The Big Game is the annual American football championship and one of the most celebrated events in the history of sports. It is not only one of the most-watched sports events across the globe, it also has the reputation of being the second-largest day in terms of food consumption in the US. Every fan eagerly waits for the Game Day to find out if their favorite team wins.
A sports betting firm has utilized the data augmentation technique to synthesize a data set of championship outcome of the Big Game's participants and other data. Your task is to generate a model to determine and classify whether a given team will win the championship or not.
Data
Data Files
train.csv : contains the training data [6500 x 9]
test.csv : contains the test data [3500 x 8]
sample_submission.csv : example for submission format of Results.csv
Data Description
| Columns | Description |
| ID | A unique identifier for the record |
| Average_Player_Age | Average age of the players on the team |
| Coach_Experience_Level | Level of experience of the head coach |
| Number_Of_First_Round_Draft_Picks | Number of players on the team that were first round draft picks |
| Number_Of_Injured_Players | Number of injured players on the team |
| Number_Of_Wins_This_Season | Number of wins that the team has leading up to the Big Game |
| Playing_Style | Represents playing style in levels |
| Previous_SB_Wins | Number of times the team has won the game in the past |
| Team_Value | Total value of the team in USD [Less than four billion implies greater than 3 billion] |
| Won_Championship [Target] | 1 signifies winning the game 0 signifies losing the game |
Submission Format
You are required to your predictions in a .csv file and upload it to 'Upload File'.
Evaluation Criteria
score=100∗f1_score(actual_values,predicted_values,average=′binary′)
