-
8th Grade
- Project
- 1 week
"Superbowl Stats Showdown: Predict the Winner!"
CCSS.Math.Content.8.EE.B.5
CCSS.Math.Content.8.F.A.3
CCSS.Math.Content.8.F.B.4
Purpose
Students will engage in a dynamic exploration of NFL Superbowl data to uncover patterns and make predictions using mathematical concepts. By analyzing past game statistics, students will graph proportional relationships and interpret unit rates as slopes, while comparing different representations of data. They will construct linear functions to model relationships between game variables, determining rates of change and initial values. This project encourages critical thinking and application of math standards in a real-world context, fostering a deeper understanding of linear relationships through hands-on investigation.
Learning goals
Students will analyze data from past NFL Superbowls to understand and apply concepts of proportional and linear relationships. They will graph proportional relationships and interpret the unit rate as the slope, comparing different representations of these relationships. Students will construct linear functions to model real-world data, determining rates of change and initial values from graphs and tables. Through this project, students will develop skills in interpreting equations and analyzing data to predict future outcomes, aligning with key mathematical standards.
Standards
- CCSS.Math.Content.8.EE.B.5 - Graph proportional relationships, interpreting the unit rate as the slope of the graph. Compare two different proportional relationships represented in different ways.
- CCSS.Math.Content.8.F.A.3 - Interpret the equation y = mx + b as defining a linear function, whose graph is a straight line; give examples of functions that are not linear.
- CCSS.Math.Content.8.F.B.4 - Construct a function to model a linear relationship between two quantities. Determine the rate of change and initial value of the function from a description of a relationship or from two (x, y) values, including reading these from a table or from a graph. Interpret the rate of change and initial value of a linear function in terms of the situation it models, and in terms of its graph or a table of values.
Products
Students will create a predictive model using data from past NFL Superbowls to forecast outcomes of future games. They will graph proportional relationships, analyze unit rates, and compare different representations to determine patterns. Students will construct linear functions to model relationships between game statistics, interpreting rates of change and initial values. By the end of the project, students will present their findings through a visual display, such as a poster or digital presentation, showcasing their graphs and models with explanations of their predictions.
Launch
Kick off the project by having students watch highlights from recent NFL Superbowls and discuss key factors that contribute to a team's success. Introduce the concept of proportional and linear relationships by examining player statistics, such as yards gained per game or touchdowns scored per season. Engage students in a hands-on activity where they create graphs of these statistics to identify patterns and predict outcomes. Encourage students to collaborate in small groups to explore different data sets and develop hypotheses about future Superbowl results based on their analyses.
Exhibition
At the end of the project, students will host a "Superbowl Predictions Showcase" where they present their data analysis and predictions for future games to classmates, teachers, and family members. They will create visual displays, such as graphs and tables, that illustrate their understanding of proportional and linear relationships in the context of NFL Superbowl statistics. Students will also explain their reasoning and the mathematical concepts applied in their predictions, fostering a deeper understanding and appreciation of math in real-world contexts.
Week 1 | Day 1 |
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Activities |
Introduction to NFL Superbowl Data - Students watch highlights from recent NFL Superbowls and discuss key factors that contribute to a team's success, setting the stage for data analysis. (15)
Understanding Proportional Relationships - Students explore player statistics, such as yards gained per game, and create graphs to identify proportional relationships and interpret unit rates as slopes. (30)
Group Collaboration and Hypothesis Development - Students form small groups to analyze different data sets and develop hypotheses about future Superbowl results based on their analyses. (15)
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Deliverables |
1. Graph of proportional relationships using NFL Superbowl data
2. Constructed linear functions for modeling relationships between game variables 3. Predictive model, presented visually with an explanation |
Preparation |
1. Compile recent NFL Superbowl highlights for kickoff activity
2. Provide datasets of player statistics from past Superbowls 3. Prepare graphing tools (graph paper, rulers, or digital graphing software) 4. Set up a space for the 'Superbowl Predictions Showcase' 5. Ensure access to materials for creating visual displays (poster boards, markers, or digital presentation tools) |