by Infogr.am
Create infographics

Big Data and Sports, by Marco Giannini

The rising role of Big Data is enlarging the gap between professional and semi-professional/amateur sports

October 4, 2016

[This is a guest post by Marco Giannini, originally published in the Italian website Sentiero Digitale]

 

 

1a-Dellavecova[1]
Matthew Dellavedova, Cleveland Cavaliers’ reserve playmaker, took to the field against the Brooklyn Nets on March 31st, 2016 without carrying his fabric and plastic Whoop branded bracelet, like he was used to do till that time.

The match was truly unimportant, as the Cavs yet qualified for the playoffs while the Nets (among the worst Nba teams this year) were already with their mind in the off-season. Dellavedova wasn’t at his best: he shot 0/6 in 18 minutes. But the bracelet tale is much more interesting.

The Whoop wristband is designed to record the heart rate, body temperature and body movements during the game (or even while sleeping or in the shower, why not). It resembles the popular Fitbit or Jawbone, but is produced just thinking to professionals, because it add to these usual data other than an ordinary amateur tracker cannot reveal: environmental temperature and humidity, pulmonary and cardiac recovery factors and so forth. The Nba league has banned it precisely in March after being informed that Dellavedova and other teammates (including the most celebrated player, Lebron James) used it continuously; officially the prohibition has arrived for safety reasons (no rigid part can be worn during the game), actually it is one of the so far not very numerous reactions to technology intrusiveness by the professional sports system, which has need to preserve its aura, based on the concept of competition on equal terms.

In training, the use of motion capture equipment and biometrics is now widespread (19 out of 30 teams in the NBA): the most common is the acceleratometer Catapult, tough it’s prohibited by the NBA board in official games. Its peculiarity is to be equipped with a precise GPS device that records the player’s position by the millimeter, and therefore also the NFL (professional league footbal) forbade it during games.

However, if you leave the ranks of the self-tracking devices and approach the technology related to television coverage, Big data takes the bigger role: as for the US professional basketball, several Internet sites provide beautifully displayed statistics of NBA players, like Buckets by Peter Bershai, which offers comprehensive data related to shooting position and percentages, duration in minutes, rebounds, assists, fouls and so forth along one or more of the last five seasons, for every player in the league.

(image: Buckets)
(image: Buckets)

Another valuable application is Ballr, developed by Todd Schweinder. It compares the scoring percentages of each player in the current season with the rivals’, and the entire league, average.

(image: BallR)
(image: BallR)

Obviously the massive use of bigdata has a reflection on the evaluation of the players themselves (for example in the current market phase), their behavior on the field (stars work hard to improve their statistics in order to obtain better advertising contracts) and even on the lucrative world of sports betting (where you can bet on who will win the best scorer title, or who will have the highest percentage, and so on).

And within the balancing mechanisms of the NBA, the Bigdata comes to help the talent scouts who follow young player from high school or earlier, pushing them to reward the birth of new stars regardless of the quality of the team that will play in (on which those youngsters can influence for good or bad), as this article from the Atlantic tells us.

Like basketball, tennis is heavily exploited by the technology applied to television coverage, starting with the fact that the playing field in each major tournament circuit is now surrounded by cameras. From takes to analysis and visualization the jump is short.

(image: Damien Saunder)

It suggests the idea an analysis system proposed by date analyst Damien Saunder, based on the HawkEye filming technology, and working also with Telemetrics software directly applied to television coverage. The depth of results and the possibility of automation is amazing, the system is totally open source (while HawkEye is a unique tool in the possession of ATP) and easily usable by sports networks.

5a-Campo-tennis[1]

The real-time information can thus return directly from the window from which came out: the network that broadcasts a game now has more tools available to support the commentary, based on accurate statistics.

5-Nadal-grafico[1]

Even across tennis courts the extensive use of statistics joins another kind of technological innovation, especially in the tracking performance; Rafa Nadal has been the first professional player to install a GPS device directly in the racket, and the ATP agreed, probably convinced that Nadal was until a few years ago the strongest tennis player in circulation..

(photo: AP)

In training the GPS device assists him in controlling and improving his shots, but its use has yet to be fully regulated: an outrageous distance in their ability to spend is likely to dig a unbridgeable gap between the champ that invests a lot of money in technology and the lower and middle-ranking professional who looks out on the world stage. Is this the dawn of a sort of “technological doping”, the prerogative of stars and tolerated by the professional leagues, which combines the traditional doping (chemist and now even surgery).

Another sensitive point is the increasing predictability of sports events, regarding betting. An application related to the search engine Bing (Microsoft) was used in 2015 to predict the results of all the knockout rounds in the European soccer Champions League: apart from a few surprises (Juventus defeated Real Madrid thanks to an unexpected score by Morata, but Bing had predicted the victory de los Merengues), the analysis based on Telemetrics have always hit the mark. Although in fact here the technological aid gives the speech a steep turn toward machine learning (a whole other can of worms and visualizations), the use of technology in pro football analysis is spreading especially in championships with higher value in terms of bets, such as the Premier League: in 2014 Arsenal FC spent millions to equip their pitch with a modern camera system and patented software analytics.

Implications come to be, in short, bulky enough to pour out the pure sportsphere, and maybe that’s the sport that, as many think, should stay out of great speeches. The fact is that – to paraphrase the Italian writer Galimberti – when ethics chases (laboriously) technology, it becomes pathetic, losing the supreme role we all grant to it. And ethics brings with it sports, in a land where the initial conditions are not the same for everyone, participants and spectators.

 

Marco Giannini works as Infographic editor for the Italian newspaper La Repubblica, in parallel with his freelancing for clients all over the worrld. You can see his work right here on Visualoop, as well as on Flickr.

Written by Tiago Veloso

Tiago Veloso is the founder and editor of Visualoop and Visualoop Brasil . He is Portuguese, currently based in Bonito, Brazil.

Follow: