Bob Stoll, a pioneer in using football analytics for betting, joins me to talk NFL analytics. He describes his model and how he incorporates statistics like air yards and QB pressures. Then Bob tells us about the surprising resource he uses for injury adjustments. Finally, we discuss the conference championship games: Tennessee at Kansas City and Green Bay at San Francisco.
JJ Zachariason, content guru at FanDuel and numberFire, joins me to talk analytics and the NFL Divisional Playoffs. He tells us about the surprising statistic for college running backs that he uses to project NFL performance. Then we get into the 4 playoff games. Among other insights, he discusses the situation that makes San Francisco even more potent and the truth about Kansas City's defense.
New Orleans might be the most complete NFL team on both sides of the ball. Host Ed Feng breaks down this team and their odds to win the Super Bowl.
Should you fade teams with interim coaches? Host Ed Feng looks at the data on bowl games with one interim coach.
Michigan plays Alabama in the Citrus Bowl. Host Ed Feng digs into the story behind these two teams this season and gives a prediction for the game.
You know to use data and analytics to predict bowl games. But what about another resource, one that doesn't involve data from the current season? Host Ed Feng tells you about a resource and what it says about Washington State vs Air Force.
To win your bowl pool, follow a two step process. Host Ed Feng first discusses which type of bowl pool to enter. Then he describes how to use a favorites versus contrarian strategy based on pool size.
Chris Andrews, director of the South Point sports book in Las Vegas, joins me to discuss his book Then One Day... and football numbers. He discusses his general approach to bookmaking, and how he deals with sharp bettors. He gives a great example of setting the line with Ohio State vs Clemson in the college football playoff. Chris talks about whether "momentum" is useful in either college football or the NFL. Finally, he tells a few of the stories that make his book such a great read.
Rob Pizzola, a professional sports bettor, joins me for a wide ranging conversation on the NFL. He talks about his team and played based models for the NFL. Then Rob discusses how he deals with fast rising teams like Baltimore. Finally, he gives some contrarian opinions on NFL QBs and takes a broad look at the sports betting landscape.
Host Ed Feng breaks down Ohio State at Michigan, Wisconsin at Minnesota and Alabama at Auburn. He ends by discussing two books and a YouTube channel that have captivated him lately.
Michael Salfino, whose work can be found on FiveThirtyEight, The Athletic and the Wall Street Journal, joins me to discuss the NFL. He tells us how initiated the Massey-Peabody football rankings. Then he explains the strategy for stopping Lamar Jackson that a team has yet to use in 2019. Finally, we discuss a key statistic for evaluating NFL teams and how this impacts his Super Bowl contenders.
Host Ed Feng discuss his results for the chance that each team makes the college football playoff. He looks deeper at Clemson, the Pac-12 contenders Utah and Oregon, and Minnesota.
Dr. Ben Baldwin, writer for The Athletic that covers the Seattle Seahawks, joins me to discuss NFL football analytics. He tells us why he goes by "new-age analytical" on Twitter. Then he explains his work on whether running the ball sets up play action, and how this has impacted Seattle's play calling in 2019. He then breaks down the Monday night game with Seattle at San Francisco. We end with a discussion on Aaron Rodgers, the Rams and the Big Data Bowl.
Kevin Cole, a data scientist at Pro Football Focus, joins me to talk football analytics. He describes his latest work in using Bayesian methods and player grades to evaluate NFL QBs. This allows him to assign a probability that Mitch Trubisky is better than Pat Mahomes and Deshaun Watson, no matter how small. We also discuss why QBs should not always minimize their interception rate. Finally, Kevin gives his thoughts on San Francisco, Green Bay, Cleveland and Baltimore.
Edward Egros, a professor SMU that works at the forefront of journalism and sports analytics, joins me to talk football. He explains his college football model and the impact of recruiting. Then we discuss SMU, Texas, Alabama and the Dallas Cowboys. Finally, he tells us about his sports analytics class, how to get NFL play by play data, and Florence Nightingale.
Whale Capper is an earthquake engineer who uses this technical expertise to predict the NFL. He tells us how he introduces variance into his model, and how this informs his betting. We talk about science vs art in his model, and how this pertains to the Miami Dolphins. He also tells us the team that he didn't like this preseason, and why he has changed his mind. We end with a great food discussion.
After six weeks of the season, we are starting to see early returns on college football teams. Which teams are living up to the preseason hype? Host Ed Feng looks at 3 teams: 1. the top 10 team that is no longer getting carried by its defense, 2. the team I had overrated this preseason that is looking good, but not in the way I expected, 3. the team in which everyone is talking about the QB, but that might not be its biggest problem.
Seth Walder of ESPN joins the show to discuss their excellent work on football analytics. He tells us how the Football Power Index (FPI) works for both college football and the NFL. In addition, he offers a college football and NFL team that FPI really likes. Then we get into ESPN's work with NFL Next Gen Stats which tracks the motion of all players. Seth tells us about pass rush win rate and the player on Tampa Bay tearing it up this season.
Rufus Peabody, a professional sports bettor, joins me to discuss how he uses analytics to make better bets. He talks about his Massey Peabody model for making college football and NFL predictions. We talk about teams like Wisconsin and Michigan in college football that have moved rapidly from their preseason projections. We also discuss Miami in the NFL, a most difficult team to quantify. Finally, Rufus talks about the data that goes into NFL player model.
Preston Johnson, a professional sports bettor and ESPN personality, joins me to talk college football and the NFL. He tells us about the two sets of numbers he uses in his football handicapping. This informs his positions on Michigan, Syracuse and SMU in college football and Denver and Green Bay in the NFL. Preston also talks about profitable versus unprofitable teasers in the NFL.
Dr. Eric Eager is a data scientist at Pro Football Focus pushing the frontiers of football analytics. He tells us whether pass rush or coverage matters more on pass defense. When the defense rushes the passer, Dr. Eager explains whether the offensive line or quarterback plays a bigger role in reducing that pressure. Then he explains the new player based model he uses to predict both college football and NFL games. Finally, we talk about the 2019 NFL season and the team that might become Jacksonville 3.0.
Aaron Schatz of Football Outsiders joins me for a wide ranging discussion on the NFL. He tells us about the most important frontiers in football analytics, which leads to a discussion of which defensive stats are least stable from year to year. Then we get into an overrated team, or Jacksonville 2.0. Finally, he tells us about an NFC North team that might surprise you.
The preseason is the time for high expectations in college football. However, not all teams live up to the hype. Using analytics and context, host Ed Feng identifies 3 overrated college football teams for 2019.
Host Ed Feng goes through 5 games based on predictions he usually saves for paying members of The Power Rank, his site for more accurate football predictions. These predictions allow him to dig deeper into the Clemson Tigers, the Wisconsin Badgers and the Kansas City Chiefs.
Colts QB Andrew Luck shocked the football world by retiring this weekend. To determine the effect of his absence on Indianapolis, host Ed Feng uses his NFL preseason rankings based on market win totals.