door hole

door hole — CS2 Stats

76561198100649131[U:1:140383403]Steam profile ↗✓ No bans

85Tracked matches43%Win rate2022Tracked since
95Hours in CS
CSDB Rating2.3 LearningPositional Player
Ladder ranks via Leetify

Performance scores

Aim17
Positioning47
Utility19

0–100 skill scores via Leetify.

Recent form

STEADY32–44–7Last 8339%Win rateWWTLWLTLLW

Last 10 vs previous 10: +20pp win rate · −0.02 avg rating · −8.6pp headshot accuracy · −92ms reaction

Win rate up 20pp 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 (−0.02), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 3–1–1 · 60% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 15%
  • Avg reaction 705ms

Last 10

  • 4–4–2 · 40% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 16%
  • Avg reaction 731ms

Last 20

  • 6–12–2 · 30% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 21%
  • Avg reaction 777ms

Newest first, from the last 83 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 (+2.1 against its own average).

Aim1.7
Utility1.9
Positioning4.7
Opening Duels1.3

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

jL

Plays most like jL 67% playstyle similarity

Most alike: positioning profile, utility contribution.

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. 763ms 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

Aim1.7
Positioning4.7
Utility1.9
Mechanics1.7
Opening Duels0.7
Win Impact2.6

Composite 2.3/10 (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-0.04−0.00
first ⅓ avg -0.04 → last ⅓ avg -0.04
Reaction time766ms−30ms
first ⅓ avg 796ms → last ⅓ avg 766ms
Headshot accuracy20.4%−1.7%
first ⅓ avg 22.1% → last ⅓ avg 20.4%

Rolling 5-match average across the last 83 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.13Best match rating · 13–2 · mirage, 4 Sept →
67%Best headshot accuracy · 2–1 · nuke, 15 Jan →
539msFastest reaction time · 2–13 · anubis, 5 Sept →
13–0Biggest win · dust2, 12 Sept →

Across the last 83 tracked matches.

Highlights

4Longest win streak
W2Current streak
3–3In matches decided by ≤2 rounds
1Overtime games

Map breakdown

infernoBest map · 50% over 18trainWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
mirageD217–1433%-0.03
dust2B199–1047%-0.02
infernoB189–950%-0.03
nukeC114–736%-0.04
trainD51–420%0.00
vertigo—41–325%-0.04
cache—20–20%-0.08
ancient—21–150%-0.04
anubis—10–10%-0.08

Across the last 83 tracked matches.

Lifetime stats

4,195Lifetime kills
0.79K/D
379Matches
25.3%Match win rate
40.7%Headshot %
10.2%Shot accuracy
314MVPs
95Hours (in match)
159Bombs planted
40Bombs defused

Most-used weapons

Lifetime map wins

448dust2
392inferno
129nuke
106vertigo
76train
15office
9ar_shoots
7ar_baggage

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.

18.3%Headshot accuracy
27.4%Accuracy (enemy spotted)
31.8%Spray accuracy
57.6%Counter-strafing
12.3°Preaim
763msReaction time
32.6%T opening success
33.1%CT opening success
0.46Enemies flashed / flash
5.0%Flash assists
4.05HE damage / grenade
3.60Flashes / 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 12.2629° — above the 12° mark we flag

    Aim Training →
  2. 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 762.8937ms — above the 700ms mark we flag

    Aim Training →
  3. 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 0.4594 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Train

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
dust213–10-0.0715%24 Sept →
nuke13–9-0.0916%18 Sept →
cache12–12-0.0413%18 Sept →
inferno3–13-0.1218%30 Jun →
ancient13–10-0.0512%30 Jun →
nuke6–13-0.0733%30 Jun →
cache12–12-0.1213%28 Apr →
mirage5–13-0.0614%20 Feb →
nuke10–130.0524%20 Feb →
dust213–7-0.026%3 Feb →
nuke13–6-0.0221%3 Feb →
dust22–13-0.0813%1 Feb →
dust26–13-0.056%27 Jan →
nuke2–10.1267%15 Jan →
mirage1–13-0.0614%8 Jan →
nuke5–13-0.0829%8 Jan →
dust24–13-0.0650%16 Dec →
inferno9–13-0.0513%15 Dec →
mirage4–13-0.0515%15 Dec →
train13–3-0.0723%15 Dec →
dust213–4-0.0422%15 Dec →
inferno4–13-0.0630%9 Dec →
dust213–90.0021%9 Dec →
mirage9–13-0.0512%9 Dec →
dust213–40.0425%9 Dec →
train11–13-0.0313%25 Nov →
dust213–5-0.0413%25 Nov →
inferno13–90.0113%12 Nov →
dust210–13-0.0224%12 Nov →
nuke13–9-0.0413%12 Nov →
mirage2–2-0.020%12 Nov →
vertigo13–9-0.0414%2 Nov →
mirage13–100.0222%14 Oct →
mirage7–13-0.013%1 Oct →
inferno9–130.0314%19 Sept →
dust26–13-0.0318%19 Sept →
nuke12–12-0.0810%18 Sept →
mirage13–110.0413%18 Sept →
dust213–80.0619%18 Sept →
ancient4–13-0.0313%14 Sept →
dust213–10.0518%14 Sept →
inferno13–20.017%12 Sept →
dust213–00.0743%12 Sept →
train12–120.0713%12 Sept →
inferno12–12-0.057%9 Sept →
nuke4–13-0.0720%9 Sept →
dust24–130.009%5 Sept →
anubis2–13-0.0813%5 Sept →
dust24–13-0.0614%5 Sept →
mirage13–20.1329%4 Sept →
dust29–130.0225%4 Sept →
mirage13–5-0.0512%29 Aug →
inferno13–10.0119%29 Aug →
dust212–120.0124%29 Aug →
train4–13-0.0026%11 Apr →
inferno13–6-0.0015%11 Apr →
inferno9–13-0.0148%10 Jan →
inferno13–8-0.0524%10 Jan →
nuke4–13-0.0421%10 Jan →
mirage13–30.1113%4 Dec →
train5–130.0324%18 Nov →
inferno2–13-0.0913%9 Sept →
dust22–13-0.0827%9 Sept →
inferno0–5-0.090%9 Sept →
mirage1–13-0.0223%5 Sept →
mirage1–13-0.0650%20 Aug →
mirage2–13-0.0416%12 Jun →
nuke13–7-0.0919%20 Mar →
vertigo8–13-0.0419%13 Mar →
vertigo12–12-0.0618%13 Mar →
mirage8–13-0.0315%13 Mar →
mirage13–16-0.0615%18 Feb →
mirage2–13-0.0831%14 Feb →
mirage7–1-0.120%13 Feb →
inferno13–3-0.0138%18 Jan →
mirage6–13-0.0116%18 Jan →
vertigo4–13-0.0224%16 Jan →
inferno11–13-0.1132%12 Jan →
inferno13–50.0330%29 Dec →
inferno13–90.0433%28 Dec →
mirage7–13-0.0914%4 Dec →
mirage0–13-0.1225%28 Nov →
inferno9–70.0112%26 Jul →

Match data via Leetify.

Recent teammates

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

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