It’s clear that data’s a huge competitive advantage — it’s no coincidence that in the same year that the Golden State Warriors are the heavy favorite to take home the NBA Championship, they are also named the “Best Analytics Organization” by MIT Sloan Sports Analytics.

Sports analytics is a rising field, going far beyond the basics like batting averages. Billy Beane of the Oakland Athletics popularized sports analytics further with his “moneyball” approach that was immortalized by Hollywood and Brad Pitt. Now the most data-minded (and winning-minded) teams are even hiring full analytics teams — the Warriors’ staff includes three data experts. Check out these three ways sports organizations are taking their data game to the next level.

1. Curtailing injuries

When it comes to just about any sport, injuries are seen as an expected — albeit costly — part of doing business. Although training and preventative measures have become more advanced, most teams still seemingly rely on luck to ensure that their best players will be healthy for the biggest games.

What if analytics could help prevent injuries more effectively? Many teams are now using a variety of different ultra high-tech wearable devices to track an athlete’s performance throughout practice — spotting an athlete whose numbers are reading “sluggish” can prevent overtraining — one of the main culprits for injuries and poor game-time performance.

2. Identifying potential racism

Even fans and journalists are getting in on the action. In a recent New York Times article, a group of fans questioned the “latent racial biases” in NBA officiating, using Charlotte Hornets player Jeremy Lin as an example. One Lin fan spent late nights after her husband and three sons went to bed poring over highlight videos and spliced together a video titled “Jeremy Lin: Too Flagrant Not to Call,” demonstrating that officials refuse to call flagrant fouls (a particularly rough foul that can lead to an ejection) in Lin’s favor.

Normally this wouldn’t be the type of thing the NBA would be inclined to respond to, or even acknowledge. But the video spread like wildfire, even picked up by media outlets in Taiwan and Hong Kong.

The NBA fought back — with data. Noting that Lin has 1,537 drives to the basket in the past 3 seasons. Though Lin has not drawn a flagrant foul in any of those drives, there are several players with more drives who also haven’t had any flagrant fouls called.

Then ESPN reporter Tom Haberstroh jumped in — noting that the 813 fouls Lin has called over the past 3 seasons is the single highest total for a point guard – and third highest for any other position — without a flagrant foul. Can’t argue with those numbers.

3. Getting more money out of ticket sales

It’s no secret that teams using flexible pricing for ticket sales — charging more for games against a popular opponent, like a rivalry game. But many teams are going far beyond the basics, factoring a number of variables including how well a team is doing, where the opponent ranks in the standings, weather, and much more. The San Francisco Giants were one of the first teams to start pioneering this approach, using over 120 different variables to determine the price of each ticket. It seems to be paying off — the team reached 327 consecutive regular season home game sellouts.

This post includes just three examples of the exploding growth in the field of sports analytics. Access to such vast amounts of data is only one piece of the puzzle — teams have to enlist the right experts in order to understand what to do with that data. Want to learn more about how analytics is transforming the world around us? Download the free State of Analytics report.