This project aims to leverage business intelligence techniques to conduct a comprehensive analysis of NBA player statistics, team performance metrics, and social media engagement during the 2016-2017 season. I aim to extract valuable insights that can empower General Managers (GMs) of NBA teams in making strategic decisions for their team.
The objective of this project was to create a complete dashboard for NBA team managers and executive teams. These dashboards will provide insights into player performance, salary justification, fan engagement, team performance and other key metrics. The dashboard aimed to help with decision-making processes and strategic planning within the organization for better success of the team.
The objective of this dashboard is to provide a comprehensive overview of NBA player salary caps for the 2017-2018 season, along with detailed player draft numbers linked to each player. The dashboard offers insights into team spending, player salaries, and the distribution of player ages within various positions. This report is found under the “Player Salary” section.
- The dashboard displays a summary of each NBA player’s total salary cap for the year 2017. This allows users to quickly compare spending across players and identify high-earned and low-earned players.
- The linked dataset provides detailed information about each player and their corresponding salaries for the year 2017-2018. Users can explore this data to understand which players contribute to the league in that season. We can identify any particularly high-earning players while reviewing their performance from the player and team performance dashboards in this project.
- The slicer report allows users to select a specific age range for NBA players. This functionality enables users to filter player data based on age.
- The dashboard is interactive, allowing users to drill down into specific teams or players for more detailed information. For example, clicking on a player name will reveal player salaries, or selecting a specific age range will dynamically update the displayed player data.
- Comprehensive Salary Overview: Provides a clear summary of player salaries for the 2017-2018 season, aiding in quick comparison and analysis.
- In-Depth Player Analysis: Linked datasets offer detailed player information, helping users understand player contributions and identify high earners.
- Age-Based Filtering: Age range slicer allows focused analysis on specific age groups, revealing trends in salary distribution.
- Enhanced Interactivity: Drill-down capabilities enable users to access detailed information on specific players or teams, enhancing the depth of analysis.
How to use:
You can see an overview of players' salaries in a complex pie chart. You can begin to filter by adjusting age to your requirement and select a player of your choice to learn more about him. As you type the age, you can see the table drill down on players in that age group. You can select any player and learn what number they were drafted in the NBA and how much they are getting paid. You can understand why high drafted numbers get paid more as they are more skilled. You can select these players from the pie chart and also learn about their details that way. You can also see how age past 35 impacts a player's earnings by a lot as a player starts to perform badly.
Overview
This dashboard provides a high-level overview of social media engagement metrics for NBA players, using data from the 2017 season. It includes three primary social media metrics: Twitter Favourites, Twitter Retweets, and Wikipedia Pageviews. The dashboard displays the influence of these metrics on NBA player salaries, allowing comparisons by position, team, and individual player.
Aggregated Social Media Metrics:
- Display cards at the top show the total values for Twitter Favourites, Twitter Retweets, and Wikipedia Pageviews.
- These cards provide a quick snapshot of each metric's total values and dynamically update when drilling down by team or player.
Key Influencers Analysis:
- The 'Key Influencers' section analyzes various statistics against player salaries (in millions).
- Includes both social media metrics and performance-based game statistics.
- Displays correlations between these statistics and salary increases.
- Grey bubbles indicate the influence of each statistic on salary; the further the bubble, the greater the influence.
- Clicking a bubble opens a chart visualizing the correlation for that particular statistic.
Engagement Metrics Breakdown:
- A bar chart showing average engagement metrics by player position (Point Guard, Small Forward, Centre, Power Forward, Shooting Guard).
- Allows comparisons of social media engagement across different positions.
- Drill-down functionality for detailed breakdowns by team and individual player.
- Helps identify which positions, teams, and players receive the most social media engagement.
- Quick Snapshot of Social Media Metrics: Display cards provide an at-a-glance view of total social media engagement metrics.
- Salary Correlation Analysis: Identifies which statistics (social media and performance-based) correlate with higher salaries.
- In-Depth Engagement Analysis: Detailed breakdowns by position, team, and player help identify trends and discrepancies in social media engagement.
- Marketing and Talent Insights: Useful for marketing teams, talent scouts, owners, and coaches to understand public engagement and player value.
- Strategic Decision-Making: Informs decisions about player salaries, marketing strategies, and talent acquisition based on engagement metrics.
Overview:
The objective of this dashboard is to compare NBA players' endorsement deals, their financial earnings, and their social media presence. It provides insights into the relationship between a player’s market value and their popularity among fans. This report is found under “Engagement Metrics vs. Endorsements and Salary”.
- Market Value Analysis: Provides a clear comparison of player endorsements and salaries against their social media engagement metrics.
- Branding Success Patterns: Identifies successful branding and market value capitalization based on fan engagement.
- Value Representation: Helps determine if a player’s financial earnings (both salary and endorsements) are well-aligned with their popularity and engagement.
- Strategic Decision-Making: Aids owners, coaches, and marketing professionals in making informed decisions about player marketability and financial agreements. reflect their standing from a purely fan engagement perspective.
Objective
The objective of this dashboard is to provide a comprehensive analysis of rookie NBA players' performance based on various statistical metrics. These metrics include games played, points per game, minutes played, field goal percentage (FG%), player efficiency, and more. By comparing the performance of rookie players, the dashboard identifies standout performers and provides insights that can aid in decision-making processes.
Key Features
Performance Metrics Analysis:
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The dashboard evaluates rookies across several key statistical metrics to gauge overall performance.
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Metrics include:
- Games Played
- Points Per Game
- Minutes Played
- Field Goal Percentage (FG%)
- Player Efficiency
- Performance Comparison:
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Enables comparison of rookie players to identify standout performers.
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Highlights players who excel in specific metrics, providing a clear view of top-performing rookies.
Summary of Player Performance:
- Presents a summary of each rookie NBA player's performance statistics.
- Offers a quick snapshot of each player's performance across key metrics for easy reference.
Data Filtering:
- Users can filter player data using the linked dataset.
- Allows focusing on specific players to tailor the analysis to particular needs.
Strategic Decision-Making:
- Assists General Managers (GMs) in making informed decisions regarding player contracts for the next season.
- Provides insights for strategic trade decisions to acquire the right players.
Rookie of the Year (ROTY) Decision:
- Can be used to make informed Rookie of the Year (ROTY) decisions.
- Helps the league identify the best rookie of their class based on comprehensive performance data.
- Informed Contract Decisions: Helps GMs offer appropriate pay to promising rookies for the next season.
- Strategic Trades: Aids in deciding which players to trade for the optimal team composition.
- ROTY Selection: Provides a data-driven approach to selecting the Rookie of the Year.
- Quick Performance Snapshot: Offers an at-a-glance view of rookie performance across key metrics.
- Customizable Analysis: Users can filter and focus on specific players, tailoring the analysis to their needs. How to use:
Users can click on players from the table to drill down to their stats on a right table under Player Stats. Users can also use sliders on scatter charts to zoom in and out of the chart and filter players based on their points per game (PPG) and FG%. Higher the PPG, higher their minutes played in a game. The size of each point on the chart is based on how much time the player is playing the game which helps you visualize top performers. You can also use an efficiency slicer to narrow the search by desired %. All players have their respective stats showcase in a table format which can be customized from the main dataset (CSV file) attached to this dashboard. One can add or remove the category of their choice.
Overview
This dashboard provides a comprehensive analysis of ELO ratings and their impact on player salary decisions and team salary cap management. ELO ratings are a valuable metric for evaluating player performance relative to their peers and the league as a whole. This README explains how ELO ratings influence team strategies and decisions, and how our dashboard can be utilized to gain deeper insights into these dynamics.
Influence on Player Salaries:
- Teams with higher ELO ratings are often more valuable due to their consistent performance and contribution to winning games.
- Players with higher ELO ratings tend to have higher market value, leading to increased salary demands during contract negotiations.
- Teams may offer higher salaries to attract and retain players with high ELO ratings, viewing them as critical assets for team success.
Team Salary Cap Management:
- Teams must balance their roster to stay within salary cap limits while maximizing performance.
- Strategic decisions involve investing in high ELO rating players to enhance team performance and success.
- Higher salaries and longer-term contracts may be offered to top talent to maintain a competitive edge.
Conference Breakdown:
- The dashboard allows for comparison of ELO ratings across all teams, with a detailed breakdown by conference.
- Managers from opposite conferences can evaluate players based on ELO ratings, aiding in better contract negotiations.
- Insights from the dashboard help understand overall league performance in terms of ELO ratings.
Free Agent Market:
- The top 5 teams with the highest ELO ratings are desirable locations for free agents aiming to win championships.
- ELO ratings guide free agents in making informed decisions about joining teams with strong winning potential.
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Performance Assessment: Provides a clear metric for assessing player performance relative to the league.
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Market Value Determination: Helps teams and players determine fair market value during contract negotiations.
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Strategic Decision-Making: Aids teams in making informed decisions about roster composition and salary cap management.
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Financial Flexibility: Ensures teams maintain financial flexibility while optimizing player contributions.
How to use:
The report is designed to be intuitive and user-friendly, allowing users to quickly understand the current state of NBA ELO ratings. You can click on East or West and drill down conference data by looking at teams in each conference. You can also filter each team by simply clicking on the team’s name on a graph and pinpoint exactly where they lie on a graph to compare with other teams. The team you have clicked will be shown on a table with the values you are looking for and understand their ELO rating.
