Tech innovations have been greatly changing how industries work and how users engage with their services or products. The sports industry is among those that have been showing great changes. Not only does it affect the industry’s growth, but it also fully changes how fans interact with their favorite sports.
Before the era of advanced technologies, fans had to rely on their knowledge when betting or making predictions. Now, even beginners can search ‘what is the under in sports betting?’ to ensure they’re making well-informed decisions. That’s not all, because predictive analysis, as an innovative tech, is taking things to another level.
Predictive Analysis in Sports
As the name hints, predictive analysis is a tool that can be used to predict a certain outcome based on historical data and algorithms. Predictive analytics can be highly useful in the sports industry, as it gives a way for coaches and organizations to analyze team and player performance or entire game dynamics. In addition, predictive analytics can also be useful to study fan engagement.
The main benefit of predictive analytics in sports is to give deeper insights to the user for things that they might overlook. Predictive analytics can gather a massive amount of data in a short time. The information may include weather conditions, the opposing team’s strategies, and players’ statistics.
Data analytics uses Machine Learning (ML) models that can further process the data. Once the data are transformed and simplified, managers, coaches, and sports analysts use it to forecast multiple game scenarios.
Advanced technologies contribute to giving access to data that sports franchises used to struggle to get. They were either too complex or required too many resources.
Use Cases
Many teams now rely on AI for development implementation or player recruitment. These AI-based predictive analytics dig deep into the potential recruits to analyze their performance and efficiency over time. This helps recruiter predicts which candidates or scouting methods have the potential to give them the best outcome in the long run.
When used for recruitment, the analytic tools consider the candidate’s shooting percentages and efficiency ratings. It can also read further into the player’s biometric data, basically anything that can contribute to the prediction. The result is a more accurate projection of the candidate’s future, for example, how long they can potentially last as a professional player.
This type of analysis isn’t only useful during recruitment. Coaches and managers can also use the data to ensure any additions to the team have a good potential to merge with the current team chemistry or strategy.
Analytics for Fan Engagement
Sports marketer benefits from predictive analytics models when they want to increase fan interaction and optimize their marketing strategy. Analytic tools will gather data such as social media interactions and merchandise or ticket sales to study fans’ preferences and behavior.
This helps sports businesses to develop more optimized marketing campaigns that would suit their markets better. They can also improve game-day experiences or make changes to pricing if needed to increase attendance.
Outcome Prediction for Betting
Predictive analytics tools aren’t useful only for organizers or teams. Fans can also benefit from using predictive analytics, especially if they often engage in sports betting.
Sports betting traditionally requires fans to have a deep knowledge of the players and teams involved. However, there would still be many unpredictable aspects that fans won’t be able to fully take into account, such as injury or weather changes.
Predictive analytics can further help sports bettors make better decisions as it gives them deeper insights calculated from a massive amount of information. Advanced algorithms can simulate match results under different situations and calculate win probabilities. Thanks to predictive analytics, fans can now also enjoy fantasy sports.
Real World Use Cases
Predictive analytics has become an integral part of many parties in the sports industry. Many leagues have been actively leveraging predictive analytics for years now, and here are some of the examples.
Houston Astros in the World Series
The Houston Astros used predictive analytics when they won the World Series in 2017. They used a system known as ‘signaling’, so they could predict which areas their opposing pitchers would most likely throw alongside their pitch types. When they played, Astros’ hitters were equipped with this knowledge, allowing them to have an advantage over their opponents.
The Golden State Warriors’ Success
The Golden State Warriors are one of the NBA’s most successful teams over the past decade. Predictive analytics played a part in their success, as they use a system called ShotMap. It’s where they predict the best shot to take during each possession. Thanks to this system, the Warriors can improve their scoring rates more efficiently.
Not only for offense, but the Warriors are also known to use predictive analytics to improve their defense. They use another system known as Defensive Shot Location, which predicts the location where the opponents would most likely shoot. This information is then used to improve the players’ positions and the team’s defensive schemes.
Leicester City Foxes in the Premier League
In 2015, the Leicester City Foxes won a Premier League title despite being named one of the weakest teams in the league. This success, too, came from the use of predictive analytics.
The Foxes mainly utilize predictive analytics to spot undervalued players and create a playing style that would take advantage of each player’s strengths. They also create a system to improve their scoring success rate.