Insane

Insane — CS2 Stats

76561198117636342[U:1:157370614]Steam profile ↗✓ No bans

467Tracked matches48%Win rate2020Tracked since
1,866Hours in CS
CSDB Rating3.8 LearningSupport
WingmanSilver IV
Ladder ranks via Leetify

Performance scores

Aim38
Positioning40
Utility51

0–100 skill scores via Leetify.

Recent form

STEADY37–55–8Last 10037%Win rateWLLWLLWWLW

Last 10 vs previous 10: 0pp win rate · +0.00 avg rating · +3.9pp headshot accuracy · +8ms reaction

Win rate 0pp 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

  • 2–3 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 24%
  • Avg reaction 611ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 24%
  • Avg reaction 645ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 22%
  • Avg reaction 641ms

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 (+2 against its own average).

Aim3.8
Utility5.1
Positioning4.0
Opening Duels0.1

Effective flashesLimited 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

iM

Plays most like iM 69% 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

Strengths

Flashes. 0.94 enemies blinded per flash — utility that consistently lands.

Areas to improve

T-side openings. Opening success drops from 34% on CT to 17% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 636ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 67% 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

Aim3.8
Positioning4.0
Utility5.1
Mechanics3.9
Opening Duels0.5
Win Impact4.4

Composite 3.8/10 (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 -0.04 → last ⅓ avg -0.04
Reaction time650ms−60ms
first ⅓ avg 710ms → last ⅓ avg 650ms
Headshot accuracy23.7%+0.3%
first ⅓ avg 23.4% → last ⅓ avg 23.7%

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

0.17Best match rating · 9–0 · inferno, 15 Jun →
63%Best headshot accuracy · 3–9 · inferno, 5 Jun →
453msFastest reaction time · 3–9 · inferno, 5 Jun →
13–2Biggest win · dust2, 22 May →

Across the last 100 tracked matches.

Highlights

4Longest win streak
6–6In matches decided by ≤2 rounds
1Overtime games

Map breakdown

Strongest and weakest map need 5+ matches on two different maps — 1 of 7 maps qualify so far.

MapGradePlayedRecordWin rateAvg rating
dust2C8430–5436%-0.04
inferno—42–250%-0.03
anubis—41–325%-0.06
ancient—33–0100%-0.04
poseidon—21–150%-0.06
overpass—20–20%-0.07
mirage—10–10%-0.10

Across the last 100 tracked matches.

Lifetime stats

72,648Lifetime kills
0.62K/D
5,927Matches
36.3%Match win rate
40.4%Headshot %
16.3%Shot accuracy · Top 25% of tracked players
6,752MVPs
1,866Hours (in match)
2,880Bombs planted
697Bombs defused

Most-used weapons

Lifetime map wins

19,739dust2
3,752inferno
3,639nuke
739vertigo
646cbble
591train
428office
398italy

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

Faceit stats

Combat

35Matches
54%Win rate
1.02Avg K/D
—ADR
47%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
7Longest win streak

Recent Faceit resultsWLWLL

MapMatchesWin rateAvg K/DAvg kills
Nuke10%0.9415.0
Overpass10%0.477.0
Vertigo1100%1.8613.0
Mirage10%0.9313.0

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.

22.2%Headshot accuracy
23.6%Accuracy (enemy spotted)
19.3%Spray accuracy
67.4%Counter-strafing
7.1°Preaim
636msReaction time
17.0%T opening success
34.2%CT opening success
0.94Enemies flashed / flash
5.6%Flash assists
8.58HE damage / grenade
4.17Flashes / 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

    Sustained sprays are missing more than they land, which is a recoil-control pattern you can drill directly.

    Spray accuracy 19.2961% — below the 20% mark we flag

    Practice Config →

Recent matches

MapScoreRatingHS%Date
dust213–11-0.0524%1 Nov →
dust23–6-0.0031%3 Oct →
dust26–13-0.0219%13 Sept →
dust213–9-0.0512%13 Sept →
dust22–13-0.0332%16 Aug →
dust27–13-0.1030%28 Jul →
dust213–8-0.039%17 Jul →
dust213–9-0.0438%16 Jul →
dust24–13-0.1018%14 Jul →
dust213–8-0.0228%13 Jul →
dust213–9-0.1113%12 Jul →
dust25–13-0.0513%12 Jul →
dust22–13-0.0814%9 Jul →
dust213–5-0.0124%9 Jul →
dust213–40.0223%8 Jul →
dust211–13-0.0420%6 Jul →
dust29–13-0.0823%6 Jul →
dust213–4-0.0217%6 Jul →
dust213–11-0.0437%6 Jul →
dust23–13-0.0719%2 Jul →
dust213–8-0.0217%2 Jul →
dust212–12-0.0845%1 Jul →
dust213–9-0.0320%29 Jun →
dust212–12-0.0411%29 Jun →
inferno9–5-0.0633%23 Jun →
dust210–13-0.0424%22 Jun →
dust212–12-0.0530%22 Jun →
dust213–7-0.0015%22 Jun →
inferno8–8-0.0842%15 Jun →
inferno9–00.1722%15 Jun →
poseidon3–9-0.0625%15 Jun →
poseidon9–4-0.0522%15 Jun →
dust29–13-0.0232%13 Jun →
dust211–13-0.0019%12 Jun →
dust29–13-0.077%9 Jun →
anubis9–13-0.0611%8 Jun →
dust212–12-0.0519%8 Jun →
inferno3–9-0.1563%5 Jun →
dust25–13-0.120%25 May →
dust25–13-0.0315%25 May →
dust210–13-0.1130%25 May →
dust213–9-0.0419%25 May →
dust213–30.0014%22 May →
dust213–80.0133%22 May →
dust213–20.0825%22 May →
dust24–13-0.0613%17 May →
dust28–13-0.097%17 May →
dust210–13-0.0617%15 May →
anubis4–13-0.0715%15 May →
anubis7–13-0.0510%15 May →
dust28–13-0.059%3 May →
dust25–13-0.0510%3 May →
dust29–13-0.0815%28 Apr →
overpass11–13-0.095%26 Apr →
dust23–13-0.0419%26 Apr →
dust26–13-0.0644%26 Apr →
anubis13–10-0.049%26 Apr →
dust213–11-0.0219%24 Apr →
dust29–13-0.0510%23 Apr →
dust210–13-0.047%17 Apr →
dust212–12-0.0328%5 Apr →
dust212–120.0212%5 Apr →
dust24–13-0.0427%5 Apr →
ancient13–11-0.0520%31 Mar →
dust29–13-0.0822%31 Mar →
dust213–70.0018%23 Mar →
dust213–50.0219%23 Mar →
dust213–7-0.0726%22 Mar →
dust25–13-0.0919%22 Mar →
dust210–13-0.0627%20 Mar →
dust213–7-0.0433%16 Mar →
dust213–6-0.0430%16 Mar →
dust211–13-0.0914%15 Mar →
dust210–13-0.085%15 Mar →
dust21–13-0.098%15 Mar →
dust213–110.0040%15 Mar →
dust210–13-0.0746%8 Mar →
overpass9–13-0.0619%8 Mar →
dust27–13-0.0721%8 Mar →
dust22–13-0.0650%8 Mar →
ancient16–14-0.0625%8 Mar →
dust213–30.0029%8 Mar →
ancient13–80.0029%5 Mar →
mirage1–13-0.109%5 Mar →
dust213–6-0.0020%3 Mar →
dust26–13-0.0421%3 Mar →
dust27–13-0.067%3 Mar →
dust213–8-0.058%26 Feb →
dust213–5-0.0019%26 Feb →
dust211–13-0.0214%24 Feb →
dust210–13-0.0524%23 Feb →
dust213–10-0.0031%22 Feb →
dust213–40.0047%22 Feb →
dust211–13-0.0522%19 Feb →
dust25–13-0.0817%17 Feb →
dust29–13-0.0525%17 Feb →
dust27–13-0.0725%16 Feb →
dust29–130.0325%10 Feb →
dust23–13-0.0214%9 Feb →
dust212–12-0.0424%9 Feb →

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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