Quantitative approach to casting
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The document outlines Project Luther, a system designed to optimize casting decisions in films based on actors' potential impact on domestic revenue. It details the methodology, including data collection, scoring actors, and selecting features for a predictive model, with various regression analyses demonstrating relationships between actor scores, budget, release duration, and projected revenue. Key findings indicate that increases in budget, number of theaters, and actor scores significantly influence revenue outcomes.
Quantitative approach to casting
- 1. Project Luther A quantitative approach to casting decisions Sarah Cullem
- 2. Create a system to select actors for new films based on their relative impact on the film’s potential domestic revenue Objective:
- 3. Jason Schwartzman Rachel McAdams Justin Long Dream Team 1 Zach Galifianakis Scarlett Johansson Jonah Hill Dream Team 2
- 4. Jason Schwartzman Rachel McAdams Justin Long Dream Team 1 Zach Galifianakis Scarlett Johansson Jonah Hill Dream Team 2 ? ? ? ? ? ?
- 5. Can we find a way to tie to our decision to the financial return of our film?
- 6. PROCESS OVERVIEW • Scrape and clean data (Box Office Mojo & OMDb API) • Select scoring method for actors in a film to include as a regression feature • Select additional features for modeling • Select best performing model based on test & train error • Apply findings to selecting casting for films
- 7. Actor Scoring Example: Rachel McAdams Rachel’s score for prediction is the average domestic gross for every prior film
- 8. Film Scoring Example: The Family Stone Score = 110.13 * 45.03 * 35.62 * 24.54 = 4334869 Log(Score) = 15.28
- 9. The log of the score showed the strongest relationship with Domestic Total Gross The Family Stone Log(Product of Actor Scores) DomesticTotalGross Product of Actor Scores Log(Product Actor Scores) Log(Product of Actor Scores)
- 10. Other features in the model Film Budget (in Millions) Theaters Days in Release Run Time in Minutes Domestic Total Gross (in Millions)
- 11. 0 1250 2500 3750 5000 1 2 3 4 5 MSETrain MSETest Model Selection: Mean Squared Error
- 12. 0 0.175 0.35 0.525 0.7 1 2 3 4 5 0.23 0.38 0.49 0.66 0.69 Model Selection: Adjusted R Squared
- 13. CoefficientBands -3 0 3 6 9 12 7.89 4.59 2.32 1.89 1.89 Lower Bound Coefficient Upper Bound Actor Scoring: Coefficients & ConfidenceP-Value 0.0 0.1 0.2 1 2 3 4 5 0 0.001 0.08 0.18 0.17
- 14. = 1.89 + 0.56 + 0.78 + 0.02 Log(Product of Actor Scores) Budget TheatersDays in Release Note: the intercept in the model equation is -96.4 Domestic Gross Model 4: Interpretation
- 15. = 1.89 + 0.56 + 0.78 + Every 100 added theaters adds $2M more revenue Note: the intercept in the model equation is -96.4 + 0.02 Log(Product of Actor Scores) Budget TheatersDays in Release Domestic Gross
- 16. 1.89 + 0.56 + 0.78 Every 10 days more on the release adds $7.8M in revenue = Note: the intercept in the model equation is -96.4 + 0.02 Log(Product of Actor Scores) Budget TheatersDays in Release Domestic Gross
- 17. 1.89 + 0.56 + 0.78 Every $10M increase in budget adds $5.6M to revenue = Note: the intercept in the model equation is -96.4 + 0.02 Log(Product of Actor Scores) Budget TheatersDays in Release Domestic Gross
- 18. 1.89 + 0.56 + 0.78 = Every 1% increase in actor scores adds ~$1.9M to revenue Note: the intercept in the model equation is -96.4 + 0.02 Log(Product of Actor Scores) Budget TheatersDays in Release Domestic Gross
- 19. Domestic Gross 1.89 + 0.56 + 0.78 = Every 1% increase in actor scores adds ~$1.9M to revenue Note: the intercept in the model equation is -96.4 + 0.02 Log(Product of Actor Scores) Budget TheatersDays in Release
- 20. Maintain a scorecard with the latest revenue score for each actor, updated as new films are released
- 21. Jason Schwartzman Rachel McAdams Justin Long Dream Team 1 Zach Galifianakis Scarlett Johansson Jonah Hill Dream Team 2
- 22. Jason Schwartzman Rachel McAdams Justin Long Dream Team 1 Zach Galifianakis Scarlett Johansson Jonah Hill Dream Team 2 20.8 82.8 43.3 114.0 88.8 93.1
- 23. Jason Schwartzman Rachel McAdams Justin Long Dream Team 1 Zach Galifianakis Scarlett Johansson Jonah Hill Dream Team 2 20.8 82.8 43.3 114.0 88.8 93.1 $21.2M $25.9M +22%
- 24. QUESTIONS