A Specific Example of Representation of a Basketball Game

We are searching for a scheme for music generation which is robust enough to take data collected at basketball games which show which five players of one team are on the playing court at a given time and how the relative score changes with each combination of players. This problem is interesting because it is simple enough to understand (help the coaching staff recognize which combinations of players are most effective) but because the data is relatively complex (there are 12 players on the team, only 5 play at a given time, and player performance is of course not consistent).

As a case study we initially hand coded simplified data from the first half (20 minutes) of the West Virginia Universitgy versus University of Georgia basketball game of December 2, 1998.

Table 1 shows which five players (by player number) were playing at each minute of the first half of the game as well as the score of each team at the end of that minute.

We somewhat arbitrarily assigned notes to each of the players as shown in Table 2.

The melody generated from this first assignment of notes to players is given in Music 13. In this example the number of notes per measure indicates the relative amount by which our team is ahead.

We chose a permutation of notes based on change ringing:

1 2 3 4 5; 2 1 4 3 5; 2 4 1 5 3; 4 2 5 1 3; 4 5 2 3 1; 5 4 3 2 1; 5 3 4 1 2; 3 5 1 4 2; 3 1 5 2 4; 1 3 2 5 4

We chose this particular permutation in large part because it repeats every ten steps, or four times in a 40 minute basketball game.

In the first measure we play the notes for the starting players in order of center, two guards, and two forwards. In the second measure we permute the position of the notes for the center and the first guard and the notes for the second guard and first forward. As one player is substituted for another we change the pitch associated with that playing role but continue with the permutation. For example, in minute 7, player 34 replaces player 25. By our permutation sequence, measure 7 of the music should have contained the notes in order E F G C A but instead uses D for A, giving E F G C D.

We used Finale Allegro to transpose measures in which our team was behind into a minor key, trying several keys until we found one that for this combination of players/notes sounded "sad." The resulting music does indicate even to first time listeners that something is different in that minute/measure, but by choosing the minor key arbitrarily we lost the consistent mapping of a player to a note.

In another attempt, rather than transposing losing measures to a minor key we lowered the pitch by an octave. The result is given in Music 14.

We have generated various other melodies based on this same basketball game. Other variations include changing how notes are associated with players, using one instrument when our team is ahead and a different instrument when our team is behind, and using percussion instrument accompaniment to indicate relative score.

While we would prefer to have losing measures in a minor key, we have not yet developed an algorithm which regardless of the combination of players always produces a measure in a minor key while retaining the identification of players and notes.