In October, Chelsea FC traveled the short distance across London to face a West Ham side in the midst of a revival after a dreadful start to the English Premier League campaign. The good form continued as goals from Cheikhou Kouyaté and Edimilson Fernandes sent Antonio Conte’s Chelsea side crashing out of the EFL Cup at the Olympic Stadium. The win was a significant one for under pressure West Ham manager Slaven Bilic but, unfortunately for the Croatian, all the noise around the game has been dominated by events off the pitch.
The violence that erupted between the West Ham and Chelsea fans was at once both shocking and tediously predictable. Such London derbies all too often end in violence, and as both punches and missiles were thrown, the conversation turned to whether or not the Olympic Stadium was fit to host games at all. A number of games have seen violence in the stands since the club moved in the summer, and measures like restricting alcohol in the stadium has done little to curb the issue.
This is where analytics can help. Algorithms for video analytics have significantly improved, and companies can now apply crowd control technology to a variety of different arena types, identifying possible risks and mitigating the issues that come with large potentially unruly crowds.
One of the major issues in Chelsea’s clash with West Ham was the layout of the stadium and the herding of the support. 5,182 Chelsea fans were funnelled through a narrow entrance of just eight turnstiles, some feared a crush could happen and the mood turned sour before a ball was even kicked. The Olympic stadium is an example of a stadium in which it’s difficult to separate the opposing sets of fans entirely, but a more developed approach to crowd flow could’ve calmed the crowd early on.
Sensory equipment and proper video analysis can be used to identify bottlenecks and congested areas by looking at crowding in the past as an indicator of future issues. Stadiums can position staff and allocate resources accordingly, predicting where crowding may occur and at what times, rather than using guesswork or simply being reactive. This kind of data collection allows for testing, too; stadium staff will be able to experiment with different arrangements of stewards and different funnelling strategies, for example, whilst being able to see the effects of the changes
If violence can’t be avoided, though, the use of facial recognition technology could help identify those perpetrating it. Software produced by companies like Herta Security utilizes data from multiple security cameras, detecting faces in real-time across the different cameras to build a picture of the person’s journey. West Ham, for example, has promised to issue lifetime bans to anyone they find guilty of inciting violence in the stadium, a lengthy process without the use of technology to speed things along. As well as identifying those involved after the event, the presence of facial recognition technology could act as a deterrent to future problems. Lifetime stadium bans are not something serious football fans would take lightly, and perhaps awareness of sophisticated identification technology would be enough to keep some fans from engaging.
The issue of crowd control is a thorny one, not least because mistakes so often mean injuries and even deaths. The London Stadium isn’t the first to see crowd violence and it won’t be the last, divisions between fans will always exist. What analytics allows for, though, is a more proactive and less reactive stance on crowd flow, violence, and bottlenecking. Chelsea’s clash with West Ham saw some decent football, but the violence in the stands mars the events on the pitch - if analytics can help smooth the policing in stadiums across sports, it should be embraced as quickly as possible.