Josh420

Josh420 — CS2 Stats

DE76561198283571617[U:1:323305889]Steam profile ↗✓ No bans

1,081Tracked matches47%Win rate2022Tracked since
CSDB Rating4.8 DevelopingPositional Player
FaceitLevel 8Top 31.2% of ranked FACEIT players
WingmanLegendary Eagle Master
Ladder ranks via Leetify

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CSDB.GGJosh420FACEITLevel 8STANDINGTop 31.2% of rankedcsdb.gg/stats

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Performance scores

Aim63
Positioning46
Utility36

0–100 skill scores via Leetify.

Recent form

STEADY47–52–1Last 10047%Win rateLWLLWWLWLW

Last 10 vs previous 10: −10pp win rate · −0.02 avg rating · −6.6pp headshot accuracy · −70ms 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

  • 2–3 · 40% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 17%
  • Avg reaction 623ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 19%
  • Avg reaction 658ms

Last 20

  • 11–9 · 55% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 23%
  • Avg reaction 693ms

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 (+1.5 against its own average).

Aim6.3
Utility3.6
Positioning4.6
Opening Duels0.8
Clutch3.4

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

NiKo

Plays most like NiKo 89% 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

Reaction time. 688ms 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

Aim6.3
Positioning4.6
Utility3.6
Mechanics6.5
Opening Duels0.7
Win Impact3.9

Composite 4.8/10 (Developing), 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-0.03−0.02
first ⅓ avg -0.01 → last ⅓ avg -0.03
Reaction time689ms+44ms
first ⅓ avg 645ms → last ⅓ avg 689ms
Headshot accuracy21.5%−1.6%
first ⅓ avg 23.1% → last ⅓ avg 21.5%

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

0.16Best match rating · 13–1 · train, 8 Mar →
46%Best headshot accuracy · 13–9 · anubis, 29 May →
445msFastest reaction time · 13–5 · ancient, 14 Jan →
13–1Biggest win · train, 8 Mar →

Across the last 100 tracked matches.

Highlights

5Longest win streak
7–8In matches decided by ≤2 rounds
14Overtime games

Map breakdown

dust2Best map · 75% over 8infernoWeakest map · 38% over 21
MapGradePlayedRecordWin rateAvg rating
ancientB3618–1850%-0.01
infernoC218–1338%-0.02
anubisB209–1145%-0.02
dust2S86–275%-0.02
cache—42–250%-0.04
mirage—30–30%-0.02
vertigo—32–167%0.01
train—22–0100%0.07
nuke—20–20%-0.07
overpass—10–10%-0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 21). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

836Matches
53%Win rate
1.07Avg K/D
72.2ADR
50%Headshot %

Clutches & streaks

37%1v1 clutch win
21%1v2 clutch win
9Longest win streak

Recent Faceit resultsLLLWL

MapMatchesWin rateAvg K/DAvg kills
Ancient10554%1.0714.9
Inferno7356%1.0415.2
Anubis5941%0.9415.2
Vertigo5347%1.0416.1
Dust22065%0.9412.8
Mirage1346%0.9012.4
Nuke1258%0.9914.3
Train667%1.4416.3

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.

22.0%Headshot accuracy
34.6%Accuracy (enemy spotted)
33.8%Spray accuracy
79.3%Counter-strafing
9.6°Preaim
688msReaction time
26.9%T opening success
35.3%CT opening success
0.50Enemies flashed / flash
5.1%Flash assists
8.23HE damage / grenade
2.87Flashes / 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 2.8708 — 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 26.8504% — below the 40% mark we flag

Spend your practice time on Inferno

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

38% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage13–16-0.0429%24 Jun →
ancient13–7-0.0510%6 Jun →
anubis8–13-0.1214%6 Jun →
ancient7–13-0.1013%4 Jun →
inferno16–130.0521%4 Jun →
ancient13–70.0519%4 Jun →
inferno10–13-0.0135%3 Jun →
ancient13–10-0.0716%3 Jun →
inferno14–16-0.0813%3 Jun →
ancient13–110.0023%3 Jun →
inferno9–13-0.0521%3 Jun →
overpass13–16-0.0518%1 Jun →
inferno9–50.0917%1 Jun →
cache22–18-0.0127%31 May →
ancient16–12-0.0220%31 May →
dust213–10-0.0737%31 May →
inferno8–130.0422%30 May →
dust213–8-0.0322%30 May →
dust20–11-0.0629%30 May →
anubis13–9-0.0146%29 May →
ancient13–80.0124%28 May →
dust213–10-0.0117%27 May →
ancient6–13-0.056%27 May →
dust213–30.0232%23 May →
ancient8–13-0.0515%23 May →
inferno14–16-0.0220%21 May →
anubis8–13-0.0619%20 May →
cache9–13-0.0819%20 May →
cache11–13-0.0729%14 May →
cache13–30.0028%14 May →
ancient5–70.0017%3 Apr →
anubis9–13-0.0810%31 Jul →
inferno10–13-0.0622%31 Jul →
anubis9–13-0.0130%10 Mar →
anubis13–50.0524%9 Mar →
train13–10.1632%8 Mar →
ancient7–130.0119%7 Mar →
ancient7–130.0420%1 Mar →
anubis9–13-0.0619%25 Feb →
ancient6–13-0.0428%24 Feb →
ancient7–130.0316%22 Feb →
ancient13–9-0.0122%21 Feb →
ancient13–30.0517%21 Feb →
inferno13–90.0220%21 Feb →
ancient13–80.0624%21 Feb →
inferno13–50.0215%17 Feb →
nuke9–13-0.1021%17 Feb →
train13–9-0.019%17 Feb →
ancient13–100.0124%16 Feb →
anubis13–11-0.0218%15 Feb →
ancient13–10.0717%15 Feb →
anubis10–13-0.0613%15 Feb →
inferno3–13-0.0943%15 Feb →
anubis13–8-0.0023%14 Feb →
mirage7–130.0138%13 Feb →
dust215–15-0.0228%13 Feb →
anubis13–60.0628%13 Feb →
inferno6–13-0.0517%9 Feb →
inferno13–3-0.0329%6 Feb →
ancient6–13-0.0721%31 Jan →
mirage3–13-0.0427%30 Jan →
inferno8–13-0.037%24 Jan →
ancient7–130.0224%24 Jan →
anubis9–13-0.0817%24 Jan →
ancient12–16-0.0212%23 Jan →
inferno13–16-0.0023%23 Jan →
ancient11–130.0233%23 Jan →
ancient8–13-0.0418%23 Jan →
ancient10–130.0123%22 Jan →
ancient8–13-0.0221%17 Jan →
ancient13–11-0.0129%17 Jan →
inferno14–16-0.0419%16 Jan →
anubis13–90.0424%16 Jan →
ancient13–20.0223%16 Jan →
inferno16–13-0.0430%16 Jan →
inferno6–13-0.0018%16 Jan →
anubis13–8-0.0127%16 Jan →
ancient7–13-0.0120%15 Jan →
anubis17–19-0.0022%15 Jan →
dust213–11-0.0030%15 Jan →
ancient13–5-0.0518%15 Jan →
anubis13–11-0.0129%15 Jan →
ancient13–50.0219%14 Jan →
ancient10–13-0.0216%14 Jan →
ancient10–13-0.0517%14 Jan →
ancient13–110.0229%14 Jan →
anubis5–13-0.0516%14 Jan →
ancient13–7-0.0624%14 Jan →
anubis11–13-0.0325%14 Jan →
anubis13–9-0.0126%13 Jan →
ancient13–40.0432%13 Jan →
inferno13–9-0.0523%13 Jan →
inferno13–6-0.0124%13 Jan →
nuke13–16-0.0412%12 Jan →
vertigo13–100.0625%12 Jan →
anubis5–13-0.0225%12 Jan →
inferno4–13-0.0024%12 Jan →
vertigo8–13-0.0031%10 Jan →
dust213–90.0223%10 Jan →
vertigo13–11-0.0119%10 Jan →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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