Hey everyone, I’m currently working on a project where I’m building a kill prediction model for CS2 players, and I’m looking for a dataset with all the relevant stats that could help make this model accurate.

Ideally, I’m looking for a dataset that includes detailed player-level and match-level statistics, such as: • Player ratings (e.g., HLTV rating 2.0, impact rating) • Kills per round, deaths per round, damage per round • Headshot percentage, opening duels (won/lost), clutch stats • Match context (opponent team rank, map played, event type, BO1/BO3, etc.) • Team-level metrics (team ranking, recent form, match odds)

If anyone has scraped something like this or knows where I can find it (CSV, SQL, JSON — anything works), I’d really appreciate it. I’m also open to tips on how to collect this data if there’s no clean public source.

Thanks in advance!

Hi All,
I am a data scientist who wants to use the Parish Register Aggregate Analyses, 1662-1811 dataset hosted by UK Data Service. However, I am not affiliated with a UK college or university so I cannot login.

I am requesting that someone affiliated with a UK higher ed institution download the dataset for me. The dataset is located here: https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=4491

Thanks!

Hi! Has anyone here used football-api.com before?
I’m trying to get fixtures for FINLAND: Suomen Cup matches scheduled for tomorrow. I’m using 2025 as the season and sending the following request

Any idea when newer seasons like 2024 or 2025 will become available on the free tier?
Weirdly enough, it worked just yesterday for the 2024 English Premier League — now both 2024 and 2025 seem blocked?

 "get": "fixtures", "parameters": { "league": "135", "season": "2025", "from": "2025-05-27", "to": "2025-05-29" }, "errors": { "plan": "Free plans do not have access to this season, try from 2021 to 2023." }, "results": 0, "paging": { "current": 1, "total": 1 }, "response": [] 

Need data to work on disease detection project for saffron. Please help to provide relevant data sets in regards to this.

Im a high school student doing a science fair project on AI and waste identification and i cannot find any datasets that focus on this for the life of me. Hoping you all will have something to help me out.

I’m currently working on a project that involves analyzing the global natural gas markets. While I’ve found a valuable dataset for Europe specifically, Bruegel’s European natural gas imports dataset I’m looking to expand my research to include other regions and obtain more comprehensive data.

Could anyone recommend reliable datasets or APIs that provide up-to-date information on natural gas markets, including aspects like prices, production, consumption, imports/exports, and storage levels? I’m particularly interested in data that covers regions beyond Europe, such as North America, Asia, and the Middle East.

Any suggestions or pointers to resources would be greatly appreciated!

I’m looking for a dataset that includes crawled onion links with titles and descriptions or site content, I’ve been crawling myself and made a filter to remove CP but due to the speed of the TOR network it’s quite a slow process and all the datasets I could find were outdated, these sites go down a lot,

any help would be appreciated, thanks!

Can someone tell me where collect Data about Soil data collection Climate data Market Data of crops

https://huggingface.co/datasets/AmarAleksandr/OusiaBloom

Ousia Bloom is an evolving, open-source record of personal consciousness made for the future. Mostly Incoherent now.

Using data from the excel file and coding in Python, you should now estimate the following: for each ETF, estimate the sensitivity of ETF flows to past returns. a. Write down the main regression specification, and estimate at least five regression models based on it (e.g., with varying the number of lags). Then, present the regression output for one ETF of choice, including coefficients with t-stats, R squared, and number of observations.

a. Estimate the OLS regression from (2a) for each ETF and save betas. Then, conduct cluster analysis using k-means clustering with different variables, but for a start, try these two dimensions: i. Flow-performance sensitivity (i.e., betas from point (2)) vs fund size (AUM). ii. Propose at least one other dimension, and perform the cluster analysis again. What did you learn? iii. Now, instead of clustering, analyse fund types, and see whether flow- performance sensitivity varies by fund type.

dm me so that I can send you the cleaned up data

Hi everyone,

Any ideas on how I could have access to IEA’s World Energy Outlook 2024 extended data set (without paying 23k€) ? I am doing research on the storage solutions and would need to have their data on pumped hydro, batteries behind the meter and utility scale, and others. This for their NZE, STEPS and APS scenarios. Thanks for the help !

I am looking for official compliance account data for bank data. I looked FDIC office of comptroller and see lots of regulations which is great but not any sample data I could use. This doesn’t have to be great data just realistic enough that scenarios can be run.

I know that if your working with bank you will get this data. However it would be nice to run some sample data before I approach a bank so I can test things out.

Hi! I am trying to build a ML model to detect Reddit bots (I know many people have attempted and failed, but I still want to try doing it). I already gathered quite some data about bot accounts. However, I don’t have much data about human accounts.

Could you please send me a private message if you are a real user? I would like to include your account data in the training of the model.

Thanks in advance!

Hi i’m looking for datasets which contains accurate vulnerabilties related to 5G, this could be really useful for my thesis project.

Hi everyone,

I’m sharing a dataset I built while working on a recent project where I needed a list of countries and cities with accurate Arabic translations and population data.

I checked out several GitHub repositories but found most were:

• Incomplete or had incorrect translations
• Missing population info
• Not consistently formatted
• Labeled incorrectly — many included states but called them cities

So I decided to gather and clean the data myself using trusted sources like Wikidata, and I’m making it publicly available in case it helps others too.

What’s included:

• Countries
• Cities
• Arabic and English names
• Population data (where available)

Available formats:

• CSV
• Excel (.xlsx)
• JSON
• JSONL
• SQL insert script

All files are open-source and available here:

🔗 https://github.com/jamsshhayd/world-cities-translations

Hopefully this saves other developers and data engineers some time. Let me know if you’d like to see additional formats or data fields added!

Finishing up a report for work. I’ve obtained US Government info and Canadian Government Info. I am looking for import data by country and KGs for HS Code 7226.11 and 7225.11.

I’ve tried importyeti and websites like that but the data seems incomplete. Is there a Mexican government website that would offer this information?

i would like to train a model to estimate the mood of a 1to1 chat, a good starting point would be a classic sentiment analysis dataset that labels each one of the messages as positive or negative (or neutral) or even better that assigns a score for example in the range of [-1,1] for the “positiveness” of the message, but ideally the perfect dataset for my goal would be a dataset of full conversations, i mean, every data point should be a series of N messages from both the sides in which all the messages have the same context, for example if i message a friend asking for his opinion about a movie the single datapoint of the dataset should contain all the messages we send each other starting from my question until we stop talking and we go doing something else, does someone know if there’s a free dataset of any of these types?

Hi,

Requesting any links/references to dataset that contains the login and logout time of employees (any format is fine)

Hello Reddit,

I’m currently conducting research and am looking for a comprehensive dataset or source that lists telemedicine companies or startups along with the names of their CEOs and websites. Ideally, I’d prefer a structured format such as CSV, Excel, or a Google Sheet, but even a reliable list or database would be helpful.

If anyone has compiled this information or knows where I could find it (public databases, APIs, industry reports, etc.), your guidance would be greatly appreciated.

Thank you in advance!

Hi all, so I am trying to find some open source data or datasets for academic research on data centres and their energy consumption. Can someone help with some resource or if they know where this could be found, since I’m unable to find any datasets on this.

I built an MCP server that works a little differently than the Cloudflare AutoRAG MCP server. It offers control over match threshold and max results. It also doesn’t provide an AI generated answer but rather a basic search or an ai ranked search. My logic was that if you’re using AutoRAG through an MCP server you are already using your LLM of choice and you might prefer to let your own LLM generate the response based on the chunks rather than the Cloudflare LLM, especially since in Claude Desktop you have access to larger more powerful models than what you can run in Cloudflare.

I have always wondered how large companies arrange their subdomains in a pattern ! As a result of my yesterday’s efforts, I have managed to upload a dataset on kaggle containing sub-domains of top tech companies. It would be really helpful for aspiring internet startups to analyse sub-domain patterns and embrace them to save the precious time. Sharing the link for datasets below. Any feedback is much appreciated. Thanks.
Link – https://www.kaggle.com/datasets/jacob327/subdomain-dataset-for-top-tech-companies

I am responsible for data acquisition for a project where we are assessing the impacts of hurricanes Katriana and Rita for work.

We are interested in impacts relevant to the coastal and environmental health, healthcare, education, and the economy. I have already found FBI crime data, and am using the rfema package in rstudio to get additional data from Fema.

Any other suggestions? I have checked out USGS already and cant seem to find one that is especially helpful.

Thanks!

hey! just wanted to share an update, a while back I posted about a tool I was building to generate synthetic datasets. I had said I’d share it in 2–3 days, but ran into a few hiccups, so sorry for the delay. finally got a working version now!

right now you can:

• give a query describing the kind of dataset you want
• it suggests a schema (you can fully edit — add/remove fields, tweak descriptions, etc.)
• it shows a list of related subtopics (also editable — you can add, remove, or even nest subtopics)
• generate up to 30 sample rows per subtopic
• download everything when you’re done

there’s also another section I’ve built (not open yet — it works, just a bit resource-heavy and I’m still refining the deep research approach):

• upload a file (like a PDF or doc) — it generates an editable schema based on the content, then builds a dataset from it
• paste a link — it analyzes the page, suggests a schema, and creates data around it
• choose “deep research” mode — it searches the internet for relevant information, builds a schema, and then forms a dataset based on what it finds
• there’s also a basic documentation feature that gives you a short write-up explaining the generated dataset

this part’s closed for now, but I’d really love to chat and understand what kind of data stuff you’re working on — helps me improve things and get a better sense of the space.

you can book a quick chat via Calendly, or just DM me here if that’s easier. once we talk, I’ll open up access to this part also

try it here: datalore.ai

I’m having such a difficult time dealing with edge cases to clean up 50k leads to be imported into our CRM. I’ve tackled this with multiple Python scripts but the accuracy is still too low and producing too many edge cases for manual changes. Is there an AI that can simply look at a name and assign whether it’s a company or human?

Good evening, I need one comprehensive data set for manufacturing facility, to perform the following in an academic project:

1- Forecasting (Exponential Smoothing)

2- Aggregate Planning

3- Material Requirements Planning (MRP)

4- Inventory Management

Could anyone help?