Tell the best visual story about college basketball attendance. Using the provided NCAA attendance dataset, students will design a data visualization that answers the central question: What story does the data reveal about basketball attendance, e.g., what factors appear to influence it?
Examples of story angles may include:
- Attendance trends over time
- Impact of conference strength or rivalry
- Relationship between wins and attendance
- Geographic patterns and fan engagement
Check the mentorship tab for optional drop-in Data Viz Studio Sessions for extra support.
What is in the dataset?
This dataset contains information about NCAA women’s basketball games across multiple seasons. Each row represents one team participating in one game. Because every game has two teams, each game appears twice in the data: once for each team. The data includes information about when and where games were played, team characteristics, game outcomes, and attendance. Some variables are incomplete, which reflects the reality of working with real-world data.
Data Dictionary
Below is a description of each column in the dataset. All columns are explained in plain language. If a value is missing, it means that information was not available for that particular game or team.
| Column Name | What This Means |
| CONTEST_ID | A unique ID number for each game. Each game appears twice (once per team). |
| CONTEST_DATE | The date when the game was played. |
| CONTEST_DATE_UTC | The game date and time in a standardized global time format. |
| ACADEMIC_YEAR | The academic year in which the season took place. |
| FACILITY_CITY | The city where the game was played. |
| FACILITY_STATE | The state where the game was played. |
| FACILITY_POSTAL_CODE | The ZIP code of the game location. |
| FACILITY_LATITUDE | The latitude of the game location (used for mapping). |
| FACILITY_LONGITUDE | The longitude of the game location (used for mapping). |
| TEAM_INSTITUTION_ID | A unique ID number for the team’s school. |
| TEAM_INSTITUTION_OFFICIAL_NAME | The school’s official name. |
| TEAM_INSTITUTION_NAME | The commonly used name of the school. |
| TEAM_INSTITUTION_CITY | The city where the school is located. |
| TEAM_INSTITUTION_STATE | The state where the school is located. |
| TEAM_INSTITUTION_ZIP | The ZIP code of the school. |
| TEAM_INSTITUTION_LATITUDE | The latitude of the school’s location. |
| TEAM_INSTITUTION_LONGITUDE | The longitude of the school’s location. |
| IS_INSTITUTION_HBCU | Indicates whether the school is a Historically Black College or University (Yes/No). |
| TEAM_INSTITUTION_DIVISION | The NCAA division the team competes in. |
| TEAM_CONFERENCE | The athletic conference the team belongs to. |
| TEAM_INSTITUTION_FEMALE_ENROLLMENT | Number of female students enrolled at the school. |
| TEAM_INSTIUTION_MALE_ENROLLMENT | Number of male students enrolled at the school. |
| TEAM_INSTITUTION_TOTAL_ENROLLMENT | Total student enrollment at the school. |
| IS_HOME_CONTEST | Indicates whether the game was played at one team’s home venue. |
| IS_SITE_NEUTRAL | Indicates whether the game was played at a neutral site. |
| IS_CONFERENCE_CONTEST | Indicates whether the game was a conference game. |
| IS_TEAM_HOME_TEAM | Indicates whether this team was the home team in the game. |
| IS_TEAM_WINNER | Indicates whether this team won the game. |
- Visualization must be original student work
- Must clearly communicate a data-driven story
- Should include clear narrative framing, effective design, and explanation of insights
Submissions should be emailed to dataviz@iu.edu by March 11, 11:59 p.m. EST as a png file embedded in a Word document with a 150–250 word description.
Optional Drop-In Data Viz Studio Sessions
To support interested students and educators, Indiana University Indianapolis sport data enthusiastic faculty and students will host optional, virtual Data Visualization Studio Sessions. These are drop-in learning sessions, designed to help students get started, ask questions, and refine their work at any stage of the project.
What Are the Data Viz Studio Sessions?
The studio sessions are informal, open Zoom sessions where students can:
- See short visualization demonstrations
- Learn how to work with the competition image and dataset
- Ask questions or get help if they’re stuck
- Listen in without participating live
Attendance is not required to participate in the challenge, and students may join any session for as long or as little as they like.
Studio Session Dates (Optional)
• Feb 18 | 7:00–8:00 PM ET
• Feb 25 | 7:00–8:00 PM ET
• Mar 4 | 7:00–8:00 PM ET
Each session will focus on practical guidance and common questions, and students can attend one, multiple, or none of the sessions.
How to Access the Sessions
To receive the Zoom link for the Data Viz Studio Sessions, please complete the form below.
https://iu.co1.qualtrics.com/jfe/form/SV_eL3l1cPyDk00lVQ
Can’t Attend the Live Sessions?
If the session times do not work for you, please email dataviz@iu.edu and we’re happy to share guidance, resources, and answer questions.
A panel of NCAA representatives and IU Indy sport analytics faculty and students will judge submissions. The winning individual or team will receive tickets to Men’s Final Four fan events.
If you are experiencing technical issues, have questions, or concerns, don't hesitate to reach out to dataviz@iu.edu.
