Innovative technological devices are not well known in sports’ audience. However, some European clubs use them to succeed as better results as possible. Not only for injury restoration cases, but also for performance development. Footbonaut is a distinguished example of the technological progress in the 21st century’s soccer industry.
Footbonaut is a training system invented and designed by Christian Güttler in Berlin, Germany (The Economist, 2015). It is a training machine which boost player’s first touch with the ball and their instant reactions – a 14-meter four-sided robotic cage which is used for improving the passing ability and the spatial awareness of a player. The player stands in the middle of a circle surrounded by 72 panels – 8 of which spit out balls to various heights, speeds and spins, while the other 64 are grids-targets. The machine is monitored by an application from coach’s smart phone or tablet.
When the player receives the ball, he has the right to make only one touch either with the foot or with the chest. At the same time, the target is identified by the lighting up of the panel around each grid. The grids are placed in 2 different heights, just like the three kinds of passes (short, long). After the ball touch, the player must aim the right grid directly. The speed of the pass and the time of reaction are also taken into consideration.
One session of the Footbonaut it is equivalent of one week of passing training (New York Times, 2013). The Footbonaut can be filled with up to 200 balls per session. It can change the game perception, the speed of thought and/or the choices of a player in a very effective way. The training results are calculated on the spot by the application and the coach creates a valuable database in his mobile device which he can incorporate into the training or manage it in countless different ways. The cost starts from $2.4 million and comes to $3.5 million, depending on including features.
Footbonaut was specifically designed for Borussia Dortmund back in 2012. The BVB had already clinched the Bundesliga title in back-to-back seasons, by winning the double for the first time. Nevertheless, the poor performance in the group stage of UEFA Champions League, was a shocking experience. The team had not only the worst offense and defense but also was statistically the worst team in passes in its group. The players had tried the fewest passes (1,527) with the worst accuracy (79 %). It was considered as the ‘long-ball’ team of the group, because the long passes constituted the 12% of the overall passes. The 1,527 passes were less than half of Barcelona’s total passes. (Daily Mail, 2012).
The use of Footbonaut is thought as one of the major factors for which the club, from the last place in the group stage, reached the UEFA Champions League final a year later by having one of the lowest budgets in the competition. It may have not won the trophy or the Bundesliga since then, but it is almost every year the runner-up in Germany and ranked 9th in UEFA’s Club Ranking with 85.000 points (UEFA, 2017).
Since 2014, TSG Hoffenheim has become the 2nd club that have been introduced to this innovative technology. The results are irrefutable. From the 16th place and the relegation play-offs, in 2013, Hoffenheim managed to be qualified for the Champions League by finishing in the 4th place, in 2017, for its first participation ever in a European Competition. Right now, it is ranked in the 125th place of UEFA’s Club Ranking with 12.685 points, the highest in its history (UEFA, 2017).
At this point, it is essential to mention that, in the 2014 World Cup final, the winning goal of Germany came from a simulation of Footbonaut. The scorer, Mario Götze, controlled a cross with his chest and volleyed the ball into the net with an exact replica of the training the machine provided. It was “one fluid, instant motion”, a successfully fulfilled plan to defeat randomness. (The Economist, 2015).
The main categories in which the players show their improvement are the pass accuracy, the key-passes per match and the annual assist production. By choosing random players, with at least 20 matches per season, in different positions on the field both from Dortmund and Hoffenheim, the individual progress will become clearly discernible. The stats has to be divided in two different periods, before the Footbonaut practice and after that.
Dortmund players started practicing with Footbonaut during 2012. It is assumed that a Central Defender (CD) has to secure his passes in front of the box area, so Hummels’ pass percentage was not high enough before the Footbonaut practice. Besides, Lewandowski was giving the ball to the opponent once per three attempts. Gündoğan and Götze’s numbers were more than sufficient for a Central Middlefielder (CM) and for an Attacking Middlefielder (AM) respectively. The stats above show that these players have better pass percentage after the new training method. The average improvement of all reaches +7.35% and the players with considerable passing abilities (Gündoğan & Götze) increased their pass percentage in top class standards.
Hoffenheim players started practicing with Footbonaut in 2014. In comparison with Dortmund players, the pass percentage of Sebastian Rudy (DM), Roberto Firmino (FW), Tobias Strobl (CD) and Niklas Süle (CD) was high enough, especially for Hoffenheim’s standards, even before the Footbonaut practice. Except for Ruddy, who has remained stable, all the others have improved, more or less, their pass percentage after the Footbonaut practice. Though, the overall average improvement reaches +2.25%, which is hardly considered as an important increase.
Subsequently, in the key-passes graph, the stats show that the only player of Dortmund who enjoyed benefits from Footbonaut was Lewandowski. Hummels did not improved his accuracy, when Gündoğan and Götze’s stats felt backwards. On the contrary, Hoffenheim’s players have remarkable progress. Rudy improved 30.45% his key-passes per match, Firmino 20.85%, Strobl 23.30% and Süle 270%. Maybe for Strobl and Süle these number are not significant because they are both CD, but for Rudy and Firmino, who are operated in the front part of the field, are.
The assist per season stats are usually the least important because the assist counts when a key-pass turns into goal, which means that a player has to count on his teammate’s scoring ability. Nonetheless, the findings are very interesting. The progress that the Dortmund players had in this statistical category was steadily upward, except for Götze. Not the same for Hoffenheim players, except for Firmino who almost have doubled his annual assist number. The results did not show any commendable progress for the other three of them.
Although the stats in the graphs are on the rise in both cases, the statistical significance has to be validated scientifically. For this reason, the t-test method will be used in this research in order to extract safe scientific conclusions. The t-test (also called Student’s T-Test) compares two averages (means) and estimates if they differ statistically. The t-test also explains how significant the difference is, if they could have happened by chance or not. During this scientific process, the two-tailed unequal variance of the players’ samples, before and after the Footbonaut practice, will be compared so as the p-value can be calculated (Statistics: How to, 2016). The p-value is the evidence against a null hypothesis (Ho: m1 = m2). It is used in hypothesis testing and conduces to the approval or the rejection of a null.
For the purposes of this research, the confident level is defined in 90%. The p-value result for the pass accuracy development of Dortmund players is 0.081, which means that the confident level is 91.2%. The statistical significance is validated, so it is confirmed that Footbonaut practice had an important impact on the players’ passing performance. This does not apply to the other two main categories. The p-value result is 0.36 for the key-passes per match and 0.42 for the annual assist production. Both values are rejected as the confident level is less than 90% and the difference is not statistical significant.
Consequently, Hoffenheim’s samples were analyzed by the same value of confident level. In this case, the findings are unforeseeable. The p-value result for the pass accuracy development is 0.18 and the confident level is inevitably not significant. By the same token, Footbonaut’s influence is not imprinted in the other two main categories, too. The p-value result for the key-passes pre-match is 0.34 and for the annual assist production is 0.28, defining the results not significant.
From scientific point of view, the Footbonaut practice seems to have very little influence in the players’ development. Even though, there are two factors which have to be assumed. The first one is that this innovative training method is an individual passing practice. Each player develops himself in different rhythm than the others do. The second one is the level of competition. The t-test method proved that the progress of Hoffenheim players is not significant in key-passes and in assist per season, but it is more significant than Dortmund’s players. By realizing the initial difference of potential between Dortmund and Hoffenheim then and now, the size of progress of the second can be perceived.
Footbonaut is a very small sign that football tries to follow the technological and innovative trend, as the scientific services are being developed. There are many sectors which the scientists have to evolve for turning Footbonaut into an effective tool. A training football tool that could help both the clubs and the players to be improved through edifying and alternative work, by leading to beneficial results for all sides.
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