Big Data has been determining that sports are beyond mere physical games. Sports, in today’s world, is more of a numbers game. From sports like baseball, football, soccer, basketball as well as fields like fantasy sports, each of these has begun depending on big data for enhancing the efficiency of its players and to work towards predicting future performances.
Whether its historical data, essential scorekeeping, forecasting for algorithmic performance or clear cut statistics of players, big data is an integral part and parcel of the sports industry.
Big Data allows teams and companies to stay updated on performance, carry out predictions, and be resolute when it comes to the sports field. Beyond the field, all the involved parties in the industry including commentators, analysts, as well as fans constantly adopt data, be it in case of providing play-by-play updates or discussing predictions.
In the competitive sports industry, collective knowledge of player stats, their abilities and comprehensive performance skills are the elements which propel the results. The sports industry has been largely modified with Big Data analytics, be it in case of experts, beginner, or youth sports. Big Data has been revolutionizing the sports sectors by elucidating statistical data and handling qualitative and quantitative information into stable and understandable content.
In case of Analytics Cloud Based Softwares, we have tools like Tableau, which allows Sports Management Analytics. This tool aids coaches in tasks such as simplifying operations, engaging fans and building dashboards, creating enhanced routines for exercise, and deducing workload management data through sports data visualizations like graphs and charts.
It also facilitates advanced solutions for fixing issues or for predicting outcomes and aid in properly equipping the athletes with the mental and physical strain demanded by sports. The software also allows aspects like any tactical or technical omissions, detection of load management errors in case of athlete response, daily supervision, data aggregation as well as the perceived rate of exertion to be effortlessly traced through predictive analytics and machine learning.
Yet another cloud based analytics platform in the arena of Sports is Boom Stats Analysis (BSA). This is a cloud-based, responsive data collection platform. The platform supports a range of sports from Cricket, Football, Lacrosse, Handball, Basketball to Rugby. It allows Coaches, players as well as clubs who require data regarding the match performance to develop a customized dashboard by sharing videos of games and insights of the players. It also records wellness and fitness data and stores player training while also developing personalized labels for every game, event, team stats or player.
In the case of game scoring applications, there are a number of platforms which aid small league coaches in gathering statistics of players, collecting game scores and also allow parents to stay updated on the data analytics promptly through their phones and to observe statistics through the live play-by-play action feature.
One such application is Score Stream. From helping the users stay updated on scoring games and aiding them in sharing past game memories with their friends and family, this application is greatly effective for youth sports enthusiasts. Developed particularly for high school as well as youth sports updates, this application provides text updates and notifications and also has play-by play commentary, real-time interactions, as well as professional photos which we can access through our phones.
When it comes to softwares for management of Athletic Sports, we have platforms like Sports Plus. This platform features aspects like the player registration, program management, payment processing, team roster management, staff management, training schedule management, field management. It allows the users to access everything on a single platform. The platform is greatly useful for athletes and coaches of youth sports, sports clubs, teams and leagues who are interested in streamlining massive degrees of data. Teams create their own website with the free website builder and its designed for people with no coding experience. Create a custom website in just a few clicks with widgets that is customized and easy to use.
In the area of team management of youth sports in case of associations, leagues, clubs as well as coaches, there are a variety of useful tools and applications. One such effective application is TeamSnap. This application allows its users to observe the athletes and rosters of the team from all kinds of sports be it tennis, swimming, hockey, basketball, baseball, softball, football or lacrosse. It also allows the users to generate schedules and effortlessly sync personal and team calendars. The platform also allows the user to gather payment, send invoices, and get real-time updates and video highlights of the games. Alongside this, it aids users in handling volunteers, carpools, sign-ups and in sending any last minute updates promptly.
You can also check out our blog on Role of Business Intelligence in the Sports Industry.
Playing sports in colleges and universities often offers athletes an advantage of having a section of their college payment covered through scholarships which are related to sports. Not to mention that successful athletes can also enhance the reputations of universities.
As a result, this has led to various universities focusing on enhancing their probabilities of discovering potential upcoming athletic stars through the magic of big data algorithms. One such example is that of the University of Virginia. The university has used algorithms which envision the chances of a football player to enter the NFL or to attend their university rather than another school.
This aids the recruiters in staying updated on where to invest their efforts and time. Yet one of the limitations of this approach is that there are many factors such as family issues or lack of financial resources which can restrict people from achieving an advanced athletic potential level prior to entering college which implies that a more comprehensive idea of the player’s background is required for undertaking the recruiting decisions alongside the reliance on data.
How Big Data is Revolutionising the Sports Industry
All kinds of sports exhibit a risk, particularly sports involving contact hold a high degree of chances of the athletes facing concussions amidst gameplay. Even if the injury is detected by the athlete or the people associated with them, it may get dismissed owing to all the benefits of engaging in sports especially in places like high schools.
This factor increases the urgence of high schools to be able to detect events like injuries or concussions. Being able to detect concussions aids high schools in doing modifications in full contact practice and holding events such as safety seminars in order to curb these kinds of injuries. Big data becomes an effective weapon to help keep track of the number of incidents in a particular time period and to conclude if the introduced strategies have proven to be successful.
This factor makes big data effective even for the people who don’t play sports. For instance, it can be adopted by physicians for enhancing treatments for the players. While helmet manufacturers can take it into account while updating models. Although this largely depends on the platform accountable as well as the approach adopted.
One problem with the current methods of collecting concussions data is that consistency and accuracy can vary greatly depending on the organization responsible and the methods used while the legitimacy of the data remains a challenge.
Live games enhance and uplift the experience for sports enthusiasts, both in case of watching amateur or professional teams. Yet there’s often cases where the live attendance is low in some sports games. This has led to many stadiums adopting big data as an approach to resolve the issue and satisfy the fans.
The big data will aid companies in doing an in depth assessment of the popular merchandise in the stadium, even focusing on aspects like the size and color of the merchandise, so that they will have knowledge of the items in high demand to ensure that they would be available in ample supply.
Yet another approach for enhancing the experience of the fans through big data is to calculate which games have better chances of being sold out swiftly and also to aid them in prompting frequent ticket purchasers with updates suggesting them to act fast in order to not miss out on the games they have shown interest in.
Big data helps curb the external struggles which adversely impact the experience of the fans as well for instance the struggle of securing a parking spot. It can aid the managers in carrying out an analysis of the traffic to check the areas which have vacant spots so that delay can be avoided by promptly directing incoming vehicles to these spots.
With the fear of COVID19 putting a halt in the ongoings of the sports industry, in many areas, Big Data has played an integral role in getting the sports industry back on its feet particularly in the arena of college sports.
One such example is that of Oregon State University which has been able to get its student-athletes return to the campus ro practice for the summer and avoided a culminating outbreak.
Many schools including Oregon State University have been adopting data for not only enhancing athletic programs but even to generate COVID-19 screening tools which can aid them in securing the student athletes upon the campuses restarting.
The university’s IT department has recently adopted platforms like Microsoft’s PowerApps, SharePoint, Power BI, as well as Office 365 for setting up an application which will help with COVID-19 screening as well as contact detection for the university’s student-athletes.
This screening comprises frequent self-appraisals in which student-athletes can carry out an all inclusive questionnaire which inquires if they have experienced any COVID-19 symptoms in the last 24 hours.
The data generated by the Power BI dashboard notifies universities and colleges of any outbreak as and when it takes place. The data can also aid in contact detection.
Yet another university which has been adopting data to tackle this pandemic and get its student-athletes back on track is the University of North Florida. UNF has also been generating a daily health screening application which will aid their student-athletes in staying secure as they re-enter campus in the midst of the pandemic.
This smartphone app is being adopted by both the student-athletes as well as all members of the university’s campus community. After the screening inquiries have been responded to, the application determines which of the students, the staff, visitors and members have been cleared to enter campus.
Since many years, professional teams have been adopting data analytics for guiding decisions regarding management, the training of athletes and their performance.
Some more universities which have been adopting data analytics in the arena of sports include Boston University, which has adopted wearable devices as well as cloud-based analytics for assessing the biometrics of players in sports like lacrosse and field hockey.
Yet another example is that of the University of Rochester, in which the women’s basketball team has adopted data analytics programs for gauging any potential recruits while following conference regulations.
One more example is the University of Nebraska-Lincoln, which set up its sports analytics department in the year of 2015
Data science is both the present and the future of sports analytics. Enhanced Artificial Intelligence and improved machine learning models have boosted the capacity for updating the performance of the teams. In the present world dominated by data and technology, categories like data science have emerged as a weapon that can be applied to enhance the winning chances of teams in different circumstances.
6 Major Branches of Artificial Intelligence (AI)READ MORE
Reliance Jio and JioMart: Marketing Strategy, SWOT Analysis, and Working EcosystemREAD MORE
Top 10 Big Data TechnologiesREAD MORE
8 Most Popular Business Analysis Techniques used by Business AnalystREAD MORE
Deep Learning - Overview, Practical Examples, Popular AlgorithmsREAD MORE
7 Types of Activation Functions in Neural NetworkREAD MORE
What Are Recommendation Systems in Machine Learning?READ MORE
7 types of regression techniques you should know in Machine LearningREAD MORE
Introduction to Time Series Analysis in Machine learningREAD MORE
How Does Linear And Logistic Regression Work In Machine Learning?READ MORE