Sports

Score Big with AI and Machine Learning

Professional sports organizations once viewed data and analytics as having the potential to deliver an informational edge over the competition. Today, analytics are table stakes. These organizations need to go beyond simply using data to make decisions and execute on new ideas faster than the competition, enabling their people to take the best action at the right time.

Learn how automated machine learning is changing the game.

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AI and Sports

Sporting organizations have mountains of raw data, with more becoming available all the time. This information can now be used to drive value across all aspects of their organization from selling more tickets to preventing injuries in players. DataRobot enables these organizations to apply AI and machine learning to power insights and decisions both on and off the field.

Player Performance

Player Performance

  • Support draft decisions with future performance predictions
  • Decide which players to sign by understanding their present value and risk
  • Evaluate trade options
  • Precisely target offers
  • Enhance player development by providing feedback to players and coaches
  • Predict and prevent injuries
Ticketing

Ticketing

  • Predict which season ticket holders are likely to churn and why
  • Identify potential season ticket holders
  • Optimally price tickets
  • Forecast ticket sales/attendance
  • Optimize suite sales
In-Game Strategy

In-Game Strategy

  • Optimize a team’s starting lineup
  • Determine optimal game strategy, including defensive positioning
  • Understand how to counteract your opponent
  • Execute and refine your strategy based on real-time events

Use Cases

With AI and machine learning applications, sports organizations can use their data to improve every area of their operations. From player recruitment and performance to ticket sales, predictive analytics can help make targeted decisions and strategic changes that impact every area of a sports organization.

Player Projection

Understanding the actual value of a player and being able to predict future performance is the key to building better rosters. With machine learning, teams can make better decisions when signing players and when making decisions related to their existing rosters.

Player Valuations

Teams strive to get the best players for the lowest cost and least risk. Being able to accurately evaluate a player’s dollar value — along with their risks — can save significant money for an organization while opening up payroll flexibility to build sustainable success. These optimal valuations provide guidance to arbitration hearings, contract negotiations, trade opportunities, free agent signings, and international player acquisitions for the right price.

Player Development

Once a team has the ability to measure the value of a player, they can use that information to create a training strategy for each of their players that will maximize a player’s future value. Additionally, with insights from AI, organizations can provide rapid feedback on a player’s game or practice performance to highlight what they are doing well and what they can do to improve.

Optimize Game Strategy

If you can better predict the strengths, weaknesses, and tendencies of your opponents and your own personnel, you can identify the right strategy for each game situation. Maximize your wins through insights on what will likely happen after each decision in order to get the best performance.

Season Ticket Churn

It is cheaper to retain existing season ticket holders than to acquire new ones. Based on a ticket holder’s behavior, automated machine learning can help sports organizations predict which season ticket holders are unlikely to renew early, understand the key reasons why, and create strategies to keep them.

Pricing

Based on prior sales and variations in pricing, along with pricing information from third party sites, use DataRobot’s enterprise AI platform to determine single game prices for every seat. As each game gets closer, organizations can determine the price of each seat to maximize either attendance or revenue.

Suite Sales Optimization

Automated machine learning can help optimize the sale of suites to identify individuals and organizations that are most likely to purchase a suite. For existing suite customers, identify organizations at risk of not renewing and proactively work to maintain them as a customer.

Corporate Sponsorship

With DataRobot, sports organizations can identify corporations most likely to purchase a sponsorship and determine the value of that sponsorship, as well as identify corporations at risk of non-renewal.

DataRobot Can Help You With:

Sports Operations

You’re in a race with your competition to find the most useful information in your data. DataRobot finds the best models for you, and with DataRobot’s deployment service, you can quickly embed those models into your processes. Allow your analytics team to focus on finding the next advantage and exploit it before the competition does.

Ticket Sales

Using DataRobot, your ticketing team will better understand the optimal price tickets should be sold for, which customers are least likely to renew their season ticket package, and which customers would be most receptive to a season ticket package. Because DataRobot provides simple deployment options, you can easily connect DataRobot models to your existing CRM platform to enable your team to function more efficiently.

Marketing

Using DataRobot’s enterprise AI platform, marketing teams can understand the impact of both above-the-line and below-the-line marketing efforts. By using insights gleaned from DataRobot and measuring the impact of your organization’s marketing efforts, your marketing team’s contribution can be better optimized for the next season.

Venue Operators

Using historical information from a range of factors, such as ticket prices, attendance, type of event, and weather, your team can use DataRobot to quickly build models to identify the events that will generate the most revenue. You will be able to forecast attendance for events in order to determine food and merchandise purchases, predict staffing and identify the right price for each seat — maximizing attendance and revenue.

Zach Mayer
Zach Mayer
Director, Data Science, DataRobot

What Our Customers are Saying

  • "We were able to extract value from our modeling process, but DataRobot really helped us hit that inflection point where it went from something we valued and something we did to really blowing it out of the water."

    Braden Moore
    Braden Moore

    VP of Analytics, Philadelphia 76ers

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