Demo:

Alex - Player Filter

Dhanish - 1st feature in our report (just the flow of seeing teams' standing in a year, players who played in that year, team stats, player stats for that year etc.)

Tianchang - Accounts

Calder - Fantasy team & Team Evaluator

To host the app locally:

change to source code directory

cd src/

download all required libraries

pip3 install -r requirements.txt

host server locally

python3 manage.py runserver

NOTE: You might not be able to host the app locally because the Lib folder is not present.

We removed Lib folder in order to keep the size within Markus upload maximum.

To access the app deployed by GCP:

Go to: https://bball-analytics.appspot.com/

Information regarding Milestone 02:

Files related to Database Design Schema can be found under /Report directory

You can find the schema definition of all the tables under /sql/tables You can find test-sample.sql and test-sample.output under /sql

Within our application, see /src/teams/models.py and /src/players/models.py:

1. For code that creates our tables
2. For code that uses pandas to scrape real data from csv files to populate the tables "TeamsInfo", "TeamStats", "Player" and "PlayerStats"

url for data found in:

(https://www.kaggle.com/drgilermo/nba-players-stats?fbclid=IwAR3Ch4TslrxGwKE4iaEBuwidrFVzsQ6oY4oQMJu_X5xjo__5svRcowjyHgo) - and (https://www.kaggle.com/open-source-sports/mens-professional-basketball) - we have csv's in github already

test-production.sql and test-production.out found under /sql directory

Features implemented so far (We used Django to implement a simple Database-Driven Application):

1. That displays all unique basketball teams that have played since the 1930's
2. That takes year as a user input and displays all basketball teams that played in that particular year. User Input comes through a drop-down menu of years
3. Click on a team to see all years the team played in. Then select a year which will then display the selected team's performance summary for that year. You may then click the button to display all players who played for this team in the selected year. (NOTE: List of players may be missing for some of the earlier years ex: 1930's '40's etc.) Finally, you can click on any of the players to view their stats when they played for the selected team in the selected year.
4. The view 36 min caculates the average data(include, PER, TS%, offensive rating, defensive rating, rebound rate, game score, etc) in a period of 36 min. This advanced metrix is very helpful when interpreting given data for each player and team.
5. Player filter: Allow user to check the season statistics for players that satisfy the user's input. For example, user may search for players who played from 2000 to 2010 as a shooting guard and had a score rate more than 65%.

Relevant source code can be found under:

1. /src/teams/models.py
2. /src/teams/views.py
3. /src/players/models.py
4. /src/players/views.py

test-production.sql and test-production.out can be found under sql/