Data for Sports makes sports data accessible, understandable, and useful.
Last updated: October 24, 2026Data for Sports (DFS) is an American software company that provides access to sports data and analytics software. We develop statistical tools and predictive models to visualize, analyze, and forecast sports performance, and over time, to power applications built on sports data. DFS is headquartered in Los Angeles, California, and is operated by Polystack Digital LLC.
We started Data for Sports because the people who care most about the numbers have to work the hardest to use them. Sports fans, fantasy players, and independent analysts cross-reference stats across three, four, or five disconnected sites, build their own charts to spot a trend, and interpret raw numbers with no plain-language context. Their options tend to be either too shallow, like headline box scores, or too technical, like raw APIs and spreadsheets. The problem isn't that the data doesn't exist. It's that the data is scattered, the deepest insight is gated, and the numbers still have to be interpreted by hand.
Data for Sports brings that work into one place. Interactive charts and trend lines replace raw tables, so any stat can be compared against a benchmark like a season average, recent form, or a projection. AI-generated summaries explain what a stat line actually means, and natural-language queries let you ask questions instead of navigating filters. Our predictive models forecast player performance against a benchmark and explain why the model favors an outcome, so every projection comes with its reasoning, not just a number. We are also building customizable visualizations, user-built models, and an API so others can build on sports data.
We hold ourselves to a few principles. Clarity comes before volume: we surface the numbers that matter for a decision and explain them in plain language. Forecasts show their work, with likely ranges and the factors behind them, and we are building a public record of every prediction and how it turned out. And we are deliberately sports data and analytics software, not a betting product. We don't publish picks, locks, or odds, and we don't monetize the betting market. Our tools exist to help people understand the game.
Making sports data accessible, understandable, and useful is the mission behind everything we build. We cover multiple sports today and continue to add more, and we are working toward a future where anyone who studies the game, from the casual fan to the independent analyst, has the full picture in one place.
We started Data for Sports because the people who care most about the numbers have to work the hardest to use them. Sports fans, fantasy players, and independent analysts cross-reference stats across three, four, or five disconnected sites, build their own charts to spot a trend, and interpret raw numbers with no plain-language context. Their options tend to be either too shallow, like headline box scores, or too technical, like raw APIs and spreadsheets. The problem isn't that the data doesn't exist. It's that the data is scattered, the deepest insight is gated, and the numbers still have to be interpreted by hand.
Data for Sports brings that work into one place. Interactive charts and trend lines replace raw tables, so any stat can be compared against a benchmark like a season average, recent form, or a projection. AI-generated summaries explain what a stat line actually means, and natural-language queries let you ask questions instead of navigating filters. Our predictive models forecast player performance against a benchmark and explain why the model favors an outcome, so every projection comes with its reasoning, not just a number. We are also building customizable visualizations, user-built models, and an API so others can build on sports data.
We hold ourselves to a few principles. Clarity comes before volume: we surface the numbers that matter for a decision and explain them in plain language. Forecasts show their work, with likely ranges and the factors behind them, and we are building a public record of every prediction and how it turned out. And we are deliberately sports data and analytics software, not a betting product. We don't publish picks, locks, or odds, and we don't monetize the betting market. Our tools exist to help people understand the game.
Making sports data accessible, understandable, and useful is the mission behind everything we build. We cover multiple sports today and continue to add more, and we are working toward a future where anyone who studies the game, from the casual fan to the independent analyst, has the full picture in one place.
Thank you.