DM Analytics

Project Stack

Four connected projects designed as one football intelligence system.

The portfolio is intentionally structured so each project supports the next: event-level chance quality, dynamic team strength, live match-state probabilities, and player evaluation for recruitment.

Foundational Model

Expected Goals Model

A La Liga expected goals case study built with an R-first statistical workflow, using interpretable probability models, season-based validation, calibration-led evaluation, and a small freeze-frame context upgrade to create reusable shot-quality infrastructure.

Status: ImplementedQuestion: How should shot quality be quantified from open event data so that analysts can separate chance quality from finishing and reuse the outputs in later forecasting and player models?
  • Naive conversion baseline
  • Logistic regression
  • GAM with mgcv
  • Freeze-frame context features
  • Season-based validation
  • Probability calibration diagnostics
View case study

Forecasting Layer

Dynamic Team Strength and Match Forecasting Model

A La Liga match forecasting case study using a broader historical open-data sample, with a baseline-to-dynamic model ladder and explicit evaluation of whether time-varying team strength improves pre-match probabilities.

Status: ImplementedQuestion: How should current team strength be estimated for match forecasting and pre-match strategic priors?
  • Naive outcome baseline
  • Static pooled attack/defence model
  • Dynamic team-strength updates
  • Temporal train, validation, and test splits
  • Multiclass forecast evaluation
View case study

Tactical Decision Support

In-Game Win Probability and Tactical Decision Model

A minute-level live forecasting case study that updates win, draw, and loss probabilities from scoreline, time remaining, red-card state, cumulative xG, and pre-match strength priors.

Status: ImplementedQuestion: How should outcome probabilities update during a match, and how can those updates support tactical decision-making?
  • Empirical state baseline
  • Remaining-goals Poisson model
  • GAM-based remaining-goals model
  • Minute-level state table
  • Pre-match strength priors from Project 2
View case study

Recruitment and Development

Player Rating and Recruitment Model

A role-aware recruitment model built from lineup-derived minutes, event-level player contributions, and team-context adjustment, designed to separate player signal from strong-team inflation.

Status: ImplementedQuestion: How should a club compare recruitment targets within role while controlling for team environment and small-sample noise?
  • Role-aware component ratings
  • GAM-based team-context adjustment
  • Reliability shrinkage
  • Season-to-season stability analysis
View case study