Project Charter

The Evolution of Statistics in MLB Free Agency

Danny Nolan

The first goal of this project is to study the history of free agency and salaries in Major League Baseball.  Players have earned compensation for playing baseball since at least the 1870’s, and so naturally the financial landscape of the sport has shifted dramatically in the 150+ years since.  Phase one of this project will dive deeper into those changes and examine events that have shaped the future of contracts in baseball.  The next portion will deal with correlations between statistics and salaries and how those correlations have fluctuated over time.  For instance, a pitcher’s win-loss record is a statistic that has fallen out of favor with the modern baseball community.  Forty years ago, however, wins were highly valued.  Would a pitcher with twenty wins in 1983 receive the same contract as a pitcher with twenty wins today, if all other stats were generally held constant?  This research will attempt to answer that question and others like it.  It will be necessary to include a section defining each metric, especially those that are more advanced and harder to understand.  Lastly, a predictive model will be created, one that allows a user to input facts and statistics.  The model will then yield a projected free agent contract as an output.  All three of these facets aim to give readers a better understanding of the many nuances present in the free agency process.  Additionally, the project will hopefully inspire others and cause them to formulate their own questions.

There have been similar models built to predict free agent contracts, both in baseball and in other sports.  For instance, Spotrac, a website housing statistics and financial information for many sports, has a tool that predicts the deal an upcoming free agent will get in the offseason.  Similarly, ESPN recently published an article surmising what two-way sensation Shohei Ohtani might receive when he becomes a free agent after the season.  Instead of predicting the contract with a model, the 26 contributors based their estimates off of previous large contracts and hearsay among MLB executives.  While this project will not be the first to build a predictive model, it will diverge from its predecessors because of its other features.  Most sources out there, Spotrac and ESPN included, do not include much qualitative contract information or data visualizations.  This project will be unique because of its multifaceted nature.

Deliverables

• Introduction page outlining purpose and format of project
• Timeline of benchmark contract/free agency events in MLB history
• Glossary-type section for statistics being used
• Page with data visualizations showing relationships between variables (statistics, dollar amount, year, etc.)
• End product section with the interactive, predictive model
• Page(s) with sources, acknowledgements, and details about DSSRF

Timeline

• Week of June 12
  • Find all free agent contract information on the top 10 free agents (by WAR over the past three years) since the start of free agency
  • Begin to use Tableau to experiment with visualizations that may be included in the final project
  • Have all events planned out to incorporate into a timeline
  • Research scholarly articles pertaining to the topic
  • Continue data collection
• Week of June 19
  • Set up the framework for the digital page (likely via Scalar or WordPress)
  • Begin to narrow down which visualizations will be included or omitted
  • Begin working on a glossary section explaining complicated statistics
  • Continue data collection if necessary
• Week of June 26
  • Complete data collection if not already done
  • Once the data has been fully collected, begin search for the best predictive model
  • Polish timeline and glossary sections
  • Be 90% done with the data visualizations
• Week of July 3
  • Finalize data visualizations
  • Begin working on the parts of the website that do not deal with data (i.e. introduction, sources)
  • Continue to hone the predictive model
  • Begin thinking about the best ways to increase the interactivity of the website
  • If time allows, think about adding new things that would enhance the project
• Week of July 10
  • Find a final model and combine it with an interactive tool
  • Put any finishing touches on the project; prepare it for presentation
  • Practice and/or record presentation for next week
  • Present work
• Week of July 17
  • Present work

Future Plans

Arguably the most interesting part of this project will be seeing how the projected contracts stack up against real life. Each year that passes will birth new data, data that can be used to improve the accuracy of the model. Ideally, I can continue to update the website and its features as time passes. That would allow the project to remain useful for as long as possible. Because MLB free agency only happens once a year, it is certainly feasible to maintain the site. I am hopeful that this work can be a gateway into a riveting career path.

Working Bibliography

Baseball-Reference.com: MLB Stats, Scores, History, & Records, 2023, https://www.baseball-reference.com/. Accessed 9 June 2023.

Baseball Savant: Trending MLB Players, Statcast and Visualizations, 2023, https://baseballsavant.mlb.com/. Accessed 9 June 2023.

Spotrac.com: Sports Contracts, Salaries, Caps, Bonuses, & Transactions, 2023, https://www.spotrac.com/. Accessed 9 June 2023.

“Cot’s Baseball Contracts.” Baseball Prospectus, 2023, https://legacy.baseballprospectus.com/compensation/cots/. Accessed 9 June 2023.

McDaniel, Kiley. “Shohei Ohtani’s free agency contract, predicted by MLB insiders.” ESPN, 8 May 2023, https://www.espn.com/mlb/insider/insider/story/_/id/37413674/shohei-ohtani-free-agency-contract-predicted-mlb-insiders. Accessed 9 June 2023.

Sommers, Paul M., and Noel Quinton. “Pay and Performance in Major League Baseball: The Case of the First Family of Free Agents.” The Journal of Human Resources, vol. 17, no. 3, 1982, pp. 426–36. JSTOR, https://doi.org/10.2307/145589. Accessed 9 June 2023.