Home-Field Advantage and Standard Deviations in Scores for All Leagues

One of the main goals of the MDS Model is to predict spreads, i.e. the expected margin of victory in each game. This then predicts games against the spread after Log5 is calculated to determine the win probability for any given game. As I've written before, "Log5 only gives the probability of Team A beating Team B (and inversely, Team B beating Team A). A major use of modeling sports is for picking games "against the spread", which is considerably harder than picking "straight up" winners: lines (i.e. spreads) are designed to be 50/50."

To predict margin of victory (MOV), I calculate the inverse of the normal distribution for each percentage and multiply this by a parameter for each league. What follows is a guidebook for the standard deviation in each league, both for the final margin in each game (difference in score) as well as for the totals in each game (sum of both scores):

SD for MOV:

NBA:      13.47

NCAAB:    13.95

WNBA:     12.96

NFL:      9.82

NCAAF:    13.00

NHL:      2.31

MLB:      4.26

MLS:      1.50

SD for Totals:

NBA:      19.13

NCAAB:    19.13

WNBA:     18.68

NFL:      13.48

NCAAF:    18.55

NHL:      2.18

MLB:      4.24

Soccer:   1.52

Additionally, I also calculated the average home-field advantage in each league. In all cases, data was used for either the current ongoing season or the most recent completed season.

HFA:

NBA:      2.41

NCAAB:    5.39

WNBA:     2.10

NFL:      2.57

NCAAF:    4.39

NHL:      0.24

MLB:      0.19

MLS:      0.55

Sources:

NBA: Basketball-Reference, NCAAB: Spreadsheet Sports, WNBA: Basketball-Reference, NFL: Football-Reference, NCAAF: Football-Reference, NHL: Hockey-Reference, MLB: Baseball-Reference, MLS: Flashscore