Football Line-Ups

Football Line-Ups

    In football, the line-up refers to how the players are positioned on the field before the game begins. The team’s coach determines the line-up based on various factors such as the players’ strengths, opponent’s weaknesses, and game strategy. The line-up consists of the starting players and substitutes who may come in during the game. The most common line-up formation is 4-3-3, which has four defenders, three midfielders, and three forwards. However, some teams may opt for different formations depending on their playing style and the opponent they are facing. The line-up is critical to a team’s success as it can dictate the outcome of the game.


    Artificial intelligence (AI) has revolutionized the way we approach various industries and fields. Football is no exception, as AI has aided in recognizing players’ names in the line-up for matches. With advanced deep learning algorithms and machine learning techniques, AI systems can analyze textual and image data and extract player names from various sources.

    About Our Client

    Eastgate Software is thrilled to have had the opportunity to work with a sport organization in Israel in 2021. As a company that specializes in providing cutting-edge software solutions, we are proud to be working alongside a client that prioritizes innovation and excellence in the sports industry. Our engagement with this organization represents a significant step in our continued efforts to expand our global reach and partner with clients that share our values. We look forward to building a long-lasting relationship with this client and contributing to the success of their endeavors.

    Business Need

    Our team was tasked with developing an artificial intelligence model capable of identifying the names of players listed in both starting and substitute positions within a football lineup. The model had to work with a variety of data sources and be able to accurately recognize the players’ names regardless of their font or image format. In order to do this, we needed to construct an OCR model that could extract features from the data and identify the relevant people in each game’s lineup.

    Our Approach & The Solution

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