Biathlon Championships Predictions - Implementation Scope

Based on the Nordic Combined champs-predictions.R file, here’s what the biathlon version should include:

Core Structure (1519 lines in Nordic Combined)

1. Library Imports & Setup (Lines 1-32)

  • Standard R libraries (dplyr, tidyr, openxlsx, arrow, mgcv, leaps, logger, purrr, lubridate, slider)
  • Biathlon-specific points systems (regular_points, mass_start_points)
  • Logging configuration to ~/ski/elo/python/biathlon/polars/excel365/champs-predictions/

2. Points Systems & Helper Functions (Lines 13-117)

  • Biathlon Points: Regular (40 positions) and Mass Start (30 positions) - ✅ DONE
  • replace_na_with_quartile() function for missing value imputation
  • get_points() function with race type logic for Mass Start vs other races - ✅ DONE
  • enforce_probability_constraints() - ensures Win ≤ Podium ≤ Top5 ≤ Top10
  • normalize_position_probabilities() - complex normalization with race participation scaling

3. Data Reading & Race Filtering (Lines 34-99)

  • Read weekends.csv and filter for Championships (Championship == 1)
  • Separate races by type:
    • Individual races: Men/Ladies for Individual, Sprint, Pursuit, Mass Start
    • Relay races: Men/Ladies for Relay, Mixed Relay, Single Mixed Relay
  • Race dataframes with original race numbering for Excel sheet naming

4. Data Preprocessing Function (Lines 411-528)

  • preprocess_data() - handles historical race data
  • Points calculation using appropriate points system
  • Weighted previous points calculation (last 5 races, recent weighted higher)
  • ELO/PELO column creation and percentage normalization
  • Race type filtering (exclude Offseason)
  • Season period assignment (4 periods per season)

5. Startlist Data Preparation (Lines 229-409)

  • prepare_startlist_data() - prepares prediction data
  • Handles both individual and team startlists
  • Team Prev_Points_Weighted calculation from individual member data
  • ELO percentage column creation (Elo_Pct, Pelo_Pct)
  • Race probability column preservation
  • Team vs individual data path logic

6. Individual Championships Processing (Lines 530-1004)

  • process_gender_championships() - main individual prediction function
  • GAM model creation using regsubsets for feature selection
  • Position probability models for thresholds (1, 3, 5, 10, 30)
  • Training on PELO (pre-race), prediction on ELO (post-race)
  • Period adjustments using t-tests
  • Brier score evaluation for model quality
  • Excel output generation with race-by-race sheets

7. Team Championships Processing (Lines 1030-1348)

  • process_team_championships() - handles relay predictions
  • Team-specific ELO columns (Avg_Individual_Elo, etc.)
  • Team position models (fewer thresholds: 1, 3, 5, 10)
  • Team startlist handling for different relay types
  • Team summary and race-by-race Excel outputs

8. Race Probability Calculation (Lines 1350-1486)

  • calculate_championships_race_probabilities() - calculates participation probabilities
  • Historical participation analysis (5-year lookback)
  • Biathlon-specific: 6-person quota constraint per nation per race (vs 3 for Nordic Combined)
  • Base probability scaling and normalization
  • Updates startlist files with race probabilities

9. Team Member Points Calculation (Lines 1006-1028)

  • calculate_team_prev_points() - calculates team Prev_Points_Weighted
  • Individual member analysis from chrono data
  • Weighted average of last 5 individual races
  • Biathlon-specific: Include Individual, Sprint, Pursuit, Mass Start (exclude Offseason)

Biathlon-Specific Adaptations Needed

1. Points Systems

  • ✅ Already adapted: regular_points (40 positions), mass_start_points (30 positions)
  • ✅ get_points() function with Mass Start logic

2. File Paths

  • Change all paths from nordic-combined to biathlon
  • Output directory: ~/blog/daehl-e/content/post/biathlon/drafts/champs-predictions/

3. Race Types

  • Individual: Individual, Sprint, Pursuit, Mass Start (vs Individual, IndividualCompact, Mass Start)
  • Relay: Use “Relay” in RaceType (vs “Team”)
  • Mixed: Mixed Relay (2M+2L), Single Mixed Relay (1M+1L)

4. ELO Column Names

  • ✅ Use MassStart_Elo not Mass_Start_Elo
  • Individual_Elo, Sprint_Elo, Pursuit_Elo, MassStart_Elo

5. Quota System

  • 6-person quota per nation (vs 3 for Nordic Combined)
  • Update quota constraints in race probability calculation

6. Relay Processing

  • 4 separate relay types: men_relay, ladies_relay, mixed_relay, single_mixed_relay
  • Team composition logic for mixed relays (2M+2L vs 1M+1L)
  • Different chrono file paths for each relay type

7. Output Files

  • 6 Excel workbooks: men, ladies, men_relay, ladies_relay, mixed_relay, single_mixed_relay
  • Race-by-race sheets with proper naming

Implementation Priority

  1. High Priority (Core functionality):

    • Data preprocessing function with biathlon race types
    • Individual championships processing (men/ladies)
    • Race probability calculation with 6-person quota
    • Basic Excel output generation

  2. Medium Priority (Relay functionality):

    • Relay championships processing for all 4 types
    • Team member points calculation
    • Mixed relay logic (2M+2L, 1M+1L)

  3. Low Priority (Advanced features):

    • Period adjustments and t-test analysis
    • Advanced GAM model diagnostics
    • Brier score calculations

Key Functions to Implement

  1. preprocess_data() - adapt for biathlon race types
  2. prepare_startlist_data() - handle biathlon ELO columns
  3. process_gender_championships() - individual predictions
  4. process_relay_championships() - relay predictions (new function)
  5. calculate_championships_race_probabilities() - 6-person quota
  6. calculate_team_prev_points() - biathlon race type filtering

The file should be approximately 1500+ lines to match the complexity and functionality of the Nordic Combined version.

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