Fanalytics With Mike Lewis Podcast

In this week's podcast, Professor Mike Lewis breaks down the week's biggest storylines in sports fandom, college football, and the NFL. Then, he dives into his Next Generation Fandom Survey to reveal recent findings on gambling and sports gamblers. Check out more Fanalytics content at www.fandomanalytics.com. Send in a voice message: https://podcasters.spotify.com/pod/show/fanalyticsmike/message Fanalytics is a part of the Professors.fm podcast network - making sense of the world with top scholars. Check out more Fanalytics content at fandomanalytics.com.  And make sure to follow us on social! Instagram: @fanalyticsmikelewisTwitter: @fanalyticsmikeYouTube: @fanalyticsmikeTikTok: @fanalyticspodcast

Professor Mike Lewis kicks off this week's podcast with a discussion on the week's most zealous fans - from one fan setting himself on fire at Federer's final match to the "checkerbearded" Tennessee Volunteers fan. Discussion of the Volunteers' ruckus fanbase leads us to talk college football as blue bloods like Michigan, USC, and Clemson fight to keep their College Football Playoff hopes alive. We then transition to our weekly discussion on the NFL's top storylines going into Week 4 of play. Check out more Fanalytics content at fandomanalytics.com Send in a voice message: https://podcasters.spotify.com/pod/show/fanalyticsmike/message Fanalytics is a part of the Professors.fm podcast network - making sense of the world with top scholars. Check out more Fanalytics content at fandomanalytics.com.  And make sure to follow us on social! Instagram: @fanalyticsmikelewisTwitter: @fanalyticsmikeYouTube: @fanalyticsmikeTikTok: @fanalyticspodcast

In this week's podcast, Emory Professor Mike Lewis discusses his top takeaways from Week 2 of NFL action as well as Appalachian State's eventful start to the 2022 football season. Topics of discussion include building meaningful fandom moments in small markets, quarterback analytics, and fandom statistics across genders. Send in a voice message: https://podcasters.spotify.com/pod/show/fanalyticsmike/message Fanalytics is a part of the Professors.fm podcast network - making sense of the world with top scholars. Check out more Fanalytics content at fandomanalytics.com.  And make sure to follow us on social! Instagram: @fanalyticsmikelewisTwitter: @fanalyticsmikeYouTube: @fanalyticsmikeTikTok: @fanalyticspodcast

In this week's podcast, Professor Mike Lewis kicks off the long-awaited NFL season with a discussion of the league's biggest week one storylines, college football's wacky week two, and Mike's findings on sports fandom across the political spectrum. Check out more Fanalytics content at fandomanalytics.com. Send in a voice message: https://podcasters.spotify.com/pod/show/fanalyticsmike/message Fanalytics is a part of the Professors.fm podcast network - making sense of the world with top scholars. Check out more Fanalytics content at fandomanalytics.com.  And make sure to follow us on social! Instagram: @fanalyticsmikelewisTwitter: @fanalyticsmikeYouTube: @fanalyticsmikeTikTok: @fanalyticspodcast

In this week's podcast, Professor Mike Lewis and his co-host Doug Battle discuss the difference in sports fandom across generations found in Mike's recently released 2022 Generational Fandom Survey. The two then discuss football's glorious return, NFL Week 1 storylines, and what public reception to The Rings of Power reflects about fandom. Send in a voice message: https://podcasters.spotify.com/pod/show/fanalyticsmike/message Fanalytics is a part of the Professors.fm podcast network - making sense of the world with top scholars. Check out more Fanalytics content at fandomanalytics.com.  And make sure to follow us on social! Instagram: @fanalyticsmikelewisTwitter: @fanalyticsmikeYouTube: @fanalyticsmikeTikTok: @fanalyticspodcast

In this week's episode, Professor Mike Lewis and his co-host Doug Battle take a look at the upcoming college football season and break down Week 1's biggest matchups. This episode also features discussion of Serena Williams, NFL quarterback storylines, and Mike's "sports apathy" findings from his 2022 Next Generation Fandom Survey. Send in a voice message: https://podcasters.spotify.com/pod/show/fanalyticsmike/message Fanalytics is a part of the Professors.fm podcast network - making sense of the world with top scholars. Check out more Fanalytics content at fandomanalytics.com.  And make sure to follow us on social! Instagram: @fanalyticsmikelewisTwitter: @fanalyticsmikeYouTube: @fanalyticsmikeTikTok: @fanalyticspodcast

In the first part of this episode, Professor Lewis and his co-host Doug Battle discuss the Big Ten's lucrative tv deal and what's next for conference realignment in college sports. Then, the two discuss the NFL players and teams taking the biggest risks this offseason - from the Cleveland Browns to Roquan Smith to the Chicago Bears to Lamar Jackson. Send in a voice message: https://podcasters.spotify.com/pod/show/fanalyticsmike/message Fanalytics is a part of the Professors.fm podcast network - making sense of the world with top scholars. Check out more Fanalytics content at fandomanalytics.com.  And make sure to follow us on social! Instagram: @fanalyticsmikelewisTwitter: @fanalyticsmikeYouTube: @fanalyticsmikeTikTok: @fanalyticspodcast

The Next Generation Fandom Survey (from the Emory Marketing Analytics Center) is a deep dive into how fandom works across the American population. It examines how fandom varies across demographic cohorts, gender, income, political ideology, and more. Amongst its many questions, the survey asks respondents to rate how much they like a variety of sports figures and celebrities. Serena Williams is one of the featured celebrities. Following Serena's retirement, we take a look at the data to observe how the women's tennis legend fares amongst sports GOATs. Send in a voice message: https://podcasters.spotify.com/pod/show/fanalyticsmike/message Fanalytics is a part of the Professors.fm podcast network - making sense of the world with top scholars. Check out more Fanalytics content at fandomanalytics.com.  And make sure to follow us on social! Instagram: @fanalyticsmikelewisTwitter: @fanalyticsmikeYouTube: @fanalyticsmikeTikTok: @fanalyticspodcast

Today we continue discussing where the NFL is going in 2022 with a data-driven look at the NFC West. Our NFL projections are based on a forecast of team performance and a subjective assessment of each team’s quarterback’s storylines. The team win forecast is primarily driven by a new advanced QB metric called QB Wins. The QB Wins metric is something that Mike has been working on for a decent amount of time. The QB Wins metric is computed using a wide range of raw data (TD passes, interceptions, yards, etc.), expert statistics (passer rating, QBR), and non-QB data (defense stats, rushing, etc.). The algorithm leverages the correlations and differences between these data sources to separate out QB, running game, and defensive performance. A second statistical analysis estimates the relationship between quarterback performance factors (and defensive and rushing factors) and team performance (wins). The result is a QB metric that identifies how much a player contributes to his team's record in a given year. In th

Today we continue discussing where the NFL is going in 2022 with a data-driven look at the NFC South. Our NFL projections are based on a forecast of team performance and a subjective assessment of each team’s quarterback’s storylines. The team win forecast is primarily driven by a new advanced QB metric called QB Wins. The QB Wins metric is something that Mike has been working on for a decent amount of time. The QB Wins metric is computed using a wide range of raw data (TD passes, interceptions, yards, etc.), expert statistics (passer rating, QBR), and non-QB data (defense stats, rushing, etc.). The algorithm leverages the correlations and differences between these data sources to separate out QB, running game, and defensive performance. A second statistical analysis estimates the relationship between quarterback performance factors (and defensive and rushing factors) and team performance (wins). The result is a QB metric that identifies how much a player contributes to his team's record in a given year. In t

Today we continue discussing where the NFL is going in 2022 with a data-driven look at the NFC North. Our NFL projections are based on a forecast of team performance and a subjective assessment of each team’s quarterback’s storylines. The team win forecast is primarily driven by a new advanced QB metric called QB Wins. The QB Wins metric is something that Mike has been working on for a decent amount of time. The QB Wins metric is computed using a wide range of raw data (TD passes, interceptions, yards, etc.), expert statistics (passer rating, QBR), and non-QB data (defense stats, rushing, etc.). The algorithm leverages the correlations and differences between these data sources to separate out QB, running game, and defensive performance. A second statistical analysis estimates the relationship between quarterback performance factors (and defensive and rushing factors) and team performance (wins). The result is a QB metric that identifies how much a player contributes to his team's record in a given year. In t

Today we continue discussing where the NFL is going in 2022 with a data-driven look at the NFC East. Our NFL projections are based on a forecast of team performance and a subjective assessment of each team’s quarterback’s storylines. The team win forecast is primarily driven by a new advanced QB metric called QB Wins. The QB Wins metric is something that Mike has been working on for a decent amount of time. The QB Wins metric is computed using a wide range of raw data (TD passes, interceptions, yards, etc.), expert statistics (passer rating, QBR), and non-QB data (defense stats, rushing, etc.). The algorithm leverages the correlations and differences between these data sources to separate out QB, running game, and defensive performance. A second statistical analysis estimates the relationship between quarterback performance factors (and defensive and rushing factors) and team performance (wins). The result is a QB metric that identifies how much a player contributes to his team's record in a given year. In th

Today we continue discussing where the NFL is going in 2022 with a data-driven look at the AFC West. Our NFL projections are based on a forecast of team performance and a subjective assessment of each team’s quarterback’s storylines. The team win forecast is primarily driven by a new advanced QB metric called QB Wins. The QB Wins metric is something that Mike has been working on for a decent amount of time. The QB Wins metric is computed using a wide range of raw data (TD passes, interceptions, yards, etc.), expert statistics (passer rating, QBR), and non-QB data (defense stats, rushing, etc.). The algorithm leverages the correlations and differences between these data sources to separate out QB, running game, and defensive performance. A second statistical analysis estimates the relationship between quarterback performance factors (and defensive and rushing factors) and team performance (wins). The result is a QB metric that identifies how much a player contributes to his team's record in a given year. In th

Today we continue discussing where the NFL is going in 2022 with a data-driven look at the AFC South. Our NFL projections are based on a forecast of team performance and a subjective assessment of each team’s quarterback’s storylines. The team win forecast is primarily driven by a new advanced QB metric called QB Wins. The QB Wins metric is something that Mike has been working on for a decent amount of time. The QB Wins metric is computed using a wide range of raw data (TD passes, interceptions, yards, etc.), expert statistics (passer rating, QBR), and non-QB data (defense stats, rushing, etc.). The algorithm leverages the correlations and differences between these data sources to separate out QB, running game, and defensive performance. A second statistical analysis estimates the relationship between quarterback performance factors (and defensive and rushing factors) and team performance (wins). The result is a QB metric that identifies how much a player contributes to his team's record in a given year. In t

Today we continue discussing where the NFL is going in 2022 with a look at the AFC North. Our NFL projections are based on a forecast of team performance and a subjective assessment of each team’s quarterback’s storylines. The team win forecast is primarily driven by a new advanced QB metric called QB Wins. The QB Wins metric is something that Mike has been working on for a decent amount of time. The QB Wins metric is computed using a wide range of raw data (TD passes, interceptions, yards, etc.), expert statistics (passer rating, QBR), and non-QB data (defense stats, rushing, etc.). The algorithm leverages the correlations and differences between these data sources to separate out QB, running game, and defensive performance. A second statistical analysis estimates the relationship between quarterback performance factors (and defensive and rushing factors) and team performance (wins). The result is a QB metric that identifies how much a player contributes to his team's record in a given year. In this podcast,

Part 1 of our NFL preview, the NFL brands and fanbases analysis, looked at which teams have the best fanbases. Today we begin discussing where the NFL is going in 2022. Our NFL projections are based on a forecast of team performance and a subjective assessment of each team’s quarterback’s storylines. The team win forecast is primarily driven by a new advanced QB metric called QB Wins. The QB Wins metric is something that Mike has been working on for a decent amount of time. The QB Wins metric is computed using a wide range of raw data (TD passes, interceptions, yards, etc.), expert statistics (passer rating, QBR), and non-QB data (defense stats, rushing, etc.). The algorithm leverages the correlations and differences between these data sources to separate out QB, running game, and defensive performance. A second statistical analysis estimates the relationship between quarterback performance factors (and defensive and rushing factors) and team performance (wins). The result is a QB metric that identifies how m

After a few weeks of discussion involving Mike's NFL Fandom Rankings, Mike and his co-host Doug Battle discuss the latest stories in sports and entertainment - from the NBA Playoffs to Disney's new Obi-Wan Kenobi Show. The common thread that ties this episode together is the segmentation of audiences across sports and entertainment. Send in a voice message: https://podcasters.spotify.com/pod/show/fanalyticsmike/message Fanalytics is a part of the Professors.fm podcast network - making sense of the world with top scholars. Check out more Fanalytics content at fandomanalytics.com.  And make sure to follow us on social! Instagram: @fanalyticsmikelewisTwitter: @fanalyticsmikeYouTube: @fanalyticsmikeTikTok: @fanalyticspodcast

Knowing where the passion lies and will lie in the future is essential for every sports league. In the third and final installment of our NFL Fandom Rankings discussion, Emory Marketing Professor Mike Lewis leverages statistical models based in economic and marketing theory to rank the top quarter of NFL fanbases. Check out the full rankings at fandomanalytics.com. Send in a voice message: https://podcasters.spotify.com/pod/show/fanalyticsmike/message Fanalytics is a part of the Professors.fm podcast network - making sense of the world with top scholars. Check out more Fanalytics content at fandomanalytics.com.  And make sure to follow us on social! Instagram: @fanalyticsmikelewisTwitter: @fanalyticsmikeYouTube: @fanalyticsmikeTikTok: @fanalyticspodcast

Knowing where the passion lies and will lie in the future is essential for every sports league. In part two of our NFL Fandom Rankings discussion, Emory Marketing Professor Mike Lewis leverages statistical models based in economic and marketing theory to rank the NFL's fanbases. He also responds to fan feedback from part one of the annual rankings. Check out the full rankings at fandomanalytics.com. Send in a voice message: https://podcasters.spotify.com/pod/show/fanalyticsmike/message Fanalytics is a part of the Professors.fm podcast network - making sense of the world with top scholars. Check out more Fanalytics content at fandomanalytics.com.  And make sure to follow us on social! Instagram: @fanalyticsmikelewisTwitter: @fanalyticsmikeYouTube: @fanalyticsmikeTikTok: @fanalyticspodcast

Knowing where the passion lies and will lie in the future is essential for every sports league. In this podcast, Emory Marketing Professor Mike Lewis leverages statistical models based in economic and marketing theory to rank the NFL's fanbases. Check out the full rankings at fandomanalytics.com. Send in a voice message: https://podcasters.spotify.com/pod/show/fanalyticsmike/message Fanalytics is a part of the Professors.fm podcast network - making sense of the world with top scholars. Check out more Fanalytics content at fandomanalytics.com.  And make sure to follow us on social! Instagram: @fanalyticsmikelewisTwitter: @fanalyticsmikeYouTube: @fanalyticsmikeTikTok: @fanalyticspodcast