MICHELANGELO JR.

MICHELANGELO JR. — CS2 Stats

US76561198057735204[U:1:97469476]Steam profile ↗✓ No bans

776Tracked matches38%Win rate2022Tracked since
1,006Hours in CS3Hrs last 2 wks
CSDB Rating3.0 LearningPositional Player
FaceitLevel 2Top 97.9% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 12,592 +8,087 16 Dec – 6 Mar · 6 days played
4,21112,761peak 12,76116 Dec6 Mar
12,862Peak Premier in tracked matches
36Days played since 2025-09-27

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 Level 2 among CSDB-tracked players (n=5,923), 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 2 medianLevel 3 medianvs Level 3
Headshot rate44.4%41.3%41.8%above
Shot accuracy12.3%12.7%12.2%meets
Kill/death ratio0.820.950.980.15 short
Match win rate39.2%42.6%43.3%4.1% short

This profile matches the typical Level 3 player on 2 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Level 3 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGMICHELANGELO JR.FACEITLevel 2STANDINGTop 97.9% of rankedcsdb.gg/stats

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Performance scores

Aim25
Positioning48
Utility37

0–100 skill scores via Leetify.

Recent form

COLD47–49–4Last 10047%Win rateLLLWLTLWLL

Last 10 vs previous 10: −20pp win rate · −0.01 avg rating · −1.9pp headshot accuracy · −17ms reaction

Win rate down 20pp 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

  • 1–4 · 20% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 13%
  • Avg reaction 681ms

Last 10

  • 2–7–1 · 20% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 14%
  • Avg reaction 652ms

Last 20

  • 6–13–1 · 30% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 14%
  • Avg reaction 660ms

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 (+1.2 against its own average).

Aim2.5
Utility3.7
Positioning4.8
Opening Duels2.2

Strong CT-side opener

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

jL

Plays most like jL 66% 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

T-side openings. Opening success drops from 49% on CT to 26% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 662ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 64% 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

Aim2.5
Positioning4.8
Utility3.7
Mechanics3.0
Opening Duels2.3
Win Impact1.0

Composite 3.0/10 (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-0.02+0.00
first ⅓ avg -0.03 → last ⅓ avg -0.02
Reaction time659ms+9ms
first ⅓ avg 650ms → last ⅓ avg 659ms
Headshot accuracy13.2%−1.4%
first ⅓ avg 14.5% → last ⅓ avg 13.2%

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

0.13Best match rating · 13–3 · vertigo, 1 Apr →
31%Best headshot accuracy · 2–13 · dust2, 8 Oct →
438msFastest reaction time · 7–13 · office, 26 Aug →
13–0Biggest win · office, 8 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L3Current streak
6–9In matches decided by ≤2 rounds
7Overtime games

Map breakdown

nukeBest map · 86% over 7ancientWeakest map · 33% over 6
MapGradePlayedRecordWin rateAvg rating
dust2C3013–1743%-0.03
mirageB157–847%-0.04
officeA116–555%-0.00
infernoC83–538%-0.07
vertigoA74–357%0.01
trainA74–357%-0.02
nukeS76–186%-0.01
ancientD62–433%-0.03
cache—31–233%-0.02
anubis—21–150%-0.03
overpass—20–20%-0.03
golden—10–10%0.06
grail—10–10%-0.09

Across the last 100 tracked matches.

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

Lifetime stats

24,366Lifetime kills
0.82K/D
1,699Matches
39.2%Match win rate
44.4%Headshot % · Top 50% of Level 2 players
12.3%Shot accuracy
2,166MVPs
555Hours (in match)
1,450Bombs planted
148Bombs defused

Most-used weapons

Lifetime map wins

6,742dust2
1,036vertigo
834office
768nuke
507inferno
190train
91italy
88bank

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.

13.1%Headshot accuracy
30.5%Accuracy (enemy spotted)
30.0%Spray accuracy
63.5%Counter-strafing
12.3°Preaim
662msReaction time
26.2%T opening success
48.7%CT opening success
0.54Enemies flashed / flash
6.7%Flash assists
11.25HE damage / grenade
5.02Flashes / 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 12.3487° — 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 13.0673% — below the 15% 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.

33% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache9–130.029%2 Oct →
mirage9–13-0.0911%2 Oct →
mirage10–13-0.038%1 Oct →
vertigo13–60.0223%24 Sept →
vertigo3–13-0.0214%24 Sept →
dust212–120.0019%24 Sept →
vertigo6–13-0.0112%24 Sept →
train13–30.0616%24 Sept →
dust27–13-0.0814%24 Sept →
cache6–13-0.097%24 Sept →
inferno5–13-0.0410%2 Sept →
train4–13-0.0211%2 Sept →
office7–13-0.0216%26 Aug →
dust213–10-0.0318%26 Aug →
mirage8–13-0.0311%26 Aug →
dust213–60.0021%9 Jul →
cache13–110.0219%9 Jul →
mirage11–13-0.0814%1 Jul →
dust28–13-0.0522%1 Jul →
vertigo13–30.1312%1 Apr →
mirage6–13-0.0321%27 Mar →
inferno16–12-0.0513%6 Mar →
nuke13–4-0.0110%6 Mar →
dust210–13-0.0310%6 Mar →
dust214–16-0.019%3 Mar →
dust214–16-0.066%2 Mar →
mirage13–8-0.008%2 Mar →
nuke13–8-0.067%2 Mar →
ancient3–13-0.066%27 Feb →
mirage13–8-0.0515%27 Feb →
nuke13–60.1119%27 Feb →
dust28–13-0.0615%2 Feb →
nuke13–11-0.076%2 Feb →
dust213–9-0.0314%1 Feb →
mirage13–10-0.0812%1 Feb →
dust27–10.0510%1 Feb →
anubis11–13-0.049%1 Feb →
anubis16–13-0.0312%23 Jan →
dust213–80.0714%23 Jan →
mirage16–12-0.039%22 Jan →
mirage13–2-0.0613%22 Jan →
dust213–50.0312%22 Jan →
mirage7–130.0215%22 Jan →
mirage13–6-0.059%15 Jan →
ancient10–13-0.0114%15 Jan →
ancient14–16-0.0411%15 Jan →
mirage11–13-0.0821%15 Jan →
dust213–60.0112%15 Jan →
nuke13–60.0213%15 Jan →
ancient11–13-0.072%15 Jan →
office6–13-0.0116%14 Jan →
mirage5–130.0510%14 Jan →
dust23–13-0.0722%14 Jan →
inferno13–11-0.0216%16 Dec →
ancient13–80.0015%16 Dec →
mirage13–8-0.0913%16 Dec →
train8–13-0.0510%10 Dec →
inferno7–9-0.0830%16 Nov →
inferno2–9-0.1713%16 Nov →
inferno8–8-0.114%16 Nov →
vertigo9–40.1014%16 Nov →
train13–10-0.0110%14 Nov →
inferno13–10-0.0414%14 Nov →
inferno7–13-0.0123%8 Nov →
train13–6-0.0416%8 Nov →
dust213–8-0.0013%8 Nov →
dust25–13-0.097%2 Nov →
overpass4–13-0.0717%2 Nov →
nuke3–13-0.0612%26 Oct →
dust216–13-0.0317%26 Oct →
office7–13-0.0414%22 Oct →
train7–130.0110%22 Oct →
overpass8–130.008%12 Oct →
ancient13–11-0.0012%12 Oct →
office6–13-0.0120%12 Oct →
train13–7-0.1215%12 Oct →
dust28–130.0110%10 Oct →
dust213–10.0819%10 Oct →
office13–9-0.039%10 Oct →
dust29–13-0.0814%10 Oct →
dust25–13-0.0113%10 Oct →
nuke13–100.0215%9 Oct →
dust22–13-0.0531%8 Oct →
office13–11-0.0112%8 Oct →
office13–00.0121%8 Oct →
dust23–13-0.078%8 Oct →
dust24–13-0.0923%3 Oct →
dust213–8-0.0712%2 Oct →
office13–60.0611%2 Oct →
office13–100.0211%2 Oct →
golden12–120.0613%2 Oct →
office7–13-0.0620%1 Oct →
dust213–70.0513%1 Oct →
vertigo13–11-0.0822%1 Oct →
dust210–13-0.0614%1 Oct →
vertigo11–13-0.1021%28 Sept →
dust213–10-0.087%28 Sept →
dust212–12-0.0615%27 Sept →
office13–70.0911%27 Sept →
grail4–13-0.099%27 Sept →

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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