Sportmonks Blogs

We’re excited to announce the release of Sportmonks’ Player Ratings! This innovative feature is set to revolutionise football analysis, providing fans, analysts, and coaches with deeper insights into player performance. Here’s everything you need to know about our new ratings system and why it’s a must-have tool for football enthusiasts. The renewed player ratings will go live at the sixth of January.

While the word fashionable or exciting comes to mind when you come across the term Groovy, in programming parlance it has somewhat of a different meaning. Apache Groovy is a powerful, optionally typed, and dynamic programming language with static typing and static compilation capabilities for the Java platform aimed at improving developer productivity.

Julia is a high-level, general-purpose, dynamic programming language designed to be fast. It is well applied in fields related to data science, artificial intelligence, and machine learning, among several others. Influenced by Python, R, and Ruby, Julia, whose development was led by the trio consisting of Jeff Bezanson, Stefan Karpinski, and Viral B. Shah, is suitable for web programming on both the server and client sides.

Sportmonks’ Football API offers developers a treasure trove of mind-blowing football-related data, ranging from team to individual stats for current and past seasons alike, among many more.

In modern football, data has become just as crucial as the action on the field. For teams, leagues, and fans alike, the journey into the world of ball tracking and ball coordinates opens up new ways to understand and experience the game. Through connected ball technology, combined with sensors and real-time data, every dribble, pass, and shot can be tracked and analyzed in incredible detail. This technology not only allows for precise insights into ball movements and player performance but also transforms how fans engage with the game. As football matches become more data-driven, video match officials and artificial intelligence have stepped in to provide accurate, live feedback on everything from shot speed to ball possession time. This article delves into the exciting innovations making professional leagues and fast-paced games more interactive, and what this means for the future of soccer.

We have now reached the point in the 2024/25 Premier League Season where early season variance is starting to balance out and underlying data is becoming more predictive and useful when it comes to assessing how teams are performing. This is typically the case once we come out of the second international break of the season and we start to move towards the end of the calendar year. This is where resources and websites like Sportsmonks really come into their own as we can use their advanced and underlying data in order to get a more solid prediction on what the Premier League is going to look like come the end of the season. Sportsmonks have their own models that allow them to calculate xG in for each team, and each player within those teams, to some depth. This xG model can then be used to create a model to calculate expected points (xPoints) for each team in the league and xPoints is often a metric that can provide accurate insights into overall team performances. In this article we will use the xPoints model from Sportsmonks to look at three of the key storylines that we can expect to see as the Premier League enters the business end of the season. This data can often provide interesting context to the matches that we are watching every weekend.

Developed by Microsoft almost two and a half decades ago, C# is a versatile and robust, powerful programming language that allows programmers to build dynamic web applications, web services, desktop, and mobile applications.

Football fans crave more than just the traditional commentary and highlights in today’s digital world. With the rise of AI technology, Sportmonks offers a transformative way to engage with football through real-time, accurate predictions. These AI-driven predictions allow fans to dive deeper into the sport, making informed decisions for fantasy leagues, betting, or simply enhancing their understanding of each match. Fans no longer watch the game; they become part of it, leveraging data that brings the game’s excitement closer than ever before. For casual viewers and seasoned fans alike, this level of interactive, data-driven engagement opens a world of new possibilities for enjoying the game. Learn more in this blog.

According to its documentation page, “Kotlin is an open-source statically typed programming language that targets the JVM, Android, JavaScript, Wasm, and Native.” Kotlin was developed by JetBrains and the project started in 2010; its first official 1.0 release was in February 2016.

Are you curious which team will most likely lift the UEFA Champions League trophy this season? Tired of relying on gut feelings and outdated stats? Imagine leveraging advanced AI and real-time data analysis to uncover actionable insights revealing each club’s potential. With Sportmonks, you can navigate the complexities of the tournament and make informed UEFA Champions League Predictions based on multiple data analyses. Join us as we explore who the favourites are and how data-driven Champions League Predictions can enhance your football experience!

Have you always dreamed of being able to predict El Clásico perfectly using real-time data? Leveraging Sportmonks data, you can gain deeper insights into player and team performances, enhancing your and your users’ match experience. With El Clásico around the corner (26th of October 2024, Fixture ID 19135354), we are looking ahead to find out what we can expect from this interesting matchup. Of course, data analytics alone can’t predict a match as emotionally charged and unpredictable as El Clásico. You can argue that the team mentality, rivalry, emotions and atmosphere are impossible to quantify in football data. And you know what? That is absolutely true. Not everything is quantifiable, and that is what makes football the beautiful game it is. However, with football data, you can give yourself and your users the chance to improve your chances of predicting the game.

Besides adding the Expected Goals statistics, we have added many more statistics to the statistics that are available in our API in the last couple of months. Haven’t you noticed them yet? No worries, we have got your back.