Michael Scarn

Michael Scarn — CS2 Stats

US76561198115365170[U:1:155099442]Steam profile ↗✓ No bans

451Tracked matches57%Win rate2020Tracked since
550Hours in CS
CSDB Rating3.7 LearningPositional Player
FaceitLevel 2Top 97.9% of ranked FACEIT players
Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 2 among CSDB-tracked players (n=6,013), 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 rate28.4%41.3%41.8%13.4% short
Shot accuracy11.0%12.7%12.2%1.3% short
Kill/death ratio0.600.950.980.38 short
Match win rate41.4%42.6%43.3%1.9% short

This profile sits below the typical Level 3 player on every metric we can compare.

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.

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CSDB.GGMichael ScarnFACEITLevel 2STANDINGTop 97.9% of rankedcsdb.gg/stats

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Performance scores

Aim46
Positioning31
Utility12

0–100 skill scores via Leetify.

Recent form

HOT53–40–7Last 10053%Win rateWWWWWLLWWW

Last 10 vs previous 10: +60pp win rate · −0.00 avg rating · +1.0pp headshot accuracy · +43ms reaction

Win rate up 60pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (−0.00), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 5–0 · 100% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 13%
  • Avg reaction 567ms

Last 10

  • 8–2 · 80% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 14%
  • Avg reaction 587ms

Last 20

  • 10–9–1 · 50% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 13%
  • 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: Positional Player — Positioning stands above the rest of this profile (+1.8 against its own average).

Aim4.6
Utility1.2
Positioning3.1
Opening Duels0.0
Clutch1.0

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

donk

Plays most like donk 93% playstyle similarity

Most alike: positioning profile, aim profile.

Where you differ: lower utility contribution; lower opening-duel success.

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 563ms 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

Aim4.6
Positioning3.1
Utility1.2
Mechanics5.0
Opening Duels0.0
Win Impact7.4

Composite 3.7/10 (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-0.06−0.00
first ⅓ avg -0.06 → last ⅓ avg -0.06
Reaction time581ms−58ms
first ⅓ avg 639ms → last ⅓ avg 581ms
Headshot accuracy13.8%−3.0%
first ⅓ avg 16.8% → last ⅓ avg 13.8%

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

0.15Best match rating · 9–1 · inferno, 8 Oct →
100%Best headshot accuracy · 7–13 · office, 5 Dec →
375msFastest reaction time · 4–13 · ancient, 11 Sept →
13–2Biggest win · inferno, 7 Jun →

Across the last 100 tracked matches.

Highlights

9Longest win streak
W5Current streak
6–5In matches decided by ≤2 rounds

Map breakdown

infernoBest map · 64% over 14ancientWeakest map · 40% over 10
MapGradePlayedRecordWin rateAvg rating
mirageB2612–1446%-0.06
dust2A2011–955%-0.05
infernoA149–564%-0.07
ancientC104–640%-0.06
nukeA74–357%-0.07
anubisB63–350%-0.07
cache—43–175%-0.05
train—32–167%-0.05
vertigo—21–150%-0.07
office—21–150%-0.10
boulder—11–0100%-0.02
fachwerk—10–10%-0.13
italy—11–0100%-0.04
alpine—11–0100%-0.03
warden—10–10%-0.07
palacio—10–10%-0.07

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (40% over 10). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

14,732Lifetime kills
0.60K/D
1,247Matches
41.4%Match win rate
28.4%Headshot %
11.0%Shot accuracy
1,601MVPs
550Hours (in match)
783Bombs planted
342Bombs defused

Most-used weapons

Lifetime map wins

4,363dust2
1,876inferno
738nuke
444vertigo
373train
59office
59cbble
16lake

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

Faceit stats

Combat

49Matches
49%Win rate
0.62Avg K/D
55.6ADR
30%Headshot %

Clutches & streaks

25%1v1 clutch win
5%1v2 clutch win
6Longest win streak

Recent Faceit resultsWLLWW

MapMatchesWin rateAvg K/DAvg kills
Mirage1856%0.6511.0
Dust2757%1.0211.9
Ancient667%0.415.2
Inferno560%0.658.8
Anubis333%0.617.3
Overpass20%0.458.0
Nuke250%0.163.5
Train10%0.6511.0

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.

13.1%Headshot accuracy
27.0%Accuracy (enemy spotted)
23.1%Spray accuracy
72.7%Counter-strafing
7.1°Preaim
563msReaction time
15.6%T opening success
24.5%CT opening success
0.32Enemies flashed / flash
0.0%Flash assists
6.53HE damage / grenade
1.41Flashes / 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 13.1262% — below the 15% mark we flag

    Aim Training →
  2. 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 0.3192 — below the 0.5 mark we flag

    Grenade Lineups →
  3. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 15.6231% — 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.

40% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust213–11-0.0514%15 Oct →
inferno13–10-0.1021%15 Oct →
dust213–10-0.0614%13 Oct →
anubis13–11-0.0812%11 Oct →
ancient13–11-0.065%11 Oct →
ancient5–13-0.0516%4 Oct →
mirage3–13-0.080%4 Oct →
cache13–7-0.0620%21 Sept →
anubis13–6-0.0917%17 Sept →
anubis13–9-0.0620%17 Sept →
mirage5–5-0.040%17 Sept →
mirage1–13-0.1518%15 Sept →
dust212–12-0.088%15 Sept →
nuke6–13-0.0133%15 Sept →
inferno10–13-0.1211%12 Sept →
nuke3–13-0.044%12 Sept →
mirage13–10-0.058%11 Sept →
ancient4–13-0.110%11 Sept →
mirage10–13-0.0330%10 Sept →
nuke13–5-0.0717%9 Sept →
dust26–13-0.064%9 Sept →
dust213–5-0.020%8 Sept →
dust213–6-0.0213%8 Sept →
mirage9–13-0.0425%8 Sept →
dust213–6-0.018%7 Sept →
inferno13–4-0.0817%7 Sept →
anubis7–13-0.0232%7 Sept →
mirage13–3-0.060%7 Sept →
mirage13–4-0.015%7 Sept →
dust212–12-0.035%7 Sept →
boulder13–4-0.0242%24 Jul →
mirage5–13-0.1217%24 Jul →
fachwerk10–13-0.1320%24 Jul →
italy13–9-0.0416%24 Jul →
cache12–12-0.046%22 Jul →
mirage13–7-0.0512%18 Jul →
mirage1–11-0.0314%18 Jul →
dust213–11-0.0317%18 Jul →
cache13–4-0.0218%7 Jun →
inferno13–2-0.105%7 Jun →
vertigo13–9-0.0818%24 May →
office13–11-0.134%24 May →
mirage13–3-0.0617%24 May →
dust213–10-0.0227%24 May →
cache13–2-0.100%22 May →
dust210–2-0.0614%24 Apr →
mirage4–13-0.150%24 Apr →
vertigo12–12-0.0742%4 Apr →
nuke7–13-0.1211%4 Apr →
dust213–6-0.040%4 Apr →
train13–6-0.0323%4 Apr →
ancient13–10-0.0516%4 Apr →
ancient9–13-0.085%30 Mar →
inferno13–7-0.0914%15 Mar →
inferno8–13-0.080%27 Feb →
dust211–13-0.0426%26 Feb →
ancient12–12-0.0618%17 Feb →
mirage13–7-0.009%16 Feb →
inferno13–7-0.0714%16 Feb →
ancient11–13-0.080%31 Jan →
ancient13–7-0.040%30 Jan →
alpine11–10-0.0321%27 Jan →
mirage13–8-0.0018%23 Jan →
dust27–13-0.0625%23 Jan →
mirage6–13-0.050%23 Jan →
warden8–13-0.075%23 Jan →
anubis12–12-0.0913%23 Jan →
inferno10–13-0.1120%7 Jan →
anubis6–13-0.109%7 Jan →
mirage13–4-0.0311%10 Dec →
mirage12–12-0.1026%10 Dec →
office7–13-0.08100%5 Dec →
mirage2–13-0.077%5 Dec →
train9–13-0.0511%5 Dec →
inferno8–13-0.0711%5 Dec →
dust29–13-0.100%14 Nov →
ancient8–20.0038%14 Nov →
inferno13–8-0.1117%14 Nov →
mirage13–10-0.120%14 Nov →
inferno13–2-0.0219%6 Nov →
inferno8–13-0.067%5 Nov →
mirage13–8-0.0414%5 Nov →
dust213–2-0.0424%5 Nov →
mirage7–13-0.0717%3 Nov →
dust211–13-0.0614%2 Nov →
dust213–20.029%2 Nov →
nuke13–4-0.0910%20 Oct →
nuke13–10-0.0814%20 Oct →
mirage13–7-0.0610%20 Oct →
dust211–13-0.080%20 Oct →
dust210–13-0.0811%20 Oct →
train13–8-0.0615%16 Oct →
mirage3–7-0.0717%14 Oct →
ancient10–13-0.098%14 Oct →
inferno13–10-0.0332%14 Oct →
mirage13–5-0.0827%10 Oct →
palacio10–13-0.079%10 Oct →
inferno9–10.1519%8 Oct →
nuke13–10-0.0416%7 Oct →
mirage9–13-0.0016%7 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 →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.