How Slow Can You Go?

Dateline: 03/05/97

On February 27, Cleveland beat Chicago with a classic Cleveland score: 73-70. The Cavs got out to an early lead and held it by keeping the game slow. They held Jordan to an unexplosive 23 points and suffocated everyone else. This was Coach Mike Fratello's game plan, and unlike many, this one didn't go awry.

One may wonder why it was Cleveland's strategy to slow the game. Chicago is not known so much as a running team and, with Michael Jordan, they are certainly comfortable in the half court -- so the Cavs could not have been counting on that. In reality, Cleveland always slows the game down, regardless of opponent, but in this game, it played a significant role in helping them win.

Slowing the game down is a ploy of perennial NCAA Tournament upstarts Princeton University. Against heavly favored opponents like UCLA and Georgetown, the Tigers have pulled major upsets or come close by slowing the game. What this does for them is the same thing it did for Cleveland...

Click for Team Ratings

...It shortens the game. A shorter game helps an underdog, especially if they get off to a good start. A little experiment should help demonstrate this.

The Experiment

Our experiment involves two teams -- a favorite who scores 60% of the time (a floor percentage of 60%) and an underdog who scores 50% of the time (floor % = 50%). In order to demonstrate the effect of a slow pace dramatically, we will simulate one very short game of 10 scoring opportunities each and one longer game of 40 opportunities each.

Below (if you have a Javascript-enabled browser), press the Run button and you will see the short and long games simulated (X indicating a made shot and O indicating a miss) along with their scores. To the right, the number of wins and losses for the favorite and the underdog will accumulate. You should see the favorite winning more consistently in the long game compared to the short game. In other words, after several simulations, the Favorite should have a larger winning percentage in the longer games than in the shorter ones. (Since we are simulating an unpredictable reality, there is a small chance that you will not see this. Feel free to write back to me and call me a fool if you think the statistics are lying.)

Short and Long Game Simulations

Score Wins Win %
Long Game
Short Game

From Experiment to Reality

This experiment is just that -- not a real game. It presents results more extreme than what you see in real basketball. A typical basketball games is not 40 possessions, but upwards of 90 or 100 possessions per team. The Cavs-Bulls game had about 78 possessions for each team, slower than even a normal Cavs game. ( Click here to see the pace of all the NBA teams this year, along with the efficiencies of their offenses and defenses.) By keeping the game to only about 78 possessions each, the Cavaliers essentially improved their chances of beating the Bulls from 26% to 34%, a significant increase. I figured this out according to the following worksheet. It shows what the Cavaliers chances of winning are when only 78 possessions are used. If you change the number of possessions to 100, you find that the Cavaliers chances drop to about 26%.

Pace of Game (Possessions)
Bulls Expected Offensive Rating
Cavs Expected Offensive Rating
Cavaliers Odds of Winning

The Bulls' and Cavaliers' expected ratings in the game can be determined any number of ways. Probably the easiest way for most people is to look at Jeff Sagarin's Ratings and calculate based on those, but they can also be done using the Las Vegas Line or using the simple method described here, which is the most scientific and the one I used. Feel free to write me if you want to know more.

What this analysis does not explicitly do is evaluate whether the Cavs or the Bulls play any better or worse at a faster or slower pace. It just says that all things being equal (or unknown), the Cavs improved their odds of winning just by slowing the game. Until someone can provide proof that pace helps or hurts either or both of these teams, this is all we know.

And all those teams looking for some kind of edge against the Bulls in the playoffs should keep this in mind.

Where the Women Are

Hold your testosterone. I'm just giving an update on the status of the ABL Finals. At this point, the Richmond Rage have stolen one game in Columbus to tie the best-of-five series at 1-1. They play game 3 in Richmond on Saturday. ESPN actually broadcast some highlights of game 2, so you may actually be able to find out on your own next week.

The league also named its best players and coach. The league's Coach of the Year was Brian Agler of the Columbus Quest. The league's MVP was Nikki McCray of the Columbus Quest. Strangely, the league actually named players from other teams to its All-League Team. I couldn't find it anyplace on the web, so I guess I'm giving late-breaking news. Here is the First Team:

G Teresa Edwards, Atlanta Glory
G Dawn Staley, Richmond Rage
F Nikki McCray, Columbus Quest
F Crystal Robinson, Richmond Rage
C Natalie Williams, Portland Power