FakeDoor

FakeDoor — CS2 Stats

JP76561198840570080[U:1:880304352]Steam profile ↗1 game ban

108Tracked matches32%Win rate2023Tracked since
310Hours in CS13Hrs last 2 wks
CSDB Rating3.9 LearningClutch Specialist
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 29 Aug 2026 (44 days ago). Ranks are recorded once per day this page is viewed.

+6Tracked matches · now 108
0.0ppWin rate · 32.1% → 32.1%

Rating over time

1,000Highest Faceit ELO seen on CSDB
42Days played since 2025-01-29

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled. 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.

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CSDB.GGFakeDoorPEAK ELO1,000csdb.gg/stats

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Performance scores

Aim49
Positioning54
Utility31

0–100 skill scores via Leetify.

Recent form

COLD22–45–5Last 7231%Win rateLLLWLLWLLW

Last 10 vs previous 10: +10pp win rate · +0.03 avg rating · +2.9pp headshot accuracy · −10ms reaction

Win rate +10pp 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

  • 1–4 · 20% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 18%
  • Avg reaction 595ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 17%
  • Avg reaction 634ms

Last 20

  • 5–14–1 · 25% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 15%
  • Avg reaction 639ms

Newest first, from the last 72 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+1.8 against its own average).

Aim4.9
Utility3.1
Positioning5.4
Opening Duels2.2
Clutch6.0

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

jL

Plays most like jL 81% 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. 617ms 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

Aim4.9
Positioning5.4
Utility3.1
Mechanics4.6
Opening Duels1.6
Win Impact0.0

Composite 3.9/10 (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+0.00
first ⅓ avg -0.04 → last ⅓ avg -0.04
Reaction time630ms−5ms
first ⅓ avg 635ms → last ⅓ avg 630ms
Headshot accuracy15.3%−1.8%
first ⅓ avg 17.1% → last ⅓ avg 15.3%

Rolling 5-match average across the last 72 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.07Best match rating · 13–8 · inferno, 10 Dec →
60%Best headshot accuracy · 2–13 · inferno, 8 Feb →
391msFastest reaction time · 8–13 · dust2, 19 May →
13–1Biggest win · inferno, 22 Mar →

Across the last 72 tracked matches.

Highlights

3Longest win streak
L3Current streak
3–9In matches decided by ≤2 rounds

Map breakdown

nukeBest map · 60% over 5trainWeakest map · 0% over 5
MapGradePlayedRecordWin rateAvg rating
dust2D234–1917%-0.04
infernoC188–1044%-0.03
mirageC114–736%-0.01
ancientC52–340%-0.02
nukeA53–260%-0.00
trainD50–50%-0.02
overpass—20–20%-0.04
fachwerk—11–0100%-0.03
vertigo—10–10%-0.05
office—10–10%-0.07

Across the last 72 tracked matches.

Lifetime stats

7,460Lifetime kills
0.96K/D
388Matches
46.9%Match win rate · Top 50% of tracked players
42.7%Headshot %
3.6%Shot accuracy
1,052MVPs
151Hours (in match)
226Bombs planted
236Bombs defused

Most-used weapons

Lifetime map wins

1,196dust2
1,137inferno
435nuke
47train
42vertigo
18office
15italy
8cbble

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

Faceit stats

Combat

3Matches
100%Win rate
0.77Avg K/D
62.2ADR
44%Headshot %

Clutches & streaks

50%1v1 clutch win
0%1v2 clutch win
3Longest win streak

Recent Faceit resultsLLWWW

MapMatchesWin rateAvg K/DAvg kills
Inferno2100%0.8312.5
Dust21100%0.6513.0

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.

15.7%Headshot accuracy
33.4%Accuracy (enemy spotted)
35.8%Spray accuracy
70.5%Counter-strafing
11.3°Preaim
617msReaction time
30.6%T opening success
42.0%CT opening success
0.57Enemies flashed / flash
4.8%Flash assists
4.22HE damage / grenade
2.72Flashes / 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

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 2.718 — below the 4 mark we flag

    Grenade Lineups →
  2. 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 30.6334% — below the 40% mark we flag

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.

0% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
dust210–13-0.0413%1 Oct →
dust27–13-0.0417%25 Sept →
inferno6–13-0.0013%24 Sept →
mirage13–50.0328%19 Sept →
dust29–130.0419%19 Sept →
dust23–13-0.0619%19 Sept →
mirage13–6-0.0116%27 Aug →
dust23–13-0.0710%10 Aug →
dust25–13-0.0422%31 Jul →
fachwerk13–5-0.0311%14 Jul →
vertigo1–13-0.0512%26 Jun →
inferno13–8-0.0416%27 May →
inferno13–7-0.0213%27 May →
dust28–13-0.118%19 May →
dust26–13-0.0420%18 May →
inferno3–13-0.1012%17 May →
ancient12–12-0.0617%17 May →
dust21–13-0.029%17 May →
mirage4–13-0.0420%15 May →
overpass9–13-0.1013%13 May →
inferno13–5-0.0321%13 May →
dust23–13-0.0510%13 May →
inferno13–8-0.064%13 May →
dust24–13-0.0224%16 Apr →
dust211–13-0.069%16 Apr →
inferno12–12-0.064%23 Mar →
inferno13–10.0415%22 Mar →
ancient13–10-0.0213%22 Mar →
ancient10–130.0441%9 Mar →
nuke5–130.0023%9 Mar →
mirage4–13-0.0317%9 Mar →
dust26–13-0.0115%9 Mar →
inferno11–130.0011%25 Feb →
dust213–6-0.0111%3 Feb →
mirage8–13-0.0514%15 Dec →
mirage5–130.039%12 Dec →
train11–13-0.058%12 Dec →
dust211–130.0217%12 Dec →
mirage9–13-0.0811%11 Dec →
inferno1–13-0.098%11 Dec →
inferno13–80.0723%10 Dec →
train8–13-0.0316%10 Dec →
nuke13–100.0012%14 Nov →
nuke13–7-0.0521%12 Nov →
ancient13–50.0319%11 Nov →
mirage12–120.0121%11 Nov →
train7–130.0723%11 Nov →
mirage13–7-0.0228%2 Nov →
inferno3–8-0.070%2 Nov →
dust211–13-0.0626%2 Nov →
dust24–13-0.129%18 Oct →
dust213–11-0.0416%26 Sept →
mirage13–11-0.0420%15 Sept →
inferno13–10-0.0114%15 Sept →
overpass12–120.0211%7 Sept →
dust213–9-0.0122%5 Sept →
office10–13-0.0735%5 Sept →
inferno13–90.0318%5 Sept →
train4–13-0.1012%5 Sept →
nuke13–30.0422%1 Mar →
dust211–13-0.0431%1 Mar →
inferno7–13-0.068%26 Feb →
dust29–13-0.088%26 Feb →
dust213–11-0.0415%19 Feb →
nuke10–13-0.0011%15 Feb →
inferno2–13-0.1360%8 Feb →
train11–13-0.013%8 Feb →
ancient8–13-0.099%8 Feb →
mirage11–130.0613%31 Jan →
inferno11–13-0.0520%31 Jan →
inferno12–12-0.0311%30 Jan →
dust28–13-0.0617%29 Jan →

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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