Use NHL salary and performance data to identify forwards who significantly outperform their contracts, making them high-value targets for trades or free agency.
- Which NHL forwards provide the most value per $1M of salary?
- How does play-driving (xGF%) relate to team success?
- What traits or metrics define an "undervalued" player?
Teams constantly seek low-cost, high-impact players to build depth and stay under the cap. Identifying these players through data-driven analysis can give front offices a competitive edge.
data/: Raw and cleaned salary + performance datanotebooks/: Data cleaning, metric creation, and visualizationsvisuals/: Value charts and scatter plotsREADME.md: Summary of methodology and findings
- Points per $1M AAV → offensive efficiency
- xGF% per $1M AAV → play-driving efficiency
- TOI/GP, GP → minimum usage thresholds
- R² = 0.53 → proven correlation between xGF% and Win%
- Python (Pandas, Matplotlib)
- Google Colab
- GitHub for versioning
- xGF% correlates strongly with team win% (R=0.728)
- Several players outperform their salary based on both production and play-driving
- Ideal trade/FA targets are often middle-six forwards under $4M
This scatterplot demonstrates the relationship between team xGF% and win percentage. With an R² of 0.53, this validates that xGF% is a reliable predictor of team success — supporting its use in player valuation.
This chart shows which NHL forwards provide the most offensive production relative to their salary. Players in the top-left are producing high point totals on low-cost contracts — ideal trade or free agency targets.
This chart highlights forwards who drive strong on-ice performance (xGF%) relative to their salary. xGF% is a strong predictor of team success, so these players offer high-impact value beyond just scoring.
This bar chart ranks the most underpaid forwards in the NHL using a combined metric of scaled Points per $1M and xGF% per $1M. These players deliver elite production and play-driving efficiency relative to their cap hit.
Top 15 Based on Value Metric Data: data/top_15_value_targets.csv
This plot is based on players filtered by cap hit (≤ $4M), TOI/GP (≥ 8), and GP (≥ 30).
Source data: data/final_value_targets.csv
- Add clustering by player archetype
- Visualize team-level value capture
- Introduce contract length, age curves, or playoff performance
- Thank you to Natural Stat Trick for the in game analytic stats
- Thank you to PuckPedia for the Salary Stats
Full analysis notebook: notebooks/nhl_value_forwards.ipynb