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Smart Draft Board is a fantasy sports analytics platform covering AFL SuperCoach, AFL Fantasy, NRL SuperCoach, FPL Draft, FPL Classic, and Fantrax โ all under one login. At its core is a GAMM (Generalised Additive Mixed Model) projection engine trained on 140,000+ player-round observations across five sport and platform combinations. Each stat is modelled independently with partial pooling and confidence tiers (AโD), so coaches know which projections to trust. Projections adapt per platform โ the same player gets different scores for SuperCoach vs AFL Fantasy because scoring weights differ. Draft tools include VBD-powered rankings (Value Over Replacement Player), a bye planner, Smart Rank composite scoring, mock drafts against AI opponents, and a shareable draft board with real-time pick tracking. For Classic/salary cap formats, the Salary Cap Lab provides PPD rankings, a position grid builder, budget tracker, price prediction, cash cow sell signals, a trade simulator, and a six-dimension team health score. Season Mode covers 14 phases of in-season management: waiver wire, trade planner, fixture heatmap, weekly dashboard, captain picker, lineup optimizer, round review, power rankings, trade grades, draft tracker, season timeline, matchup mode, price prediction, and injury intelligence. The Projection Studio lets coaches build custom profiles by blending GAMM models, recent form, career baselines, and manual per-stat overrides โ with Monte Carlo simulations showing full score distributions. League Sync connects SuperCoach, AFL Fantasy, FPL, or Fantrax accounts to import rosters, matchups, and scoring automatically. Every recommendation then tailors to the coach's actual squad. A generous free tier includes full rankings, projections, and draft board. Pro ($39.99/yr AUD) unlocks Season Mode, Salary Cap Lab, unlimited projection profiles, live league sync, Monte Carlo simulations, and scenario analysis.
Plotly
Smart Draft BoardPlotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.
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Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 4 months ago
Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / over 1 year ago
Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / over 1 year ago
In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / over 1 year ago
How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / about 2 years ago
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