Taka is a sports technology and analytics company based in the UK and Northern Ireland with the majority of their operations happening between London and Belfast.
They currently mainly support worldwide grass roots football teams and youth football including players, coaches, clubs and college scouts/recruiters rather than elite clubs however are looking to expand into being a multi sport platform, supporting sports such as rugby.
I spoke to Pujith, a Senior Product Designer at Taka who talked me through their current software, how AI has changed the way they analyse player data and where he sees it going in the future.
Pujith told me about their main 3 product users: Player, Coaches and Recruiters. He described one of their main features as a linked in style platform that allows players to input information about themselves such as their name, team, nationality, height, preferred position, dominant foot etc. They can then share this information with their coaches or with recruiters.
Using their video section, Taka collects all their match play highlights such as passes, shots etc. in a personal profile allowing players to watch, download or share with others as well as look back at their match play for either enjoyment or to analyse how they could improve.
They also provide players with individual development plans, personal content feeds and opposition analysis features to help further improve their game. Players are able to use filters to search through their match play and the system highlights to them what they did do well on the pitch as well as negative contributions on the pitch.
Similarly to players, coaches can use the same platform at a team level set up to analyse and see all the players in their squad, their positive contributions to the match both on and off the ball as well as negative areas that each player could improve on. This helps coaches to understand the each players and the teams style of play and how the team build up on the pitch.
He also touched briefly on how recruiters can use this platform to search up either specific players or search for players that fit a specific gap needed in a team such as a defender, winger etc or look for players who show specific qualities and attributes on the pitch.
Taka are one of the first football analysis platforms to analyse the significance of players actions on the pitch rather than basing their analysis on facts and figures or purely number like other platforms. They use the pitch data collected in each match to point out players positive and negative actions on the pitch that happen both on and off the ball.
They can also look at a number of previous matches individually to see the consistency of this player and their actions. An example Pujith gave me was that a player who had very little touches but they were all positive actions such as a successful through ball or scoring a goal would have a better player rating than a player who had lots of touches but a lot of them were negative. This differs to other platforms who base their player rankings based on possession stats.
There is the ability to filter to specific skills or actions that they want to see!
Currently as AI is still upcoming and new and therefore Taka still continue to use traditional analysis for now. They are using Watcher Network, a platform with large number of professionally trained scouts and analysts who manually go through the match footage, analysing each player contribution to the game as well as positive involvement/actions and negative involvement/ actions and their skills.
https://youtu.be/njHxWZYwfho?si=vhq_YydiVGChGXa0
They also analyse players off the ball actions such as making the runs and how this impacts the game. They also manually mark each players positive and negative action positions on a pitch view diagram to show where their best contributions were and if there is any dangerous areas they are making bad ones eg. in front of their goal.
Taka are currently integrating artificial intelligence and developing AI-driven player tracking software which uses computer vision to analyse the clips and pinpoint each players and referee on the pitch as well as differentiate between the two teams on the pitch and each player. This is done by highlighting the player it is analysing with a red box around them. This software is able to understand each players action on the pitch both on and off the ball whether that is a pass, shot on goal or making a run. One of the concerns was the loss of jobs for those who previously manually reviewed this footage however their role now shifts to reviewing the output provided by AI, ensuring it is providing correct and reliable outcomes for players and staff. Pujith expressed how this shift from manual analysis to AI analysis really speeds up the whole process allowing players and coaches to access this information much faster post match as well as being available before the next match.
Another AI tool currently underdevelopment at TAKA is “Assistant Coach”, a new AI platform which looks quite like a standard chatbot currently. Pujith expressed how players, coaches and analysts found using the filters on the athletes page to find specific players or players who match specific attributes was really hard as you were still provided with many options and the top option not always being the best option for that coach or recruiter.
Their new platform uses GenAI to allow coaches to input what specific player or find players who have a specific attribute they want to find and quickly receive a response with accurate data. This is obviously a lot faster than their current solution of having to manually search through each player as the AI Platform can quickly sift through hundred of player profiles and video footage to recognise a specific player or a coaches needs.