Wants to Score With Sports Data API has taken some aggressive steps to position itself as a market leader in sports data with the release of the NFL API. Sports data tools – already playing a crucial part in the business side of many international sports – is set to see further demand as fans expect greater access to up-to-the-minute stats and as a new raft of fan and athlete-based startups are created around international and local competitions.

The use of Big Data in sports entered popular culture with the release of Moneyball in 2003 and the subsequent movie in 2011. The story documents how big data analytics became central to a team’s competitive advantage by giving scouts more accurate information about which rookie players had the best long-term potential, and how to split player incomes to keep the best while also meeting tightened salary cap rulings.

The use of accurate athletics data has since become a massive business by-product, with partnerships like SAP and the 49ers teaming up to create player dashboards to manage NFL scouting activities (in a game where quarterbacks earn an average $3.8 million, accurately using data to pick the best of the best can make sure those salaries are an investment for the team).

Meanwhile IBM have worked with the French Open to develop data tools that document player’s match performance, based on 41 years of Grand Slam data. Broadcast sports has long known the value of using data to keep fans tuned in and on the edge of their seats, and increasingly stadium’s are using data feeds to keep players focused on the game by streaming data to gameboards and to stadium-branded apps to help keep fans up to date while they are in attendance.

Sports data is set to see an even greater surge in public interest following the recent move of data analyst, Nate Silver to ESPN. Silver captured public attention with a regular blog for the New York Times on election data which he used to analyze in-depth and make accurate predictions about recent US elections. While planning to continue to unpack big data for political predictions, Silver’s mandate at ESPN will expand to allow him to talk about sports data. Silver’s early mathematical career involved creating a predictive modelling tool for major league baseball to assist with fantasy football gaming, a similar model to’s approach. is targeting their data feeds to the fantasy football market, with a range of products aimed at providing detailed real-time data to fantasy football websites and add-on products. 2013 data products available via the API include team and player stats, scores and rankings, injuries data, news and updated rosters. Packages allow for levels of data access and speed of updates, ranging from post-game updates to almost-real time data (available after a 30 second delay).

Data can be returned in JSON or XML format and sample datasets are available for developers to use when testing application prototypes.

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