All - I built a model for the NCAA March Madness last year to predict the winners, and half-time and final scores. Reasoning and history show, bet the under for the first round. Everyone is on the road and everyone is amped up to play tough D. I made money following that model.
I am starting to load in data for the IHSA series and it is bare bones presently, with only regular season results loaded.
I need to collect the following:
To improve the accuracy of score predictions for upcoming Illinois High School football games, here are additional types of data that would be useful:
I am starting to load in data for the IHSA series and it is bare bones presently, with only regular season results loaded.
I need to collect the following:
To improve the accuracy of score predictions for upcoming Illinois High School football games, here are additional types of data that would be useful:
- Team Stats:
- Offensive stats (points per game, yards per game, turnovers).
- Defensive stats (points allowed per game, sacks, interceptions).
- Special teams performance (field goals, kick returns).
- Individual Player Stats:
- Key player performances (quarterback completions, rushing yards, receiving yards).
- Injuries or players missing games.
- Game Location:
- Home vs. away games, as home-field advantage can affect outcomes.
- Weather Conditions:
- Past weather conditions during games and forecast for upcoming games (rain, wind, etc.).
- Historical Matchups:
- Previous meetings between teams, including head-to-head results.
- Team Trends:
- Recent form (winning streaks, losing streaks).
- Momentum shifts over the season.
- Coaching Changes:
- New coaches or changes in team strategy.
- Strength of Schedule:
- Quality of opponents faced in previous weeks.