Data analysis is becoming fairly prominent in modern football. You only have to look at Manchester City’s recent Opta Initiative as proof to how much of an integral role data analysis is playing in terms of how football is played today.
Prozone is one of the most commonly used resources for data analysis in football, with 15 out of 20 current Barclays Premier League squads using it and over 100 sporting teams using the analytical service worldwide. The service primarily focuses on the following coaching progress: Live Analysis, Post-Match Analysis, Trend Analysis and Opposition Analysis.
Now while the service that Prozone provides is traditionally aimed at the sporting industry as most people know it (Football, Rugby etc.), the above coaching progress could very easily be applied to a very different type of “sport”: eSports.
“eSports”, which concerns the competitive play of video games, is more popular than it’s ever been, with dozens of different leagues and tournaments all over the world, concerning all different types of genre of video game from FPS to MMORPGs, even FIFA has been a part of the World Cyber Games since its beginning in the year 2000. While there’s many different genre of games that are played in eSports, for the purposes of this blog, let’s examine how Prozones methods could play out in an FPS like Halo.
First, we look towards how the Live Analysis function would play out. Prozone’s Live Analysis provides an insight into the performance on the players on the pitch. It allows its users to review key events as they play out in real time and monitor the performance of individual players and the team’s units as the match progresses. As to how this service could play out in eSports with a game like Halo, it could just as easily be converted to giving an insight as to how each individual virtual player on a team is performing, which player has the strongest kill-death ratio? who’s the most accurate shooter? how long has the team held the lead for,? or if it’s a game mode like Capture the Flag, who has held the flag the longest? who has attempted to get the flag the most? who has protected it the most?.
Secondly, we examine how the Post Match Analysis function would be used for an eSports team. This analyses every aspect of the performance once the match is over, it also assess both the players and the team from either single game or multiple game. To place this in the eSports context, it could serve as means of providing an overall report of how the team as a whole performed against their opponents, how consistent they have been with their wins in terms of using it over the course of a few games? who is consistently playing the game well and who the weaker players are?. It can also help the teams understand which game mode suits their playing style better if the modes are alternated between matches; is the eSports team more effective in Slayer than they do in other modes?. This service can be easily used to help an eSports team to get a better understanding of what is working and what isn’t working in their current strategies.
Thirdly, we will look at how the Trend Analysis feature would work in an eSports setting. This is basically a much more specific examination of what works and what doesn’t whilst also looking at what style of play is being utilized by the team the most and what each individual player does more than anything else. With eSports this could be used in determining what weapons are selected the most frequently? what perks are picked the most frequently?; which player is using the armor lock perk the most? who is using the jetpack perk the most? and more importantly, are these choices of perks working for that individual player? Is there something better they could be using to improve the team overall?.
Finally we look at how the Opposition Analysis could be used in eSports. Prozone uses its Opposition Analysis feature to identify upcoming opponents strengths and weaknesses, therefore informing management and coaches of their tactical decisions as well as improving the preparation of their team. This would be directly applicable to its possible use in eSports, helping teams figure out what areas of the game their future opponents are strongest and weakest at, so for example, do they hold their leads longer than you do? What types of weapons are they using? Are they better with them than you are? Which game modes do they play better in? Do they kill spawn? Do they camp?. In many sense, Opposition Analysis covers the first three areas just applied to opponents instead of your team.
While there are options available for Data Analysis such as eSports Scout, they are currently very basic and are limited in the amount which are available to use. They are nowhere near as refined and as evolved as services like Prozone. If such precise level of service was made available, Data Analysis could become as much of an integral part in eSports as it is in football today.
So as for asking the question of could Prozone’s methods of data analysis be applied into eSports, the above statements suggest that the data that would be collected wouldn’t be too far away from the player in the real world and the player in the virtual world.
This guest blog by Ryan Edwards (PR intern) – Ryan is a former International Journalism student from Liverpool John Moores University, with a working background in PR and Marketing. *All views are his own.