v1.6.2

• Fixed bug in PoissonGoalsModel where weights parameter was not being handled correctly in the gradient function.

v1.6.1

• Updated goals models loss functions to work with scipy 1.16+
• Improved numerical stability of the loss function for the Negative Binomial model to improve convergence
• Added Colab notebook for implied probabilities examples
• Python 3.14 support

v1.6.0

Package Updates

Matchflow

• can now read / write data from cloud storage (e.g. S3, GCS, Azure Blob Storage) using fsspec
• Now supports multiple join strategies:
  • left, right, outer, inner and anti joins
  • Automatic type inference and conversion for join keys
  • Customizable type coercion functions for complex join key scenarios
• Fixed bug where where executor did not recognise .concat() function

Betting

• Updated implied submodule to add logarithmic overround removal method and return structured results
• Renamed kelly submodule to betting
• Added multiple_criterion function for calculating Kelly Criterion for multiple outcomes
• Added arbitrage_hedge function to calculate hedge bet sizes
• Added arbitrage_opportunities function to identify arbitrage opportunities across bookmakers
• Added value_bets function to identify value bets based on model probabilities
• Added odds_conversion function to convert between different odds formats (decimal, fractional, American)
• Updated all betting utility functions to return structured output

Documentation Improvements

• Updated Matchflow documentation
• Updated implied documentation
• Updated betting documentation
• Started adding Colab notebooks for interactive examples, more to come!

v1.5.1

• Restricted scipy to version <=1.15.3 due to breaking changes in the minimize function introduced in 1.16+, which affect goal model compatibility.

v1.5.0

Package Updates

• Pitch

  • Initial release of interactive Pitch plotting library

• MatchFlow

  • Flow now has it's own query language, with support for boolean expressions and field comparisons via .query

• Goals Models

  • All Goals Model's .fit functions now take an optional dictionary of arguments to pass to scipy's optimiser
  • All GoalsModels now fit using an optional gradient (defaults to True), which improves the fit time by approx 5-10x

• FootballProbabilityGrid

  • Updated class to include more betting markets
  • Now supports fractional Asian handicaps and totals
  • Optionally normalizes probabilities to sum to 1 (default: True)
  • Calculations now use vectorized numpy operations for improved performance
  • Caching of results for repeated queries to improve efficiency

• Goal Expectancy

  • Added support for removing overrounding from input probabilities
  • Improved handling of edge cases in probability distributions
  • Altered to using probabilities rather than odds
  • Added more diagnostic output for debugging
  • Optionally normalizes probabilities to sum to 1

Documentation Improvements

• Added Pitch documentation
• Updated Flow documentation with .query examples
• Completely rewritten documentation for Goals Models and goal expectancy
• Removed obsolete examples

v1.4.1

Package Updates

• Fixed bug in Flow.cache executor logic

v1.4.0

v1.4.0 (2025-06-19)

Package Updates

• Introduced optional FlowOptimizer for smart plan rewrites
  • New optimize=True flag on all flows (off by default)
  • Safe, conservative rewrites: pushdown, fusion, and simplification
  • Enhanced .explain(compare=True) for before/after plan introspection
  • Optimizer is backwards-compatible and fully opt-in
• Added .plot_plan() on Flow and FlowGroup to visualize pipeline structure
• .explain() now works on FlowGroup, and supports compare=True
• New .with_schema({...}) method to cast and validate fields
  • Example: Flow.with_schema({"x": int, "ts": parse_datetime})
• Added .rolling_summary() to FlowGroup for windowed group summaries
  (e.g. rolling 5-minute aggregates per player or team)
• Added .time_bucket() to FlowGroup for time-based binning summaries
• Added .show() method to pretty-print results using tabulate
• Flow.collect() now supports optional progress bars during execution

Documentation Improvements

• Refreshed documentation to include:
  • FlowOptimizer and optimize=True
  • .with_schema(), .rolling_summary(), .show()
  • Plan introspection via .explain(compare=True) and .plot_plan()
  • Enhanced type hints throughout the package for improved compatibility with mypy

v1.3.0

Package Updates

• Initial release of MatchFlow

Documentation Improvements

• Added MatchFlow documentation
• Added MatchFlow recipes documentation
• Added API references for all of penaltyblog
• Added stub file for metric Cython code
• Added stub file for models Cython code

v1.2.0

v1.2.0 (2025-04-10)

Package Updates

• Updated Elo Ratings model to be more football-specific so that it now includes home field advantage and can predict draw probabilities
• Added new Cythonised Ignorance Score metric
• Added new Cythonised Multiclass Briar Score metric
• RPS functions now raise a ValueError exception if outcome is out of bounds

Documentation Improvements

• Updated Elo documentation
• Added Pi Ratings documentation
• Added examples for ignorance score
• Added examples for multiclass briar score
• Updated examples for RPS

v1.1.0

Performance Enhancements

• Rewrote Dixon-Coles model using Cython, achieving approximately 250x speed improvement.
• Rewrote Poisson model using Cython, achieving approximately 250x speed improvement.
• Implemented Negative Binomial Goals Model in Cython for enhanced performance.
• Added high-performance Cython implementation of the Bivariate Poisson Goals Model based on Karlis & Ntzoufras.
• Introduced Cython implementation of the Bivariate Weibull Count Copula Goals Model based on Boshnakov et al.
• Developed Pi Ratings System based on Constantinou et al.
• Migrated ranked probability score functions to Cython for improved speed.

Package Updates

• Temporarily removed Stan-based models due to dependency management challenges. Investigating improved packaging strategies for future reintegration.
• Temporarily removed Rue and Salvesen model pending revision to accurately reflect its intended methodology (previously implemented as a hybrid Dixon-Coles variant).

Documentation Improvements

• Updated and expanded model examples in the documentation.
• Enhanced type hints throughout the package for improved compatibility with mypy.
• Updated documentation to pydata Sphinx theme.

CI/CD and Testing

• Expanded GitHub Actions workflows to perform unit tests across all supported Python versions.
• Extended GitHub Actions workflows to perform unit tests on Windows, macOS, and Linux.
• Configured GitHub Actions to automatically build wheels for all supported Python versions across Windows, macOS, and Linux.