Great end result. Good work.
Budget: 110 EUR Deadline: 2 days
Hi Joachim.
I have to say that I have recently worked on a web scraper for a college project, not just that I have also created a Streamlit application for the scraped data to view and analyze the data using dynamic charts.
Python is one of my storng skills since I have been building so many data projects using it.
for your project, I can scrap the data, clean it, and give you a Streamlit app that you can view live whenever it updates without the need for further coding. Or if you don't need the app and want me to work on the unfinished app you alredy have I can do it too.
feel free to contact me to start working on the project.
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Budget: 450 EUR Deadline: 5 days
Hi, Thanks for the detailed breakdown. I’ve worked on similar scraping projects, including high-volume sports data collection and proxy-based stealth automation. For Sofascore, I can build you a Python library with well-structured functions that return upcoming matches, historical match stats, player info, and rankings—all through fast and resilient scraping.
My plan is to use `httpx` with `curl_cffi` and session rotation, matching headers and device fingerprints precisely. To avoid 403 errors on long scraping runs, I’ll optimize proxy handling and retry logic. The functions will output clean pandas DataFrames with raw JSON payloads per record so you can explore or store the data easily.
I’d also propose caching session tokens or cookies when possible to reduce authentication overhead and detect anti-bot behavior early. If you have your current football script, I’d be glad to improve on it directly.
Could you confirm if you already have a proxy provider, or would you like me to recommend a better one based on your volume?
Looking forward to working with you.
Best,
Daniel
Yelisey H.
Winning proposal
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Budget: 110 EUR Deadline: 2 days
Good afternoon!
I am ready to implement your project in Python using requests to the internal API of Sofascore.
✅ What I will do:
Write a stable Python script (library/function) that will parse data on tennis matches from Sofascore (odds, statistics, ATP and WTA rankings, etc.).
Provide a convenient interface for obtaining data in JSON format and pandas DataFrame.
Solve the problem with blocking (error 403) by using reliable header rotation and proxy (if needed — I am ready to offer tested solutions with residential proxy).
⚙️ Stack:
Python (requests, pandas)
Internal API requests JSON directly to the server (without browser automation)
🚀 I guarantee:
Data stability and accuracy
High speed (hundreds of thousands of requests per day)
Clean and understandable code with comments
Cost: 110 EUR
Deadline: 3 days
Available for clarifying details!
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Budget: 450 EUR Deadline: 5 days
Hello Joachim,
I've carefully analyzed your project to scrape tennis data from Sofascore. This is a challenging task, and I have the expertise to build the robust, high-speed solution you need.
The 403 error you are encountering with your current script is a clear sign that Sofascore is successfully "fingerprinting" and blocking your requests. A simple curl_cffi approach with basic headers and proxies is often not enough for a target this sophisticated.
To solve this, I will build a professional-grade scraping library in Python using a much more powerful architecture:
Core Engine (Playwright): I will use Playwright, not just a requests library. This allows us to automate a real browser instance, making our script's behavior nearly indistinguishable from a human user.
Advanced Anti-Fingerprinting: I will implement stealth techniques to avoid detection. This includes creating custom browser "contexts" with randomized user agents, screen resolutions, and other browser-level properties that anti-bot systems look for.
Intelligent Request Management: The script will be designed to mimic human Browse patterns, not just make rapid-fire requests. It will also handle proxy rotation intelligently to minimize the risk of IP blocking.
As a PCAP™ certified Python developer, I specialize in building these kinds of reliable data extraction systems. The final deliverable will be a clean Python library with functions like get_upcoming_matches(), get_historical_data(match_id), etc., that return the data in a DataFrame as you requested.
Total Estimate:
Timeline: 5 days
Price: $450 USD
Your budget of €110 is unfortunately not sufficient for developing a system that can bypass a modern anti-bot solution at the scale you require. My price reflects the development of a professional tool that will be fast, reliable, and capable of handling your data needs.
I am ready to build a scraper that truly works.
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Budget: 110 EUR Deadline: 2 days
Good evening, I can help you with your project, I also have experience in this field. Write to me and we will discuss all the details.
22
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Budget: 110 EUR Deadline: 1 day
Hello..
I did something similar for football for the flashcore website. (it's in the portfolio). Approximately 2,000 matches per minute in speed. If this option suits you, I suggest discussing it in more detail in private messages.
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