This is another destination on the bucket list. It's a little distant, but for a couple of days, a stat-geek, baseball fans nirvana. I'll see if the wife is up to it after we take in the SABR junket in Pittsburgh this year. Mrs. TheSlav is a good soldier for wanting to hang out amongst such a nerdy crowd.
Watch for these sports analytics developments in 2018
Personnel decisions are still important, but increasingly sports analytics is driving business decisions such as improving the fan experience, streamlining concession operations, and increasing revenue. And not all of the work is glamorous enough to make it into a Hollywood blockbuster starring Brad Pitt.
We asked three MIT Sloan alumni to share their thoughts about emerging trends in sports analytics in the upcoming year, as well as the untold stories that don't often make headlines.
Integrate data sources to advance competition
The biggest story in basketball analytics on the horizon will be the integration of disparate data sources to uncover unique and powerful insights.
Right now, teams and the league office collect and analyze many different data sets — game events, game and player tracking, practice and training, wearables, and injury and medical, just to name a few. Each data set is relevant for one or more set of stakeholders, from general managers to coaches to medical personnel to analytics staffs. But the ability for these data sets to fully speak to each other is still relatively limited, and the opportunity exists to combine them in potentially game-changing ways.
This opportunity will rely on technologies like machine learning and computer vision, as well as the ability of analysts to create insightful yet simple data visualizations to influence key decision makers at the teams and league. If successful, this next data revolution will serve to advance basketball competition through player performance improvement, injury prevention and recovery management, and even enhanced teamwork and quality of play.
– Evan Wasch, MBA '11, Senior Vice President, Basketball Strategy and Analytics, NBA
Communicate why data is useful
The biggest story in sports analytics over the next year will be the continued focus on applying data analysis to improving athlete performance and injury prevention. This will be a battle in the NBA as long as wearables are banned in-game, but the increase in data collected during practices and with more robust player tracking cameras will challenge NBA analytics departments with the perpetual question: What do we do with this?
Utilizing wearable technology will of course be most crucial for the NFL, as injury prevention [and] minimization will be the most important factor in keeping the league afloat down the road. Hopefully the significant increase in data collected by NFL teams, and the importance of this data, will encourage franchises to invest more in their analytics departments in the next couple of seasons.
From my perspective, the most important untold story in sports analytics is the communication aspect of the job. You can create any statistic you want — but if you're not able to clearly explain what it is and how it can be utilized to improve the team, then the statistic is inconsequential. A lot of my focus is on ensuring our front office and coaching staff fully understand all of the information we're providing them so they can act appropriately on that information. I've read a lot of excellent research on basketball on free websites like Nylon Calculus and at the Sloan Sports Analytics Conference, but sometimes these researchers need to take a step back and think about how their work could be communicated to people who think Random Forest is a national park in California. The most successful analytics minds throughout sports are all excellent communicators, and that part of the gig never gets its proper shake.
– Jake Loos, MBA '14, Director of Basketball Analytics and Technology, Phoenix Suns (NBA)
Create a different fan experience
The fan experience is something we're constantly revaluating, especially as we see fan preferences change. Before the 2017 season, we did an $18 million renovation to center field [at Minute Maid Park]. Tal's Hill went away, and we had to make sure we put in something really cool.
We put in a field-facing area that offered a different in-park experience. It's open and it's more social. Fans can stand or lean against the bar and watch the game, rather than sitting in an assigned seat. That area was hugely successful, and part of the success was bringing in a popular local brand, Torchy's Tacos. That area became a focal point for people to eat and drink and watch baseball. Now we are thinking, "What are the other opportunities to create a different experience and appeal to food and beverage preferences of our fans?"
Watch for these sports analytics developments in 2018
Integrated data sources, an emphasis on communication, and new fan experiences.
By Brian Eastwood | December 28, 2017
Why It Matters
For 15 years, sports teams have led the way in using analytics for competitive advantage. Three experts tell us about the discipline's next frontiers.
When most people hear the term "sports analytics," the first thing that comes to mind is "Moneyball" — the 2003 book and 2011 film that detailed use of predictive analytics to evaluate on-field talent and find players with skills or other talents that competitors have overlooked.
Personnel decisions are still important, but increasingly sports analytics is driving business decisions such as improving the fan experience, streamlining concession operations, and increasing revenue. And not all of the work is glamorous enough to make it into a Hollywood blockbuster starring Brad Pitt.
We asked three MIT Sloan alumni to share their thoughts about emerging trends in sports analytics in the upcoming year, as well as the untold stories that don't often make headlines.
Integrate data sources to advance competition
The biggest story in basketball analytics on the horizon will be the integration of disparate data sources to uncover unique and powerful insights.
Right now, teams and the league office collect and analyze many different data sets — game events, game and player tracking, practice and training, wearables, and injury and medical, just to name a few. Each data set is relevant for one or more set of stakeholders, from general managers to coaches to medical personnel to analytics staffs. But the ability for these data sets to fully speak to each other is still relatively limited, and the opportunity exists to combine them in potentially game-changing ways.
This opportunity will rely on technologies like machine learning and computer vision, as well as the ability of analysts to create insightful yet simple data visualizations to influence key decision makers at the teams and league. If successful, this next data revolution will serve to advance basketball competition through player performance improvement, injury prevention and recovery management, and even enhanced teamwork and quality of play.
– Evan Wasch, MBA '11, Senior Vice President, Basketball Strategy and Analytics, NBA
Communicate why data is useful
The biggest story in sports analytics over the next year will be the continued focus on applying data analysis to improving athlete performance and injury prevention. This will be a battle in the NBA as long as wearables are banned in-game, but the increase in data collected during practices and with more robust player tracking cameras will challenge NBA analytics departments with the perpetual question: What do we do with this?
Utilizing wearable technology will of course be most crucial for the NFL, as injury prevention [and] minimization will be the most important factor in keeping the league afloat down the road. Hopefully the significant increase in data collected by NFL teams, and the importance of this data, will encourage franchises to invest more in their analytics departments in the next couple of seasons.
From my perspective, the most important untold story in sports analytics is the communication aspect of the job. You can create any statistic you want — but if you're not able to clearly explain what it is and how it can be utilized to improve the team, then the statistic is inconsequential. A lot of my focus is on ensuring our front office and coaching staff fully understand all of the information we're providing them so they can act appropriately on that information. I've read a lot of excellent research on basketball on free websites like Nylon Calculus and at the Sloan Sports Analytics Conference, but sometimes these researchers need to take a step back and think about how their work could be communicated to people who think Random Forest is a national park in California. The most successful analytics minds throughout sports are all excellent communicators, and that part of the gig never gets its proper shake.
– Jake Loos, MBA '14, Director of Basketball Analytics and Technology, Phoenix Suns (NBA)
Create a different fan experience
The fan experience is something we're constantly revaluating, especially as we see fan preferences change. Before the 2017 season, we did an $18 million renovation to center field [at Minute Maid Park]. Tal's Hill went away, and we had to make sure we put in something really cool.
We put in a field-facing area that offered a different in-park experience. It's open and it's more social. Fans can stand or lean against the bar and watch the game, rather than sitting in an assigned seat. That area was hugely successful, and part of the success was bringing in a popular local brand, Torchy's Tacos. That area became a focal point for people to eat and drink and watch baseball. Now we are thinking, "What are the other opportunities to create a different experience and appeal to food and beverage preferences of our fans?"
One thing that surprises people is that sports teams are basically small and medium-sized businesses. People think about MLB and NFL as huge leagues, but on the team level, we're run as SMBs. One of my projects is working on our mobile technology, and I'm doing everything from analyzing data to standing at [fan entrance] gates and troubleshooting problems, because there's only so many people in the organization. I'm implementing the strategies that we are putting into place. We're like any other company trying to maximize the use of its resources. It's not all sitting in an office writing pretty algorithms or writing analyses. It's boots on the ground.
– Jay Verrill, MBA '12, Director of Business Strategy and Analytics, Houston Astros (MLB)
Sent from my iPhone
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