Behind every success, there is so much underground work. The ability to be able to learn from mistakes, make the right decision, work on the critics and come back strongly brings the success story to limelight.
Sports analytics is a very powerful area of every sport and since its emergence, the world of sports has been revolutionized and a great turn around is seen today.
In sports like football, scouts, coaches, assistants, medical teams, and players themselves now have to depend on the wonders of sport analytics for better performance. Sports analysts make use of this system of judgment to trace football histories, predict possible match outcome, perform player ratings in terms of strength and other undiscovered facts to have a possible conclusion on any team or player or even coach. Studios are well furnished and decorated with modern information technology facilities like projectors and screens, phones, Ipad, advanced computerized systems, and preferred data analytic tools for pre-match, half time, and full time discussions of any game.
This does not only apply to the game of football but across different sports like Boxing, Athletics, Tennis, Swimming, Badminton, Taekwondo, Cycling, Formula 1, Golf, Rugby, Hockey, Cricket, Volleyball, Baseball, Squash, Snowboarding, Horse racing, Polo, Chess, Scrabble, etc.
The analytical tool(s) that are used in the world of sports are many and each of them has its own way of performing analysis and choosing any depending on the desired task outlined by the user. Next, we explore different tools used in sports, and how they help the decision making processes.
Data Analysis and Visualization: These tools are used by coaches and other crew members of a team to use previous data gathered on any team or player to analyze and display results generated after analysis. Softwares that can be used for data analysis and visualization includes:
R- This tool is used for performing powerful statistical computing. The way it functions is that it will use all the data inputted by the user and give the result that will be later interpreted and used to make drastic decisions.
Python- Python is a powerful programming environment and its libraries are well structured in such a way that users are provided with problem solving tools like the Pandas, NumPy, and Matplotlib to come up with results which are used for better choice of tactics.
Tableau- This tool helps to carry out analysis and display in a tabular form for easy viewing and decisive options.
Structured Query Language (SQL)- SQL is a very sensitive and dangerous tool. It consists of data that is stored for secured reasons. This sensitive tool contains data with passwords and logins. If it has been hacked, secrets will be exposed and opponents can take advantage of the protected data to exploit victims. In the world of sports, treasured secrets are encrypted and unauthorized access can’t see what is contained in the team’s entire record.
Power BI- This tool is also called “Business Intelligence” tool. Aside from being a source of entertainment, sports are business oriented professions and every management is meticulous when it comes to picking good players that will benefit them, and going out there to win the trophies that will fetch the finance or using marketing strategies to get spectators in the stadium. BI is actually a tool with great significance as the finance of every team lies in the correct use of this tool.
Wearable Sensors- There are actually devices that are structured to analyze the well being of players and they are called “wearable sensors”. Devices like accelerometer and heart rate senses how long players can last on the field of play.
Biomechanical analysis software- These software are structured to get full movement of any player on and off the pitch. An example of this software is the 3-D motion software.
Video Analysis- Video analysis is actually very vital when it comes to coming up with tactics to handle an upcoming match, half time analysis, in match decision making (substitution and VAR reviewing), and post match corrections. Tools that can be used for this are SportsCode, Hudl, VideoHub, Kinatrax, and Dartfish.
Using Machine Learning- With the rate of drastic advancement in technology, the use of AI and machine learning is very paramount in analyzing sports. Making use of platforms like IBM Watson, Keras, TensorFlow, PyTorch, etc, will enhance tremendous growth.
Making Use of Data Sources- Data gathering is key to decision making as every data used in the process will go a long way to help any team. There are platforms that already have raw data on any aspect of concern. The only thing to do is to contact these organizations and ask for any desired data. It could be that the management of a team has been looking for a way to minimize losing matches. They can approach these organizations, ask for previous match data on games lost, clean the data, and use any suitable software to carry out investigations and findings to stop any further occurrence.
The world of sport is not just for entertainment. It is real business blended with passion, joy, tears, achievements, and many many badges of honors. For any player, coach, or management that wants to stay high in the game, the use of sport analytics is inevitable.
