Posted on 12/29/2010 by

Some things in this life are just not fair. In my last post I referred to one of those things in the following paragraph:

“Value in basketball terms for a player to me can be easily defined in terms of Wins Produced for the team and we know those are highly correlated to point differential. By that logic, in the simplest terms the MVP must be the player that has generated the most Wins or point differential for his team. Now there are some additional factors to consider. Where you play your homegames is important (i.e. the Jazz and Nuggets players are teeing off from the kiddie tee and I’ll probably expand on this in the future) .”

Now before you get all outraged at me for hating on the Jazz and Nuggets, let me explain.

Baby Patton Oswalt demands satisfaction

This all goes back to my previous post on Homecourt advantage in the NBA (which you can read here). The basic equation goes something like this:

Probability of Home team winning a game (Win %)

= (Projected Wins Home Team-Projected Wins Road Team)/82 +.606

=Win %: (Proj. Home Team Win% – Proj. Road Team Win%) +HCA(.606)

This is the simple equation I came up with for the home team winning  a single game (see here for detail). The base assumption being that based on the data set (all regular season games from 1999 thru 2008  ) the home team wins 60.6% of time) and  this was good and worked fairly well. As I got older and wiser (or at least more creaky), I then decided to add some more factors in:

• Add in the effect of rest days and back to backs.
• Add in the effect of altitude
• Use a more recent data set.

I downloaded every game for the last five years ( see here ). And I went about adding the rest days and altitude. I did that as follows:

• For rest days, I chose three levels:
• 0 for back to backs
• 1 for day of rest between games
• 2 for >2 days of rest
• For Altitude, I also chose three levels:
• Zero to low elevation (430′ or below): Boston, LA, Memphis, Miami, New Orleans, Sacramento,New York City,Orlando,Dallas,New Jersey,Toronto,Houston,Seattle(gone but not forgotten),Portland,Golden State and Washington (hi Ted!)
• Some elevation (430′-1117′): Charlotte (Jordan with just some elevation seems wrong somehow), Milwaukee, Chicago, Cleveland, Atlanta, Indiana, Detroit, San Antonio, Phoenix, Minnesota
• Nosebleed Country (5300-9400′): Denver and Utah

I did some maths (which if you want to read just follow the link already) and figured the homecourt advantage in each scenario over playing at a neutral site. I then put that in a pretty table like so:

In summary, both, altitude and rest days affect the Homecourt advantage (HCA) and they interact with one another. Average HCA is at 59.9%.  Altitude is directly proportional to HCA . Rest days are a little stranger.  Altitude directly interacts with rest. Denver and Utah kill teams at home if they have a rest edge but they get killed themselves if the other team is coming in with at least a two day rest edge.

So how does all this lead to me claiming that Utah and Denver players are playing with nine foot rims? Let’s illustrate. If I:

• Grab last year’s NBA schedule
• Work out scenarios for each game
• Assume all teams are equal in talent (i.e send in the clones)
• And Simulate it!

I get:

So if I assume all teams are equal,  Utah and Denver both get a 10% boost in winning percentage when they play at home. This is good for four extra wins a season versus the average (and about 6.2 Wins against poor Golden State last year). It’s really not a level playing field.