Work

Selected work

Delivered by Palmer28’s founding firms, Accelerait and GrayBeck.

Sports & Media · A major professional sports league

Schedule optimization and ratings prediction

+8%

TV ratings above historical average

  • Scheduling
  • Forecasting
Challenge
A legacy scheduling system was slow to solve and produced schedules that left value on the table.
What we built
Ratings prediction models trained on preseason and historical viewership data, and an optimization algorithm purpose-built for the league’s scheduling problem, delivered in an interface the staff run themselves.
Result
  • TV ratings 8% above historical average
  • Schedule penalty score reduced 50%
  • Ratings predictions 93%+ accurate

Finance & Investment · A private credit manager

Multi-fund loan allocation

$20B+

in portfolio assets supported

  • Capital allocation
  • Network flow
Challenge
Loans had to be allocated across several funds by hand, while eligibility, concentration limits, hold sizes, and a shared supply of loans all interacted.
What we built
An allocation engine that places every loan across every fund at once in a single optimization model. Hard rules stay hard; when they conflict, the engine names the conflict instead of quietly relaxing a requirement. Each run keeps its inputs, outputs, and solver record, and works alongside the desk’s existing workbook.
Result
  • More than $20 billion in portfolio assets supported

Finance & Investment · An alternative asset manager

A first systematic quant strategy

75%

directional accuracy, routinely exceeded

  • Pricing
  • Forecasting
Challenge
Positions were taken manually, based on experience and spreadsheet analysis, with no systematic quantitative process behind them.
What we built
Machine learning models trained on equity capital markets data, with uncertainty quantified, in an automated pipeline that takes deal parameters and returns a workbook built to the firm’s specifications.
Result
  • Directional accuracy routinely above 75%

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