Mock Draft Time: With the finish line of the 2013-2014 NBA season in full sight, it seemed appropriate to drop my first full first-round mock draft of the season. Keep in mind that the draft landscape regarding specific picks is very fluid this year due to the larger than normal amount of traded picks with very specific trade protections. For a full list of who owes what, check out the NBA Draft Pick Debt section here.
So without further ado, here is the March 26th full first round:
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Analytics Isn’t Moneyball: In 2011, Brad Pitt starred in a blockbuster movie based on Michael Lewis’s 2003 book Moneyball, about Oakland A’s manager Billy Beane and how he used advanced analytics and stats to identify value in players in an effort to build a better team at a lower cost.
Unfortunately, this seems to be what people believe advanced analytics in sports is about, using stats to spend less money. However what the advanced statistics revolution is really about is far bigger than that and it’s born from the idea that what you can see isn’t the whole story.
More and more sports teams are trying to understand the game. Some of that is because owners of teams are learning how to maximize their other business through the use of Big Data, but also because Big Data isn’t nearly as hard to cultivate, manipulate and examine as it was five to 10 years ago. Data is easier to collect and it’s becoming easier and more cost effective to process.
By now, many of you have heard about SportsVu, the new spatial cameras installed in every NBA arena, which allows for the exact position of a player to be measured and cataloged along with all of the actions and reactions that follow.
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We now can not only see that a player rebounded the ball, we can now see where specifically he was, where opposing players were and what happened before or after the rebound was made. What has emerged from all of this is an entirely new world of information and intelligence that was often unnoticed and unconsidered.
The NBA is using some of this data on their Stats website, and while some of the trivial stuff that can be gleaned from the spatial tracking of players gets talked about – namely how far a player has run in a season – the truth is, and the SportsVu data people will tell you, there is so much data being collected, we haven’t even figured out how to use it all yet. What is out there and published is the tip of the proverbial iceberg of what is possible to see and understand.
There are entirely new companies and experts being hired to sort through the data, create toolbars and dashboards to help teams manipulate the data, source the data points that means the most and craft the data collected into tools that help evaluate not only how the game is played, but also how the game is coached and managed.
Add in new wearable technologies and sensors that allow for hyper accurate measurements of how players perform, to the spatial data and we are arriving at point of being able to “see” and even project optimal in-game performance.
Teams are starting to use spatial technologies to teach players the value and importance of spacing, what defensive and offensive sets yield the best results and to help teams to understand which combinations of players can yield the best possible outcome.
Advanced analytics isn’t at all about finding diamond-in-the-rough players, but rather how to identify players that fit into a specific system, how to craft systems that work better and how to predict what could work better in the future.
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For most of its history, sports has been managed and operated by gut feeling and eye-tests. With the ability to see and understand the game in a more methodical and objective way, new trends in coaching, training and developing talent have emerged.
So when you hear someone talk about advanced analytics, it’s not about finding cheaper players, because the players that excel in the advanced analytics world are going to be the players that are typically the most sought after and most valuable.
Advanced analytics is about being smarter about your decisions, using data to reinforce process and to use more than what you see on the floor in shaping principals and decisions.
Like all good tools, when used in combination with smart and talented people they can make the job at hand easier and with fewer mistakes, which is why some of the teams that get saddled with the analytic labels tend to have more successes than failures.
Robinson Finding His Groove: Blazers forward Thomas Robinson had a rough go of it after being drafted fifth overall in 2012. After a couple of stops in Sacramento and Houston, Robinson has finally found a home in Portland and is starting to show why he was so highly thought of coming out of Kansas. Robinson talked with Basketball Insiders about his role, finding some balance and how much he’s learned playing with guys like LaMarcus Aldridge.
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