In Part 2 of my Uni Games review, I looked at the five teams with the best point differential per game.
Team A: +7.9
Team B: +5.4
Team C: +4.6
Team D: +3.5
Team E: +3.5
These teams were, in order, Sydney Uni, Flinders, Monash, UWA, Adelaide.
Most folks guessed Sydney at the top correctly, then it was a mix of correct and incorrect guesses.
Here is a graph. All game results and the graph are here. Scores came from AFDA.
The point differential measured here is good predictor of ability, in a single number.
Let's look at an example. Deakin had 5 wins and 6 losses for the tournament. Meanwhile La Trobe went 5-5. They seem pretty close? I mean La Trobe only finished one spot higher. Actually, La Trobe was losing games to the best teams by only a few points, and generally thumping low teams. While Deakin never got closer than 6 points to a top 8 finishing team.
The point differential shows this: La Trobe +3.1 and Deakin -2.6.
What else do we notice?
Flinders had a point differential of +5.4, lower than Sydney Uni (+7.9), who had swept through all their opponents more easily than anyone else. So Flinders' win in the final can be considered an upset, given Sydney's scoring ability.
Melbourne Uni, the team that finished 4th, finished higher than point differential would predict, while Monash finished lower (7th). Melbourne's one-point victory in the quarterfinal (the single game that changes final position the most) over Monash was responsible for that.
Point differential isn't strictly comparing apples with apples. Some players get injured. Some teams rest their stars for parts of games. And the teams did not play all other opponents.
What is consistent is that the top 8 teams played 3-4 pool games, 4-5 crossover games against strong opponents, and then 3 games against strong opponents. So comparisons between them are pretty reliable. Latrobe, Deakin, Murdoch and Ballarat had a different run, playing 3 weaker opponents to finish the tournament. La Trobe, in particular, feasted on RMIT and ECU on Thursday (15-2 wins both games) while the top 8 teams were playing strong opponents.
The remaining 7 teams had weaker opponents for the majority of the tournament.
A glance at the graph of point differential does show 9 elite teams though, that matches well with subjective observation at the tournament.
And the graph does point out how much better ANU were than their final finishing place of 15th.
Is point differential useful? Well, next time you are at tournament and want to predict the outcome of key games such as semis and finals, check out the scoring margins from previous games. There will always be occassional upsets, but on average, the team with a higher point differential goes through.