A brief but interesting introduction
There are many graduates in today’s world that are interested in joining the sports industry. Computer science majors are no different. Although, as it may seem at first, getting a degree in computer science makes you a “geek”, or a “nerd”, you can still work in the sports industry. The latter is an ever-growing industry complete with various career paths that a computer science major can take. First it is important to note that in today’s world computers are ubiquitous, you can find them anywhere you go. From shopping centers to offices, from betting platforms and casinos to banks and financial companies. In our present world, everyone’s lives have been changed by computers. Many technically inclined minds are interested in computing and go on to study computer science at universities. In the past this was a stand-alone discipline that would only allow you to work in computer laboratories, research centers or universities. But in the modern world, everything has changed. As this article will show, there are many opportunities that are offered for computer science majors in the sports industry.
What does the sports industry look like from an economic perspective and why you should be interested in joining it?
The sports industry has been a growing industry for several decades. In North America alone, the sports market will grow from 48.73 billion dollars in 2009 to 83.1 billion dollars in 2023. Thus, over a period of 14 years, the sports market in North America is projected to grow by as much as 71%. This gives an average compound annual growth rate (CAGR) of approximately 4 % per year. This should be compared with the average rate of economic growth in the United States of 3% per year. Because the American economy usually expands by approximately 3% per year, so its nominal output increases by 3% every year (on average for the past 30 years), it means that most industries also expand at a similar rate. The sports industry, however, can be said to be beating the market. This means that its compound annual growth rate is greater than average economic growth in the United States.
Now let us look at how the sports industry is doing globally. Globally, the sports market has done even better. Since 2014 and up until 2018 its compound annual growth rate (CAGR) has been 4.3% and it has grown to a whopping 488.5 billion dollars in 2018. Hence, on a global level, it has performed even better than in North America. It is worth noting that global GDP in 2018 stood at roughly 85 trillion dollars, hence the sports industry constitutes an average of 0.6% of world’s economic output. Given its higher-than-normal CAGR growth rate, it is likely that this number will only grow.
What are the various subdivisions or categories of the sports industry?
The sports industry, being an extremely large and profitable industry, is divided into several categories. The first is professional sports, where players engage in games such as rugby or football. Here you will find championships, matches and other official sporting events. The second is the market for sports apparel. The vendors here cater to sports players and fans and sell various official sports clothing. The third is sports gambling. Here people can place bets, or wagers, on which team is going to win the match. Sites such as worldbookmakers allow a user to access a wide array of online sports betting sites and place wagers on his favorite teams. As an aspiring computer science graduate, you are free to choose from those segments of the sports industry to begin your career.
How computer science can help the sports industry develop further?
Data Mining
The use of computer sciences in sport has become an interdisciplinary field which uses Information Technology to interpret and analyze sports data. According to Wikipedia Computer science in sport is used for such things as data mining, computer modeling, simulations, and data processing. Data mining involves collecting large quantities of data for further processing. Here, the computer analyst will try to look for patterns or trends in the data that has been collected for analysis. For example, a computer scientist can analyze cricket matches going back 50 years to attempt to make a prediction as to who will win the next match. Sports provide a large amount of data that can be analyzed. In this data patterns and trends can be seen. Based on this, predictions can be made. Large quantities of data are extremely difficult to interpret without the use of a computer. For example, there can be 100 000 pieces of data that need to be processed. For this, a computer algorithm is needed. To add further, collecting the data without the use of a computer can be nearly impossible. According to computer scientists, this data can have hidden trends or patterns that need to be analyzed. Although previously data mining was used mainly for business and technology, it has now found its way into professional sports. Using a sophisticated data mining algorithm can help an analyst make an accurate prediction about how a given sports team will perform in a match.
It is worth noting that sports data mining became a growing field of study after a consensus had been reached that the opinion of experts is simply not good enough to predict the given match outcome. One of the positive aspects of the sports industry is that it collects records going back many decades. Hence there is a wide breadth of information that statisticians can work with and base their predictive models on. Using data mining can greatly help the manager to improve the team’s performance. Having the ability to analyze your team’s performance and discern hidden trends and patterns can help the manager to better train the team. Here a computer scientist can help the team to understand where it makes mistakes, which the manager of the team may have overlooked. For example, a hidden pattern in the team’s game data can be discovered. Based on this pattern the manager of the team can alter his training, which will allow the team to better perform in the future. Another example can be found in football. Here certain metrics, such as the number of touches, number of shots created, number of ball retentions and number of balls won can be analyzed. A computer scientist can look at the data going back for ten or twenty years and analyze the statistics. Based on this, he can make a prediction about which players are best for certain roles in the game. Players individually can also be analyzed with a computer, which will include such parameters as endurance, memory, and coordination. The analysis can then be used to select the best players available for the match. Here a computer scientist specializing in data mining can make a career in the ever-growing sports industry.
Data Processing
Data processing involves a conversion of large quantities of data into a readable and desired format. Initially, you receive what is known as raw data. Raw data is unprocessed data that can hardly be analyzed. With the help of a computer, raw data can be processed so a human can read it and make decisions based on it.
As sports can provide you with an extremely large quantity of data, data processing becomes essential for the manager or an analyst to quickly decide on. Sports data processing is another area of the sports industry where a computer scientist can work in. Here large quantities of data are analyzed with a computer and decisions are made by the manager of a team or a personal trainer to customize individual athlete’s training and improve performance. Here a large pool of statistics needs to be analyzed quickly and efficiently.
The statistics can include the number of passes a player has made, how many meters an athlete has run or how many touchdowns have been won. Overall, the collected pool of data can be extremely large. Should the manager of a team be interested in analyzing each individual athlete’s performance from various teams, he will simply be lost in raw data. This is where a computer scientist comes into play. By using data processing a huge and unnecessary swarth of raw data is processed into nice looking graphs, charts, statistical tables, and statistical aggregates. Thus, out of a huge sea of data, a nice-looking graph can be created, which will immediately show where in the team improvements must be made. The role of a computer scientist here will be to create a digital algorithm which can be used to process the large amount of raw data. Using this algorithm, the data can be immediately visualized or transferred into a single number, which will aggregate thousands of statistical points behind it.
Already today Big Data is used by sports clubs around the world to help them analyze individual athlete’s performance. Big Data is a computer science field that aims to statistically analyze large quantities of data and extract as much as possible useful information from it. Big Data is used in sports to determine which football or rugby player to pick for the game. The trick here is not choosing the best player but the correct player. The player whose specifications are a perfect fit for the team. This can greatly improve game performance of the team as well as lower general costs of buying new players. This is because the best player can cost 10 million dollars, while the right (correct or perfect) player can cost only 1 million or less. This way the football club can become much more efficient and achieve a higher rate of winnings.
Computer simulations and computer modeling
A computer simulation is a model built on a computer that attempts to simulate a real-world environment. Simulations can be extremely helpful when trying to predict the outcome of a game or an event. The increase in the power of computing has allowed for more and more real-world environments to be simulated. Sports is one of them. For example, simulations can be done of individual player’s moves to determine what part of the player’s body needs additional improvement or training. Here you need to simulate several biomechanical variables, such as joints, muscles, elastics of the body and body inertia. As the human body is complex, making a model of it requires a lot of processing power. Such models can help determine whether an athlete needs additional training. A computer science graduate that is interested in building computer simulations, can build a career in the sports industry focusing on simulating various parts of the human body. One of the fields that a computer scientist can focus on is building simulations of biomechanics. This latter term is used to describe the study of how the living body moves. For example, study is made of the movement of muscles, bones, and ligaments of the body. Biomechanical simulation is then used to analyze these movements on a computer.
In sport biomechanics is often used to improve performance of an athlete and minimize injury during the game. Computer science can be extremely helpful as biomechanical analysis can be extremely complex and impossible to perform without the use of a computer. Building simulations of the human muscle and bone movement can allow a professional to immediately see where an improvement must take place. Further, in conjunction with data mining, it can be possible to predict a player’s performance in the field using a computer simulation. Further, by using a biomechanical computer simulation it can be seen which sports gear should be best used by each individual player. Thus, the correct pair of shoes can be chosen for a football player or correct and optimal rackets for a tennis player.
Producing correct gear for each sport is also a huge part of the global sports industry. Be it shoes or trainers, they need to be ideally suited for the type of sport they are designed for. A computer scientist employing the tools of biomechanical simulation can use existing data on the movement of a sportsman’s body to design optimal sports gear for the game. For example, evaluating the data on football player’s movements can allow a researcher to improve the football shoes produced by a large manufacturer, for example by Nike. Most of the companies that specialize in producing sports gear hire computer scientists to help them optimize their products for any given sports (here biomechanical simulations need to take place). Let us take another example. Certain components of a bicycle can be optimized to reduce the weight of the bicycle and reduce the aerodynamic drag of the bicycle to improve its performance. To achieve that goal, a computer simulation of the bicycle must be performed.
Artificial Intelligence and Machine Learning
Machine learning takes place when a computer analyzes a large quantity of data and learns from it. This allows for the adoption of algorithms used by the computer to better accommodate its client. Artificial intelligence uses machine learning to discern patterns in the data and make predictions from it. Good AI algorithms allow a computer to make solid predictions about the future behavior of an athlete. Electronic labels can be applied to athletes to measure their running speed, distance they have travelled, acceleration, deceleration, and muscle movements. The data can then be fed into a computer with an AI algorithm installed on it. The computer’s artificial intelligence can then make predictions as to which player will perform the best in each environment.
The manager of the team can use the results obtained by the AI to better select players for the coming match. Should the next game be held in a stadium in a foreign country, the computer AI can predict the chances of winning the game based on the information that has been analyzed. The National Football League in the United States uses machine learning and AI algorithms to enhance the performance of its players in various matches. A computer scientist specializing in AI and machine learning can build a career in the sports industry in this field. Here he will use AI algorithms to help design strategies for the game. Also, he will assist in predicting the outcomes of games and work with large quantities of data to help the AI learn from it.
Conclusion
Even though computer science and sports at a first glance seem vastly different fields from each other, computer science graduates can build extremely good careers in the sports industry. Be it in data mining and processing, or computer simulations and modeling, and AI and machine learning, a computer scientist can make a highly positive contribution to the sports industry. More and more clubs around the world are going digital, meaning that they are starting to employ computer scientists to help them win games and train their athletes. With computer technology improving every day, in the future players may get virtual coaches, which will help them train to the highest degree possible.