The Lakers won the NBA playoffs thrillingly beating the Miami Heat in an NBA season like no other in the history of the game thanks to the COVID 19 pandemic. Bubbled up in the Walt Disney resort in Florida, the games were held without crowds but with artificial crowd voices created by sound engineers to give the feel of an actual crowded venue to the millions watching the game from their homes on television.
Even with the venues & crowds changed, the games were still contested fiercely. And, of course, as is the norm now, strategies were heavily guided by intelligent data analytics for both teams.
So, how did analytics become a strategic decision-maker in NBA (or in fact the sporting world as a whole)?
First, a quick pit stop examining how analytics became a sporting activity.
Up until recently, not many would have seen the sporting sector as a big market for software. Other than booking systems & score & point management, there wasn’t a huge demand for advanced computing in the early 2000s. But this is not the scenario anymore. Now, we have almost every sporting event, teams & even individual players with dedicated technology partners handling their digital infrastructure spanning from events as simple as automated score archival to advanced activity tracking & even intelligent playing style recommendations.
Data analytics crunches massive volumes of data generated from different sources such as cameras, activity trackers on players, temperature & surface conditions, etc. & derives useful insights from this data to help in producing better results. The impact made by analytics is so huge that studies predict that by 2024 the market for sports analytics will be worth USD 5.2 Billion with a 22% growth rate from 2019 where it was worth USD 1.9 Billion.
You can know more about the role of analytics in the wider sports world here.
Now, the full-court press on the role of analytics in the NBA.
When analytics has the potential to make such an impact, almost any sporting team will be interested in making a bet on it. As such, the National Basketball Association (NBA) certainly was a visionary in promulgating the use of data analytics amongst its 30 participating teams.
This brings us back to our first story of how data analytics became the 3rd team in the NBA finals.
Today, gameplays are set by coaches after relying on data analytics from past matches to calculate efficiency & precision of shot takers & accordingly assign player positions. Earlier this was done through gut feeling & blind trust. Lakers coach Luke Walton has said in the past that he relies on analytics to prepare a game plan & then on game feel during the actual game. Let’s have a round-up of the top 3 of these possibilities:
Creating game plans
As illustrated earlier, data analytics is helping coaches & managers create more meaningful game tactics to help teams stay competent on the court throughout the match. By analyzing thousands of historic point scoring methods, player movements & on-court camera captures, it is easier for teams to derive a winning strategy based on factual data. This was best illustrated by the rise of the Golden State Warriors who were one of the first NBA teams to rely on data analytics. Ever since they began using insights from analytics, their win percentage grew from 57% in 2013 to a whopping 82% in 2015, & in the process, they stunned the entire NBA league by creating a winning dynasty.
Ensuring player well being
Fatigue is a very important element in any sporting domain that involves heavy physical activity. Using data analytics, coaches can determine the optimal time frame for which each player is fatigue-free on the court & provide them with ample intervals to rest or be substituted to ensure that there are only fatigue-free players on the ground or court at any point of time. Using data from trackers & wearables on athletes can help in detecting vital signs like increased blood flow, oxygen level depletion, etc. During the 2020 season, the NBA announced the use of wearables like tracking rings to help keep track of player health, enable social distancing & much more to keep everyone safe from the COVID 19 pandemic.
Improving revenue
Teams can improve their ticket sales by running data-driven marketing campaigns based on themes that fans would love. By analyzing engagements from all digital channels like social media, online forums, etc., it becomes easy to spot trends that will attract fans into buying merchandise sold by teams through various channels. Miami Heat has been using analytics to predict home game attendance successfully for several seasons now & (in pre-COVID days) was able to use the insights to prepare their ground staff schedules as well as improve their seat pricing & stadium infrastructure.
The role of data analytics in NBA, or indeed in any sporting competition, today is crucial. From improving player health to enabling better revenue streams, sporting teams are empowered to do much more than what they did in the past by running analytics on the right data sets.
Of course, the key challenge here is to ensure that there is an accurate & comprehensive data annotation process in place to extract & define the most accurate data sets for teams to generate valuable insights through analytics. Without the right data annotation strategy, the insights generated from the large pool of data sets may not yield an effective result.
It is clearly important for sporting teams & sport governing bodies to demand the best analytical services to propel the next level of growth in their respective sporting domain.
That’s the winning formula.