OpenCV
Pandas
Scikit-learn
NumPy
Dataiku
Exploratory
htm.java
Figure Eight
PhantomStat
SofaScore
PhantomStat is a sports analytics platform built for the gap between casual score sites and paywalled pro tools, covering five sports: football, MMA/UFC, MLB, NBA and tennis.
Football โ free preview pages for 1,230+ teams and 1,960+ players, with modules for Attack vs Defense (xG/shots/goals), Form Index & Rebound, Goal Geolocation Map, Cards Intelligence, Corner Mastery, Top Scorers Cross-Ref, Referee Tendency, Goalkeeper Weakness and Penalty Shot Tracker.
MMA/UFC โ 465+ fighters, 180+ analyzed fights. Free preview shows per-minute striking/grappling rates, KO Power and Cardio scores, a Performance Explorer (set any stat line, see how often the fighter clears it) and Opponent Level context. Pro unlocks the round-by-round Fatigue Curve and Strike Targets & Control breakdown.
MLB โ eight modules: Plate Discipline Lab, Statcast Quality Hub, Performance Spectrum, Situational Splits Matrix, Today's Matchup, Pitcher Arsenal, WAR Decomposition and a Similarity Engine.
NBA โ 30 teams, 500+ players, live matchups. Form Explorer across PTS/REB/AST/3PM/PRA, Opponent Defense, Rest/Back-to-Back splits, a Filter Engine and a multi-line threshold view.
Tennis โ career averages (win rate, holds/breaks serve, serve/return splits, aces, unforced errors, tiebreak% and deciding-set%) on every ATP player page.
Browsing is free with no signup. A free account adds saved watchlists and personalized dashboards; Pro unlocks the advanced modules sport-wide.
OpenCV
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PhantomStat's answer:
PhantomStat started from a simple gap: casual sports sites stop at the final score and a season average, while the analytics that go deeper are built for professionals and locked behind expensive tools. The goal was to put real per-entity detail โ xG and PSxGA for soccer, round-by-round fatigue curves for MMA, matchup splits for MLB, opponent-defense splits for NBA, serve/return breakdowns for tennis โ in front of any fan for free, with a paid Pro tier reserved for advanced filtering rather than for basic access to the numbers.
PhantomStat's answer:
Sports fans who want more than a final score, and fantasy/simulation players who need the underlying splits rather than a season average. That covers casual fans checking a player's recent form, fantasy managers comparing matchup histograms before setting a lineup, and anyone who follows football, MMA, MLB, NBA or tennis closely enough to want per-round, per-game or per-matchup detail instead of a single headline stat.
PhantomStat's answer:
PhantomStat covers five sports in one platform โ football, MMA, MLB, NBA and tennis โ with dedicated pages per player, team, fighter and matchup. Instead of just headline numbers, each page surfaces the underlying breakdown: xG and PSxGA for football, per-round fatigue curves for MMA, a Prop Line Explorer with histograms for MLB, form and opponent-defense splits for NBA, and serve/return breakdowns for tennis. Browsing is free with no signup required; a paid Pro tier ($29.99 / โฌ29.99 / ยฃ24.99 per month) unlocks advanced filtering and the full historical archive.
PhantomStat's answer:
Most single-sport score sites stop at the headline number, and most deep-analytics tools paywall everything before you can see anything. PhantomStat lets you browse every player, team, fighter and matchup page with no signup required, and covers five sports in one account (football, MMA, MLB, NBA, tennis) instead of forcing you to juggle a separate tool per sport. Pages are built for search too โ SEO-friendly URLs mean a specific player or matchup is usually one search away.
Based on our record, OpenCV seems to be more popular. It has been mentiond 62 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
OpenCV is the world's largest open-source computer vision library, supported by the non-profit organization, Open Source Computer Vision Foundation. It offers a wide range of algorithms that cover a variety of tasks, from basic image processing to advanced object recognition and motion analysis. - Source: dev.to / 8 months ago
Google's Gemini and other multimodal models also fit here, especially for mixed-input apps. James Allsopp, Founder of Ask Zyro, suggests, "For anything involving images or mixed inputs, tools like Claude 3 Opus (great for handling long context) or Google's Gemini can work well, depending on what you need for your user interface." These frameworks excel in scenarios requiring visual understanding, such as augmented... - Source: dev.to / 12 months ago
To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isnโt just a tool, itโs a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that donโt just interpret visuals, but... - Source: dev.to / about 1 year ago
Ideal For: Computer vision, NLP, deep learning, and machine learning. - Source: dev.to / over 1 year ago
Almost everyone has heard of libraries like OpenCV, Pytorch, and Torchvision. But there have been incredible leaps and bounds in other libraries to help support new tasks that have helped push research even further. It would be impossible to thank each and every project and the thousands of contributors who have helped make the entire community better. MedSAM2 has been helping bring the awesomeness of SAM2 to the... - Source: dev.to / over 1 year ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
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Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
NumPy - NumPy is the fundamental package for scientific computing with Python
Dataiku - Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.
Exploratory - Exploratory enables users to understand data by transforming, visualizing, and applying advanced statistics and machine learning algorithms.