Football software provides TV viewers with real-time CGI match analysis
Image credit: University of Konstanz
Computer scientists from the University of Konstanz have developed software which automatically analyses football matches up to 30 times per second and can display decisive diagrams during live matches.
The software can highlight areas of team dominance on the pitch as well as passing options in real time.
It can also indicate the level of pressure experienced by individual players and can even run what-if scenarios of alternative match-play variations.
Lead researcher Manuel Stein said the software will allow viewers to see the patterns of the game – the interactions between players and entire teams as well as the influence they exert on one another.
“Everyone in football tries to collect data, but few know what to do with it. We are trying to generate knowledge from this data,” he said.
To turn a computer into a match-play analyst, Stein taught it some basic facts about football such as who the players on screen are and how to recognise the location of the ball.
He also taught it to recognise the direction that individual players are facing, how fast they are moving and how quickly are they likely to reach the ball.
The software is able to determine the position, speed and movement direction of every individual player and of the ball up to 30 times per second.
Based on these measurements, it then calculates which player can reach any square metre of the pitch first and how many players from each team pose a threat to that part of the field.
It takes less than a fraction of a second to superimpose the results of this calculation on the TV screen: a dynamic, constantly changing map of each team’s zones of influence.
Using simple colour cues, Stein’s software is able to show TV viewers such match-play influencing factors such as the level of pressure opposing teams place on individual players, the free spaces and safe passing lanes.
For all of this, the software only needs the TV capture; complicated GPS trackers attached to the players’ shirts or camera-tracking technology are not needed.
All of these hues on the TV screen can make for a very colourful football pitch. To prevent confusion, the software’s various analysis features can be switched on and off as needed and stacked as filters.
Furthermore, the software makes suggestions as to which filters to use in any given situation and can switch them on or off as desired to reduce unnecessary visual clutter.
However, it is not primarily the viewers at home that the software has been developed for. Its real target groups are football analysts and sport reporters. The software allows them to create diagrams of match-play situations within a fraction of a second and to broadcast them in real-time.
Stein is currently developing a “what-if” analysis – a forecast of how the match play would have evolved under different circumstances – that is based on his software.
Here, key match-play situations can be accessed and replayed using alternative scenarios. Based on the individual players’ location data and influence factors, the computer calculates a coherent, realistic course of events.
The system can estimate, for example, what would have happened if a player had passed the ball to the right rather than the left and how the dynamics of the game would have changed if a defender had stood five more metres to the right.
The more data the software has access to, the more precisely it can evaluate the situation on the pitch. However, currently the information it can use is limited to that on the TV screen and it does not know what happens outside the camera’s field of vision and can only make vague predictions.
Ultimately the research team hopes to be able to work with teams and broadcasters who record images and player location data during football games.
If they provide the researchers with access to this information, they can, in turn, deliver more precise analyses.
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