CURSD's answer:

CURSD is the only platform that ranks teams across 9 professional sportsleagues using a single composite luck metric. Instead of just showing xG or Pythagorean wins in isolation, the CURSD Score combines up to 7 signals per sport (expected goals, Pythagorean expectation, finishing variance, shot quality, close-game record, injury burden, schedule strength) into one number that tells you exactly how much luck has shaped a team's season. The site also auto-generates a new data-driven article every day and publishes a CURSD Match Report after every Premier League game.

CURSD's answer:

Next.js 16 (App Router), TypeScript, Tailwind CSS, Recharts for data visualization, Vercel for hosting, GitHub Actions for automated data scraping and article generation, Anthropic Claude API for AI-powered content, API-Football for soccer data, ESPN/NHL/MLB official APIs for US sports, and Baseball Savant for Statcast data.

CURSD's answer:

• Sports fans tracking luck across Premier League, La Liga, Serie A, Bundesliga, Ligue 1, NBA, NHL, and MLB
  • Fantasy sports players using the CURSD Score to identify regression candidates
  • Sports analytics enthusiasts comparing luck signals across leagues
  • Bettors looking for data on which teams are overperforming or underperforming their underlying numbers

CURSD's answer:

Sites like FBref and Understat show raw xG data for individual leagues. CURSD goes further: it synthesizes multiple luck signals into one cross-sport score, covers 9 leagues in one place (soccer, NBA, NHL, MLB), and frames the analysis around a question fans actually care about: is my team unlucky, or are they just bad? The daily articles and match reports add narrative context that pure stats sites don't provide.

CURSD's answer:

Sports fans who care about the "why" behind results, not just the scoreboard. Fantasy sports players looking for regression candidates. Sports bettors who want to identify teams the market is overvaluing or undervaluing. Data-curious fans of Premier League, La Liga, Serie A, NBA, NHL, and MLB who want one place to check how much luck is affecting the standings.

CURSD's answer:

I kept noticing teams that dominated matches on every underlying metric but kept losing. The data said one thing, the scoreboard said another. I wanted a single number that captured that gap across every sport I follow. So I built CURSD as a side project, starting with the Premier League and expanding to 9 leagues. The daily article pipeline came from wanting the site to stay fresh without manual effort, so I automated the entire content production using Claude's API.