Monte Carlo
Sports Analytics
Preface
Background
1
Introduction
2
Distributions
3
Regression
4
Poisson Regression
5
Logistic Regression
Head-to-head
6
Margin of Victory
7
Win-Loss Models
8
Win-Tie-Loss Models
9
Offense-Defense Rating
10
Player Contribution
Free-for-all
11
Time Models
12
Rank Models
Missing Data
13
Informative Missingness
Monte Carlo
14
Tournament
Bracketology
15
Expected Score
16
Summary
References
17
Data
Monte Carlo
Read the
simulate section
which includes
interval estimators
of probabilities and expectations.
13
Informative Missingness
14
Tournament