Paydirt Models, Tools, Whitelisting, and Database Management Offerings

This catalog is to serve as an introduction to the tools, models, and data services at Paydirt that are available for whitelisting as a B2B service. This list will include any Daily Fantasy Sports (DFS) or Sports Betting models/tools as well as Stats and Ownership Projections. Paydirt also offers Data Management and API services for companies that need backend support to assist with scaling and reliability.

Models/tools can be whitelisted in the form of using Paydirt projections and methods or, for an extra consulting fee, can be outfitted to utilize proprietary projections and/or methods. If a client has a special request or idea for a model that does not exist in this catalog, we at Paydirt are happy to work through the process of bringing it to life.

Data and API management services with Paydirt come in the form of creation, curation, and management of highly scalable systems for your data, projections, and information. We take the data you are holding in less efficient systems and create MongoDB database clusters and optimized collections which are highly robust and extremely fast. For API management we can create and curate APIs using FastAPI structures through AWS for ease of use and adjustments.

For interest, questions, or consulting reach out to James McCool at paydirt.analytics@gmail.com 

Paydirt Stats Projections

General Information:

Paydirt offers Statistical (stats) Projections for all the major sports (NHL/NFL/MLB/NBA) as well as all the major esports (LOL/CSGO/COD). These projections are managed through a mongoDB oriented API structure with query maximization and caching. The list of available stats for each sport are as follows:

  • NBA Stats:
    • Minutes, FGM, FGA, FG2M, FG2A, Threes, FG3A, FTM, FTA, Rebounds, Assists, Steals, Blocks, Turnovers, 2P, 3P, FT, Points, Rebounds, Assists, Points+Rebounds+Assists, Points+Rebounds, Points+Assists, RA, Steals, Blocks, Turnovers
  • NHL Stats:
    • Player SOG, Player Goals, Player Assists, Player TP, Player Blocks, Player Saves
  • NFL Stats:
    • Pass Yards, Pass TDs, Rush Attempts, Rush Yards, Rush TDs, Targets, Receptions, Receiving Yards, Receiving TDs
  • MLB Stats:
    • Walks (Batter), Steals (Batter), Hits (Batter), Singles (Batter), Doubles (Batter), HRs (Batter), RBIs (Batter), Runs (Batter), BB (Pitcher), Hits (Pitcher), HRs (Pitcher), ERs (Pitcher), Ks (Pitcher), Outs (Pitcher)
  • League of Legends Stats:
    • Kills, Deaths, Assists, CS
  • CSGO Stats:
    • Kills, Headshots, Assists, Deaths
  • COD Stats:
    • Kills, Deaths, Plants+Disarms, Capture Time

Because Paydirt is a small and agile company, we have plenty of capacity to look into adding specific stats missing from the list above if you have a need for them. Feel free to reach out for a conversation about adding stats to the projections feed.

Paydirt Tools and Models:

General Information:

The tools and models for each individual sport follow a similar framework to one another. This helps users maintain a familiarity with the tools across sports as well as creating an ease of maintenance. Some basic information about each type of tool and model is as follows:

  • Overall Structure:
    • Models are built using Streamlit, a framework to create applications in Python, and is easily managed as both a standalone web application or as an iframe, making it very flexible to client needs
    • The apps are (currently) hosted through Huggingface, a data and AI community that offers free hosting. We are working away from this platform as we look to scale but currently find it to be agile and very easy to work with.
    • The data feeds are managed through a MongoDB pipeline utilizing both caching and optimized querying to provide fast access and quick updates
  • Range of Outcomes:
    • The Range of Outcomes (also referred to as the ROO) is built on algorithms that utilize monte carlo simulations to create an acceptable set of outcomes that are then measured against various data such as salary thresholds, finishing percentiles, and leverage gains. This model is highly valuable and shows users not only what the expectation is, but also how often certain players or teams achieve specific outcomes around the expectation.
  • Contest Simulations:
    • The Contest Simulations have two models, Regular and Showdown, and are built using Paydirts own Seed Frame logic to create fields and simulate DFS contests. This technology has been built to measure player value and sentiment as well as give users hundreds of thousands of DFS lineups to query and use in their own process.
    • The Contest Simulations are an incredibly valuable tool in the modern DFS ecosystem and offer important insight into the true value of both player level and team level decisions.
    • Note that the Contest Simulations require a backend process and managed algorithms to create the seed frames and populate the database to ensure that users have as quick and easy a process on the frontend as possible without any hard math or data bloat involved on click.
  • Pivot Finder:
    • The Pivot Finder is a very useful tool for hand builders while also providing use in creating rule sets and conditionals for MME and portfolio builders. It uses projections and salary inputs to give a list of acceptable pivots you can make off of the more popular options on the slate, allowing for easy gains in relative value.
  • Stack finder:
    • The Stack Finder is a tool designed for correlation based sports in DFS that utilize salary, projection, and ownership projections to return a list of highly valuable stacks with regard to projection and ownership. It uses trimming algorithms to show only stacks that are as valuable in terms of projection as they are ownership.
  • Showdown Optimizer:
    • Paydirt offers a simple Showdown Optimization solution for NBA and NFL, the main sports with interest in showdowns, which can give lower level users an easy way to build a couple of lineups.
      • Paydirt is looking to replace any low level optimizers with a lineup feed from the seed frames in the form of an “optimals tab”, so we expect to remove the Showdown Optimizer by the 2025 MLB season.

NBA Oriented Tools and Models:

  • NBA Range of Outcomes
    • Note that this model as a baseline includes just the Range of Outcomes table built from the projections model, it can also include an optimals tab built from the seed frames but access to those necessitates access to the contest simulations.
  • NBA Contest Simulations (Regular)
  • NBA Contest Simulations (Showdown)
  • NBA Pivot Finder
  • NBA Showdown Optimizer

NFL Oriented Tools and Models:

  • NFL Range of Outcomes
    • Note that this model as a baseline includes just the Range of Outcomes table built from the projections model, it can also include an optimals tab built from the seed frames but access to those necessitates access to the contest simulations.
  • NFL Contest Simulations (Regular)
  • NFL Contest Simulations (Showdown)
  • NFL Pivot Finder
  • NFL Stack Finder
  • NFL Showdown Optimizer

MLB Oriented Tools and Models:

  • MLB Range of Outcomes
    • Note that this model as a baseline includes just the Range of Outcomes table built from the projections model, it can also include an optimals tab built from the seed frames but access to those necessitates access to the contest simulations.
  • MLB Contest Sims (Regular)
  • MLB Contest Sims (Showdown)
  • MLB Pivot finder
  • MLB Stack Finder

NHL Oriented Tools and Models:

  • NFL Range of Outcomes
    • Note that for NHL specifically, this model includes a range of outcomes table set that runs at the player level, line combination level, and power play level.
  • NHL Contest Simulations (Regular)
  • NHL Contest Sims (Showdown)
  • NHL Pivot Finder
  • NHL Stack Finder

PGA Oriented Tools and Models:

  • PGA Range of Outcomes

Paydirt Databasing and API Management Services:

General Information:

Paydirt specializes in data, which extends farther than the front end into strong backend structuring and management. We understand that many smaller companies are using excel or google sheets as data solutions, but as you scale these solutions become either too cumbersome or too slow. Paydirt offers the following solutions to improve scalability in regards to data management:

  • Database and Storage Structuring:
    • We take your existing systems and set them up in a MongoDB cluster, managing your collections and setting up query optimization pipelines. This process ensures you have a reliable data storage and querying solution that can scale into significant size and scope.
    • With the way that MongoDB file storage works we have a highly flexible and easily managed data structure that can be easily ingested into various applications through general CRUD and query practices.
    • Likewise, MongoDB also allows for in-depth data analysis of collections and data so that clients can find the most valuable areas of their data and where it can be improved.
  • API Creation and Management:
    • We can take the data managed in any database system and create APIs for ease of use in a multitude of applications. Utilizing a FastAPI pipeline through AWS, we can take the data managed in any database system and create APIs for ease of use in a multitude of applications.
    • If Paydirt is managing data for a client through a MongoDB storage structure, the API creation is robust, scalable, and handled entirely in house. This allows us to take on bugs and make adjustments quickly and efficiently without having to work with a third party data management group.

We are confident in our ability to take existing data management structures, especially those without a database solution, and optimize them for speed, scale, and workability. If you are looking to maximize your data, Paydirt will help you.

Pricing Structure:

Stats/Ownership Projections Whitelisting:

  • Stats Projections include both baseline stats for sports betting as well as fantasy point projections with service to Draftkings and Fanduel
  • Prices for each of the major sports (NFL, NBA, MLB, NHL) in regards to Stats Projections are as follows
    • NFL ($1,000 per month, $5,000 per season)
    • NBA ($1,000 per month, $5,000 per season)
    • NHL ($750 per month, $4,000 per season)
    • MLB ($750 per month, $4,000 per season)
    • LOL ($500 per month)
    • CSGO ($500 per month)
    • COD ($500 per month)
  • Ownership Projections include baseline, small field, and large field ownership projections for use in DFS as a standalone whitelisting option
  • Prices for each of the major sports (NFL, NBA, MLB, NHL) in regards to Ownership Projections are as follows
    • NFL ($300 per month, $1,500 per season)
    • NBA ($300 per month, $1,500 per season)
    • NHL ($300 per month, $1,500 per season)
    • MLB ($300 per month, $1,500 per season)
    • LOL ($300 per month, $1,500 per season)
    • CSGO ($300 per month, $1,500 per season)
    • COD ($300 per month, $1,500 per season)

Tools and Models Cost Structure:

  • Tools and Models can be either whitelisted or, for an extra fee of consultation and creation, outfitted with a client’s projections and methods.
  • If whitelisting, all sports specific tools and models will be populated by Paydirt projections.
  • Tools and Models are charged per month, per sport, and can be packaged together as a bundle for an individual sport to save cost.
  • Whitelisting costs for each sport specific tool and model type ($individual / $bundle) are as follows:
    • Range of Outcomes tables ($300 / $250 per month, per sport)
    • Pivot Finder ($300 / $250 per month, per sport)
    • Stack Finder ($250 / $200 per month, per sport)
    • Contest Simulations ($500 / $450 per month, per sport)
      • As an example of cost difference for a sport with all models included, an NFL contract utilizing each individually would cost $1,350 per month (Assuming Range of Outcomes, Pivot Finder, Stack Finder, and a Contest Simulations model for regular OR showdown slates) while bundling would cost $1,150 per month.
  • Paydirt also offers a Portfolio Manager tool that allows for user upload of a DFS portfolio along with a projections set which then gives information around lineup volatility, duplications, win rates, and leverage. This tool is very powerful and used by high end users to create high upside portfolios.
    • Portfolio Manager ($500 per month)

Database and API Management Consulting and Cost:

  • Database and API management services work better as a combo but can be utilized individually depending on a client’s wants, needs, and prior commitments.
  • Both services require an extra consulting step to decide on scope and process, which is charged as a secondary fee before any technical work is handled.
    • Consulting fee ($75 per hour)
  • For both the Database and API solutions, after deciding scope and necessary requirements through consultation, the Database process requires authorization of current systems to create connections and spin up agents and scripts to handle the transfer of data pipelines.
  • For the Database solutions, this includes setting up an admin app that allows for manual data transfer. Costs for a Databasing solution are as follows:
    • Admin app create ($150, one time fee, per cluster)
    • Cluster creation ($150, one time fee, per cluster)
    • Recurring management fee ($500, per month, per cluster)
      • Should scope or scale exceed initial estimates it will be necessary to revisit the data plan and implement a more robust solution which would incur extra charges
  • For API solutions that do NOT include a database solution and use a previously implemented storage system, there will be extra steps of authorization and admission to current databases. This comes in the form of a consultation and extra technical work.
    • Database adaptation ($75 per hour, max $500 per system)
  • For API solutions that do include a database solution, we can connect to our clusters and connections with ease and spin up a FastAPI backend API rather quickly.
    • API creation ($225, one time fee, per API)
    • Recurring management fee ($150, per month, per API)
  • For both Database and API management solutions, extra technical work in terms of adding endpoints, variables, data sources, or any other work that requires a change of code or function may result in consulting or technical fees, depending on the size and scope of the work necessary.

Miscellaneous:

Paydirt is in the business of helping people create, curate, manage, and distribute their data and expressions in as many ways as possible. We are happy to work with companies and clients in ways that are not strictly outlined above. Some miscellaneous offerings include:

  • Logic and reasoning projects for tools, models, or apps
  • App creation and management through Streamlit, RStudio, or other Python based app structures
  • Data pipelines through web scraping and power queries
  • Excel and Google Sheets oriented solutions, functions, and spreadsheet management

If you have data and/or ways to display it, Paydirt will be able to help you maximize that expression. We are looking forward to working with you!