Leading up to the 2017 NBA Draft, we will be diving into what our Draft Models tell us about this year’s top prospects. Our Draft Models include the PNSP Model, NBA Role Probability Model, and Similarity Scores which each provide unique ways of evaluating college prospects. Our Prospect Profiles will look at which stats positively/negatively affect NBA projections, unique data points from a player’s stats, and relevant comparisons to current NBA players. You can find links to all of our Prospect Profiles in the header menu above (NBA –> NBA Draft –> Prospect Profiles). In this article, we take a look at KU Freshman Josh Jackson.
All posts by Sam Walczak
NBA Playoff Betting Models Through Rounds 1-2
This article provides a brief recap on how our NBA playoff predictions have performed so far in 2017. To see a more detailed background on the models used for these predictions, see this article. Continue reading NBA Playoff Betting Models Through Rounds 1-2
NBA Playoff Betting Models
Throughout the 2017 NBA Playoffs, we have been tweeting spread and total predictions for some games (e.g., Warriors -11, Game Total 220). This article provides some context to the numbers – how accurate are they? How are they being created? How are they interpreted? Do we use a Gregg Popovich variable? You can find all the answers below. Continue reading NBA Playoff Betting Models
2017 NCAA Tournament Recap
Here is a quick recap of how The Model performed during the 2017 NCAA Tournament. At the bottom of the article, you can find links to all of our content from this year’s tournament.
Continue reading 2017 NCAA Tournament Recap
March Madness – Final Four
The article below gives our predictions for the Final Four games for this weekend, including our win probabilities, point spreads, point totals, and over probabilities. For some additional background on our models, click here.
Continue reading March Madness – Final Four
March Madness – Elite 8
The first table displays our predicted win probabilities for the Elite 8, followed by a table showing our predicted point spreads, point totals, and over probabilities. As an example of how to interpret the predictions, in the first row of the win probability table, our models give Florida a 61% chance of beating South Carolina (and, conversely, South Carolina a 39% chance of beating Florida). The favored team according to our probabilities (i.e., > 50% chance of winning) has their probability marked in green. In the first row of the second table, our models have Florida (-6.3) beating South Carolina by 6.3 points, and Vegas has Florida (-3) beating South Carolina by 3 points. Positive numbers for both spread columns indicate that Team2 is favored. Additionally, our models have the total combined points scored in the Gonzaga vs. Xavier game as 141.7 (Vegas has 145.0), with a 74% chance of going over the total (note that the over probability model and the point total model are generated separately, so their predictions will not always agree).
Continue reading March Madness – Elite 8
March Madness – Sweet 16 Betting
The following table displays our predicted point spreads, point totals, and over probabilities for all eight Sweet 16 games. As an example of how to interpret the tables, in the first row, our models have Florida (+2.2) losing to Wisconsin by 2.2 points, and Vegas has Florida (-2) beating Wisconsin by 1.5 points. Positive numbers for both spread columns indicate that Team2 is favored. Additionally, our models have the total combined points scored in the Florida-Wisconsin game as 131.5 (Vegas also has 131.5), with a 57% chance of going over the total.
March Madness – Sweet 16 Probabilities
The following table displays our predicted win probabilities for all eight Sweet 16 games. As an example of how to interpret the predictions, in the first row, our models give Florida a 21% chance of beating Wisconsin (and, conversely, Wisconsin a 79% chance of beating Florida). The favored team according to our probabilities (i.e., > 50% chance of winning) has their probability marked in green. For more on our methodology, click here.
March Madness – 2nd Round Betting
The following table displays our predicted point spreads, point totals, and over probabilities for all sixteen 2017 second round games. As an example of how to interpret the tables, in the first row, our models have Villanova (-6) beating Wisconsin by 6 points, and Vegas also has Villanova (-6) beating Wisconsin by 6 points. Positive numbers for both spread columns indicate that Team2 is favored. Additionally, our models have the total combined points scored in the Villanova-Wisconsin game as 130.8 (while Vegas has 128.5), with a 45% chance of going over the total.
March Madness – 2nd Round Probabilities
The following table displays our predicted probabilities for all 2017 second round games. As an example of how to interpret the tables, in the first row, our models give Villanova a 65% chance of beating Wisconsin (and, conversely, Wisconsin a 35% chance of beating Villanova). The favored team according to our probabilities (i.e., > 50% chance of winning) has their probability marked in green. For more on our methodology, click here.