AI With the Assist..

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Data is everywhere, and with data being so prevalent in all aspects of the world, it was only a matter of time that data, along with machine learning and artificial intelligence, would help basketball players hone their skills and better their game. The new technologies can specifically help players improve their shooting, as well as help coaches draw up plays for their team.

Noah Basketball

One major technology that is aiding basketball players is Noah Basketball. It tracks shots as well as produces data on those shots, which help improve both player and team shooting statistics. It gives players data on their shot — such as the arc and trajectory of their shot — and gives coaches access to data that allows them to figure out from where, how often and how well their players shoot on the court. The newest version of this technology, which includes tool to help analyze the data is called Noahlytics, and is being used by NBA teams, top college programs, as well as hundreds of individuals.

Their system consists of cameras attached above the backboard that track the ball’s arc as well as the depth and left-right position as it approaches the rim. This system gathers data on every single shot, adding it to a database of more than 150 million shots already collected. This data is so important for machine learning algorithms that are being incorporated into the newer systems. For example, the next version that is set to come out, has facial recognition which can track shots from multiple shooters at the same time. This allows the system to collect the data and analyze it from team practice sessions.

With all the data on how shots are being made, a player’s shot and skill are more efficiently evaluated. Usually, coaches and scouts evaluate shooting ability on how many shots are taken and made during a workout, which means that the more shots taken, the better the player can be assessed. However, Rachel Marty, the daughter of Alan Marty — founder of Noah Basketball in 2001 — trained an algorithm to recognize the characteristics of a made shot so that a player can be assessed without taking thousands of shots. It is made to predict a player’s skill based on the few shots that were taken. By analyzing this data, this aspect of Noahlytics can provide accurate information on the player’s ability.

Big Data Jobs

Stats

Stats, a sports company, was actually the first company to install camera systems in NBA arenas. These cameras track not only the basketball, but the players movements and body positions as well. More than just on the basketball and the shot taken/made, the software analyzes the players and simulates how a team would respond to a certain play. The deep learning algorithm of this system takes the five individual players on a team and represents them as one entity. This program, which is still in development, allows a coach to draw up a play and see how the opponent team might defend it. It also accounts for different teams’ differences in players and play style.

Another technology similar, and also still in development, does almost the same thing as Stats. It allows a coach to sketch a play on the computer and an AI program trained with player movement from the NBA converts these sketches into simulation of how both teams would move and position themselves during the play.

ShotTracker

ShotTracker is another firm that uses technology for basketball analyses. This one also cool because it gathers data in real time. It is a sensor-based system that captures stats and performance analytics for an entire team in real time. It uses electronic sensors installed in an arena, that can map the court in 3D. While a basketball is being played, ShotTracker gathers data using real time movement of both the ball and the players.

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The firm says that its technology can allow coaches to make adjustments based on games that are going on at that moment. They could implement these changes during any time out or during half time. This technology could help coaches see areas on court where their team is shooting well and where they are not. A team can also easily determine where it is getting pounded by defense.

Conclusion

Machine learning and artificial intelligence with deep learning algorithms allow for some of the most innovative technologies for gathering basketball data and analyzing it. As mentioned above, some of the companies involved include Noah Basketball, Stats, and ShotTracker. With implementation of these programs and systems, the level of basketball analyses is exponentially improved to help players, coaches, and teams be better prepared and to succeed.

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