enemies flashed / flash
4.8%Flash assists
6.98HE damage / grenade
10.77Flashes / 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 0.4073 — below the 0.5 mark we flag

    Grenade Lineups →
  2. Advanced Mechanics

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 33.7074% — below the 40% mark we flag

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.

31% win rate across 36 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis13–7-0.0321%2 Nov →
cache13–7-0.0420%2 Nov →
ancient11–13-0.0715%21 Oct →
anubis13–16-0.0414%29 Sept →
ancient13–50.0624%29 Sept →
anubis7–13-0.0111%27 Sept →
cache13–11-0.0516%27 Sept →
anubis13–70.0722%27 Sept →
ancient16–14-0.0314%27 Sept →
nuke10–13-0.0714%19 Sept →
ancient7–13-0.0915%19 Sept →
ancient5–13-0.110%14 Sept →
anubis9–13-0.0314%14 Sept →
ancient13–16-0.0415%9 Sept →
nuke6–13-0.0524%31 Aug →
anubis13–9-0.0112%30 Aug →
ancient10–130.0017%29 Aug →
anubis6–13-0.0512%29 Aug →
cache8–13-0.0818%29 Aug →
cache13–16-0.0618%26 Aug →
ancient11–13-0.069%25 Aug →
anubis13–10-0.0418%19 Aug →
ancient8–13-0.059%19 Aug →
ancient16–14-0.0310%16 Aug →
cache3–13-0.0322%16 Aug →
ancient6–13-0.129%12 Aug →
nuke13–10-0.0615%9 Aug →
cache13–90.0125%3 Aug →
anubis9–13-0.0230%13 Jul →
anubis5–130.0229%10 Jul →
inferno13–8-0.0529%29 Jun →
ancient5–13-0.0924%23 May →
ancient10–13-0.048%21 May →
nuke13–11-0.0417%16 May →
ancient13–11-0.0616%29 Apr →
cache13–3-0.0618%29 Apr →
ancient13–50.0420%26 Apr →
anubis14–16-0.0411%24 Apr →
anubis13–5-0.0115%22 Apr →
anubis14–16-0.0322%17 Apr →
ancient9–130.1017%17 Apr →
ancient7–130.0119%24 Mar →
ancient13–11-0.049%24 Mar →
ancient13–9-0.0419%15 Mar →
anubis3–13-0.089%15 Feb →
nuke10–13-0.0821%9 Feb →
inferno16–12-0.0419%7 Feb →
overpass13–8-0.0311%7 Feb →
anubis13–30.039%7 Feb →
anubis11–13-0.0512%6 Feb →
nuke13–5-0.0410%4 Feb →
anubis5–13-0.0514%3 Feb →
ancient13–5-0.0125%3 Feb →
anubis13–6-0.0326%3 Feb →
nuke13–8-0.0521%27 Jan →
ancient8–13-0.0535%27 Jan →
nuke13–80.0416%26 Jan →
ancient13–80.0314%22 Jan →
nuke13–100.0014%18 Jan →
overpass11–13-0.0420%18 Jan →
mirage6–13-0.0420%11 Jan →
nuke13–8-0.0210%6 Jan →
train8–13-0.0213%6 Jan →
inferno15–15-0.0317%4 Jan →
nuke13–11-0.049%9 Dec →
cache_b5–13-0.0010%9 Dec →
inferno13–50.0210%8 Dec →
cache_b6–13-0.0611%8 Dec →
ancient12–16-0.0615%3 Dec →
nuke13–5-0.048%3 Dec →
nuke7–13-0.0120%26 Oct →
overpass11–13-0.0916%26 Oct →
overpass13–50.0110%19 Oct →
ancient10–13-0.0215%12 Oct →
train13–60.0211%12 Oct →
ancient15–15-0.064%12 Oct →
nuke13–9-0.0213%11 Oct →
ancient10–13-0.0419%11 Oct →
nuke13–6-0.0821%5 Oct →
nuke8–13-0.0915%28 Sept →
ancient13–3-0.0813%24 Sept →
ancient22–25-0.065%21 Sept →
nuke13–11-0.0714%21 Sept →
ancient13–16-0.0316%16 Sept →
train11–13-0.0111%14 Sept →
ancient10–13-0.0510%1 Sept →
ancient7–13-0.0719%24 Aug →
ancient8–13-0.113%22 Aug →
ancient13–5-0.0719%22 Aug →
nuke9–13-0.0619%20 Aug →
ancient7–13-0.0218%17 Aug →
overpass13–10-0.0415%17 Aug →
mirage3–13-0.1014%12 Aug →
mirage6–13-0.076%11 Aug →
ancient8–13-0.079%10 Aug →
ancient8–13-0.0717%10 Aug →
nuke11–13-0.0411%9 Aug →
nuke13–6-0.0411%24 Jul →
inferno13–11-0.056%24 Jul →
inferno9–13-0.0019%9 Jul →

Match data via Leetify.

Recent teammates

Milestones

500 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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