It’s May and the 2019 NBA Draft is a little over a month away. Soon we will watch the future stars of tomorrow excitedly walk onto the stage and shake Commissioner Adam Silver’s hand. Of course, mixed in with the future stars will be many draftees who will simply never pan out.
Continue reading “How Likely Is Each Draft Pick to Someday Make an All-Star Team?”
The difference between good and bad bench play could be 3 or 4 points per game.
Back in 2015, Seth Partnow, now a member of the Milwaukee Bucks analytics team, did a great job analyzing how each team deployed lineups featuring each possible number of starters, from 0 to 5. Inspired by his approach, I gathered data on starting and bench units for the current 2018-19 regular season, through December 30th. I was particularly interested in the question in the title of this article: How important is a good bench to NBA success?
Continue reading “How Important Is A Good Bench To NBA Success?”
What is more valuable, an offensive rebound or a defensive rebound? Consult Expected Points Gained.
The currency of a basketball game is points. This is obvious. After all, this is the one thing we add up to determine who won and who lost.
This really simple insight actually has a lot of value as a framework for evaluating everything that happens on the court. Each action that a player takes, be it good or bad, has to have its effect traced back to the scoreboard to be properly measured. Of course, some actions, like made jumpers and rebounds, are neatly recorded in the box-score and others, like contesting a shot or moving the ball quickly to keep an offensive action going, are not. But, at the end of the day, we really need to tie everything back to points.
Continue reading “Expected Points Gained, A Framework For Evaluating Actions On A Basketball Court”
Inspired by Ben Falk’s Predict challenge on his website, Cleaning the Glass, (a really cool website if you’re an NBA fan) and filled with intrigue about year 1 of the LeBron led Lakers experiment, I decided to tackle this question.
So, how should we go about answering it?
Defending the jump shot, particularly the 3-point shot, is one of those seemingly small topics that for some reason I keep coming back to. I think what first peeked my interest was a podcast in which a guest speculated that one of the biggest unanswered questions in basketball analytics was the degree of control the defense has on the offense’s 3-point field goal percentage. He said that some analysts guessed that much of the year-to-year variability in 3-point percentage defense was due to chance. The main source of control a defense has with to respect to 3-pointers could be limiting the number of attempts (particularly open and corner threes), rather than forcing a low percentage.
I dived right into some small projects inspired by this discussion. My first post examined whether the shooting ability of the players actually taking the 3-pointers against a particular defense had some ability to explain variability in 3-point percentage defense. I looked into whether the Celtics’ sustained run of top-5 3-point percentage defenses under Coach Brad Stevens could be a fluke of randomness (it’s highly likely it’s not). I also analyzed which team statistics were most likely to carry over from the first half of the regular season to the second, and found defensive 3-point percentage was low on that list.
Now, I have tried quantify exactly how many points of defensive rating (points per 100 possessions allowed) are subject to opponent shooting variability. Besides simply considering 3-pointers, I also looked at free throws and ‘deep’ 2-point attempts, where I defined deep as greater than 16 feet.
With the 2018 NFL season underway, I decided to release some work on my first NFL project: a team rating and prediction system.
Motivating this project was a simple question. How much should we adjust our thinking about a team based on the result of 1 game? This has always been a question which has intrigued me.
We go into a new football season with some general expectations of the ability level of each team. Many of our expectations come from their past performance, but some new information is also added with offseason signings, trades, injuries, etc… Of course, there is a lot of uncertainty surrounding each team.
Then we witness week 1! Some teams look like underrated breakout candidates, and others flop. Hot takes abound. But how much information can 1 game really give us?
Continue reading “Threes and Layups NFL Team Ratings, Explained”
Though the NBA regular season is still 43 days away, it’s never too early to take a look at regular season win total over/unders!
Rather than building a projection system and delving into whether specific teams are more likely to go over or under, I instead decided to determine whether or not five key predictors could in any way help us make predictions in general. I will introduce the specific predictors in the next section.
To conduct my analysis, I looked at the over-under lines for all teams over the past six regular seasons. I was able to find a combination of lines from Bovada and the Westgate SuperBook, using the articles cited in the reference section. The dates for these lines ranged from October 5th to October 18, so they generally were recorded a week or two before the start of the regular season. All other information used in this article, mainly the statistics used to calculate my predictors, came from basketball-reference.com.
Continue reading “Which Types of NBA Teams are the Best Win Total Over/Under Bets?”
