Creating an insight involves first selecting your country dataset, creating your target audience, choosing a timeframe to view through, and looking at your audience through the lens of your chosen primary question.
STEP 1: Country
Select the country (once you select the country, the ages available for that country will be displayed)
STEP 2: Audience & Demographics
Select from the available demographics:
Age Ranges
Gender
Income
Race
Ethnicity
STEP 3: Filters
Choose from filters based on specific fan bases and favorite teams (optional). Decoder™ utilizes a 7=point Likert Scale to measure fan base avidity/interest. A casual fan is defined as 2-7 on the Likert Scale while avid fan is defined as 6-7. For favorite team, it is a combination of the top 3 ranked teams by respondents for each respective league.
NFL Fan (2-7)
NBA Fan (2-7)
MLB Fan (2-7)
NHL Fan (2-7)
MLS Fan (2-7)
WNBA Fan (2-7)
NWSL Fan (2-7)
ATP Men’s Tennis Fan (2-7)
WTA Women’s Tennis Fan (2-7)
PGA Men’s Golf Fan (2-7)
LPGA Women’s Golf Fan (2-7)
World Wrestling Entertainment Fan (2-7)
English Premier League Fan (2-7)
Formula 1 Fan (2-7)
La Liga Fan (2-7)
NFL Avid Fan (6-7)
NBA Avid Fan (6-7)
MLB Avid Fan (6-7)
NHL Avid Fan (6-7)
MLS Avid Fan (6-7)
WNBA Fan (6-7)
NWSL Fan (6-7)
ATP Men’s Tennis Fan (6-7)
WTA Women’s Tennis Fan (6-7)
PGA Men’s Golf Fan (6-7)
LPGA Women’s Golf Fan (6-7)
World Wrestling Entertainment Fan (6-7)
English Premier League Fan (6-7)
Formula 1 Fan (6-7)
La Liga Fan (6-7)
Favorite NFL Team (in top 3 rank)
Favorite NBA Team (in top 3 rank)
Favorite MLB Team (in top 3 rank)
Favorite NHL Team (in top 3 rank)
Favorite MLS Team (in top 3 rank)
Favorite English Premier League Team (in top 3 rank)
Favorite Formula 1 Team (in top 3 rank)
Favorite La Liga Team (in top 3 rank)
STEP 4: Questions
General level of interest in sports
Sports watched/followed & follow behavior (e.g. watch favorite team only)
Participation in sports as a child/adult
Sports followed
Why not interested in sport
While not interested in these leagues, have you ever been a fan
Age became a Fan of favorite team(s)
How became a fan (favorite individual athletes/drivers/fighters)
How became a fan (favorite teams)
Impact of participation as a child
Reasons for interest (league)
Fan Avidity by league: 7-point scale
Net Promoter Score
What would make league(s) of more interest
Fan Avidity by Event: 7-point scale
Follow national teams (by sport)
Reasons for interest (event/competition)
Favorite teams by league (in top 3 rank)
Reason for not having a favorite team
Frequency of attendance (by league)
If (foreign) league played nearby, level of interest to attend
Attendance in past 12 months by major entertainment type (concerts, sports, etc.)
Frequency of watching/attending your local/favorite team (by league – all games, post-season only, etc.)
Frequency of engagement by activity (e.g. follow athletes on social, watch games on an app)
Hours per week spent on media activities (by activity)
Platforms used in past week
Platforms used for sports content in past week
Streaming platforms used to view sports content in past week
Media Outlets used for sports content
Spend your spare time outside of work/school
Interest in entertainment and other activities: 7 pt scale
Psychographics
What You Get
You will receive a Microsoft Excel table with the data displaying the results for the question(s), audience, filters and timeframe you selected. The data includes sample sizes and percentage for each response. Please note, if you are interested in market sizing and indexes, please visit https://www.visioninsights.net/contact and enter your contact details and a Vision Insights’ representative will follow-up with you directly.
About the Data
22 Countries
Online survey with probability-based random sampling for reliable, representative results
Over 13,000+ surveys fielded monthly across US, Canada and Mexico
Surveys fielded in 19 additional countries bi-annually in March and September
Larger and more statistically robust sample sizes compared to industry competitors
Youth data is a major priority and Decoder’s data is representative of each country’s population as follows:
