#playeranalytics

Modern stadiums are equipped with smart infrastructure, offering fans features like high-speed Wi-Fi, mobile ordering, and seat upgrades through apps. These improvements make attending a game more comfortable and engaging.

"Effort is a skill, the same as vision and footwork. " [..] "While a computer can spit out a heat map, it can't gauge the quality of a shot challenge. For that, you need humans, trained to consume games as Riles intended. Which is why, starting this season, the NBA hired 15 new employees to track every deflection, contest, charge, loose ball and screen assist. The numbers are distributed to teams and available to fans on NBA.com. The loggers are former high school coaches, college players, camp counselors and referees." [..] "Activity is not enough. The NBA tracks how many miles per hour everybody moves on the court, and out of 486 players, James Harden is No. 481; Wall, 476; James, 475; Blake Griffin, 474; Green, 459. "What really matters is the effectiveness of the movement, not the energy," adds Daryl Morey, the Rockets' general manager. "All else equal, more hustle is better than less hustle, but the reality is less hustle from Michael Jordan is better than more hustle from Gerald Wilkins." Aptitude and awareness, strength and quickness, hand size and wingspan, are all ingredients in a complex formula. Effort is only the most obvious one." [..] ""One of the hardest things to predict is whether players will have the discipline to keep improving, keep working," Morey says. The deal turned out to be a bargain, with Beverley first among guards in the NBA's aggregate stat, setting up a possible Hustler's Ball with Green in the Western Conference finals. "Guys like Pat, who really had to fight their way into the league, I find often continue to work more than guys who made it on physical tools alone," Morey reasons. "Guys who are born with more athletic gifts are able to make it with less work."" [..] "Effort, after all, is expended in different ways by different people—whether it's Durant fighting through three defenders to reach his sweet spot at the elbow or Green climbing over a double screen to contest a corner three." [..] ""I think it's important to remember we're not playing baseball," Adams cautions. "There are some things you just can't quantify.""

"the very exercise of drawing up lists and rankings can be misleading for the probabilistically-illiterate because it seems to imply set-in-stone certainty about who the best player is, who the second best is, etc.; and this rigid numbering masks the underlying concepts of probability. And yet, drawing up player lists is key for the recruitment workflows of clubs, be it in drafts or transfer windows, or even just to set up a schedule for their scouts. [..] In the passing motif methodology I’ve used so far, the vector representing each player has 45 entries or numbers. The key conceptual bit is that when you have this type of vectorised representation, you can imagine each player as being in a “space” of some sort. [..] What this entry tried to show is that there is solid evidence that a player’s position in the 45-dimensional space determined by the passing motif methodology encodes a good amount of information which determines how many key passes he ought to have given a sort of “passing ability”. That doesn’t mean it encodes all the information. Perhaps the vectorised representation is missing out on what it is that makes Coutinho great. Nevertheless, once we’ve accepted and understood that the list will offer us, I doubt any club could claim that a list like this from different leagues from around the world is of no use to their organisation just because they might miss out on the Serbian League’s Coutinho (sadly, such is the ‘glass half empty’ prejudice that analytics face). [..] This entry began by taking a vectorised representation (passing motifs vectors) and established that if we look at the number of key passes each player made, the players’ vectors’ position in this space seemed to encode this info. On the other hand, it didn’t seem to encode the information pertaining to goalscoring. That isn’t to say it might not encode information regarding other metrics. Expected Assists maybe? It also doesn’t mean that other vector representations don’t encode some of this information better than my own passing motifs representation. It’s a bit of a 3 step thing really: 1. Find a vector representation, 2. Check what sort of information it seems to encode well (especially information that isn’t explicitly available elsewhere), and 3. Find a way to give players a rating using this fact."