Miscreants use domain names for malicious purposes such as phishing websites or fake webshops. Reactive approaches such as blocklists play an important role in fighting such abuse but have limitations, namely that the domains are typically only included in such a list after abuse has been reported (e.g., there may already be some victims). We propose RegCheck, a system designed to proactively flag suspicious domains at registration time. The core of RegCheck is a machine learning classifier that assesses the risk that the domain name will be used for malicious purposes based on characteristics known at the time of registration. Based on this assessment, it flags some registrations and requires them to undergo additional verification prior to the domain name being activated. The system has been developed collaboratively between SIDN (.nl) and DNS Belgium (.be) and has been deployed as a real-time system at the .be registry since March 2024. Since its deployment, the registry has witnessed a decrease in the number of .be domain name registrations that have been revoked for breaching the terms and conditions, indicating a decline in the number of active malicious registrations.

Creativity is highly valued in soccer players. It contributes to exciting and unpredictable play, which can help teams to overcome defensive strategies and create scoring opportunities. Consequently, evaluating the creative abilities of players is an important aspect of the player recruitment process. However, there is currently no clear way to measure creativity in soccer. It is not captured by the typical result-based performance indicators, as being creative entails going beyond just doing something useful, to accomplishing something useful but in a unique or atypical way. Therefore in this paper, we define a novel metric to quantify the level of creativity involved in a player's passes. Our Creative Decision Rating (CDR) utilizes machine learning techniques to assess two important factors: the originality of a pass, and its value in terms of increasing the team's chances of scoring a goal. We validated our metric on StatsBomb 360 contextual event stream data of the 2021/22 English Premier League season and show through a number of use cases that it provides another angle on a player's skill, complementing existing player evaluation metrics. Overall, our metric provides a concise method for capturing and quantifying the creativity of soccer players and could have important implications for player recruitment and talent development in the sport.

In-game win probability models, which provide a sports team's likelihood of winning at each point in a game based on historical observations, are becoming increasingly popular. In baseball, basketball and American football, they have become important tools to enhance fan experience, to evaluate in-game decision-making, and to inform coaching decisions. While equally relevant in soccer, the adoption of these models is held back by technical challenges arising from the low-scoring nature of the sport.