All posts by Eric King

My Model Monday: Modeling NFL Injuries

Injuries are inevitable in a game as physical as NFL football. Every season, numerous star players and important contributors are sidelined, leaving their fans and fantasy owners disappointed. Injuries appear to strike at random; an elite athlete can have his knee blown out in one cut like Dalvin Cook last season. However, is there a way to identify if certain players are more injury prone than others? I dug into the data to find out how well we can predict injuries among skill position players in the NFL.
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Prospect Profiles: Kevin Huerter

Leading up to the 2018 NBA Draft on June 21st, we will be using our NBA Draft Models (PNSP Model, Role Probability Model, and Similarity Scores) to investigate this year’s top prospects. These Prospect Profiles look at which stats affect NBA projections, present unique data points from a player’s stats, and give relevant comparisons to current NBA players. You can find all of our Prospect Profiles here or through the header menu above (NBA –> NBA Draft –> Prospect Profiles). In today’s article, we look at Kevin Huerter.

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Prospect Profiles: Robert Williams

Leading up to the 2018 NBA Draft on June 21st, we will be using our NBA Draft Models (PNSP Model, Role Probability Model, and Similarity Scores) to investigate this year’s top prospects. These Prospect Profiles look at which stats affect NBA projections, present unique data points from a player’s stats, and give relevant comparisons to current NBA players. You can find all of our Prospect Profiles here or through the header menu above (NBA –> NBA Draft –> Prospect Profiles). In today’s article, we look at Robert Williams

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Prospect Profile: Kevin Knox

Leading up to the 2018 NBA Draft on June 21st, we will be using our NBA Draft Models (PNSP Model, Role Probability Model, and Similarity Scores) to investigate this year’s top prospects. These Prospect Profiles look at which stats affect NBA projections, present unique data points from a player’s stats, and give relevant comparisons to current NBA players. You can find all of our Prospect Profiles here or through the header menu above (NBA –> NBA Draft –> Prospect Profiles). In today’s article, we look at Kevin Knox.

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Prospect Profiles: Miles Bridges

Leading up to the 2018 NBA Draft on June 21st, we will be using our NBA Draft Models (PNSP Model, Role Probability Model, and Similarity Scores) to investigate this year’s top prospects. These Prospect Profiles look at which stats affect NBA projections, present unique data points from a player’s stats, and give relevant comparisons to current NBA players. You can find all of our Prospect Profiles here or through the header menu above (NBA –> NBA Draft –> Prospect Profiles). In today’s article, we look at Miles Bridges.

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Prospect Profile: Collin Sexton

Leading up to the 2018 NBA Draft on June 21st, we will be using our NBA Draft Models (PNSP Model, Role Probability Model, and Similarity Scores) to investigate this year’s top prospects. These Prospect Profiles look at which stats affect NBA projections, present unique data points from a player’s stats, and give relevant comparisons to current NBA players. You can find all of our Prospect Profiles here or through the header menu above (NBA –> NBA Draft –> Prospect Profiles). In today’s article, we look at Collin Sexton.

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Prospect Profile: Marvin Bagley III

Leading up to the 2018 NBA Draft on June 21st, we will be using our NBA Draft Models (PNSP Model, Role Probability Model, and Similarity Scores) to investigate this year’s top prospects. These Prospect Profiles look at which stats affect NBA projections, present unique data points from a player’s stats, and give relevant comparisons to current NBA players. You can find all of our Prospect Profiles here or through the header menu above (NBA –> NBA Draft –> Prospect Profiles). In today’s article, we look at Marvin Bagley III.
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2018 NBA Finals

Through three rounds, we have gone 10/14 in series predictions. Two of these incorrect picks have come from series involving the Cavaliers. As we have seen in prior years, our models have a hard time assessing the Cleveland Cavaliers because they consistently under perform in the regular season. In the Championship round, our models are siding with the Golden State Warriors. Four of our five models picked the Warriors to win, and the average probability across the five predictions is 0.69. We will continue to update the table below following each game in the series!

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2018 NBA Conference Finals

The probabilities for our second round predictions were generated from four unique statistical models that are built on team and player level data from the regular season. Our prediction for each series comes from computing the average of these four models. Keep in mind that teams who had significant injuries in the regular season may be undervalued by the models. Likewise, teams who have players that played through the regular season but are injured for the playoffs are likely overvalued. For more information on our modeling techniques check out our methodologies page. Continue reading 2018 NBA Conference Finals

My Model Monday: Deep Dive Into Technical Fouls

Tensions between players and NBA officials have been on the rise over the past couple years. In the 2016 – 2017 season, referees called 917 technical fouls, and in the 2017 – 2018 season that number increased to 946. Players and coaches are antagonizing referees more and more, forcing referees into handing out more technical fouls. On most occasions, a technical fouls is due to a player or coach letting their emotions get the best of them. Other times, the technical may have been drawn intentionally to send a message. When a technical foul is called, the opposing team is awarded a free throw, but the overall effect on the game doesn’t always end there. In this article, I investigate how technical fouls effect the game from the perspective of the teams involved and the officials. All of the data in this analysis came from basketball-reference.com. Continue reading My Model Monday: Deep Dive Into Technical Fouls