I think you may achieve what you need doing as follows. If you've got n number of teams, all the possible matches between teams can be represented with a Kn Complete graph.
The way I would come up with your desired sorting, is taking (removing) edges from that graph, one at a time, always trying to find an edge that matches teams that didn't match immediately before. Further more, I think this approach (with a little variation) can be used to generate the best way to maximize concurrent matches, if each time you take an edge you pick the one with the teams that haven't played in most time.
For simplicity, lets assume that teams are ints in the range of 0 to n-1. The graph can simply be represented with a boolean matrix. To pick the match with the teams that haven't played in most time, you can keep track of the last time each team played. For n
teams, you'll have a total of n*(n-1)/2
number of matches.
IEnumerable<Tuple<int,int>> GenerateMatches(int n) {
bool[,] pendingMatches = new bool[n,n];
for (int i = 0; i < n; i++) {
for (int j = 0; j < i; j++)
pendingMatches[i,j] = true;
}
int[] lastPlayed = new int[n];
int totalMatches = n*(n-1)/2;
for (int m = 1; m <= totalMatches; m++) {
Tuple<int, int> t = null;
int longestPlayed = -1;
for (int i = 0; i < n; i++) {
for (int j = 0; j < i; j++) {
if (pendingMatches[i,j]) {
int moreRecentlyPlayed = Math.Max(lastPlayed[i], lastPlayed[j]);
int timeSinceLastPlay = m - moreRecentlyPlayed;
if (timeSinceLastPlay > longestPlayed) {
longestPlayed = timeSinceLastPlay;
t = Tuple.Create(i,j);
}
}
}
}
lastPlayed[t.Item1] = lastPlayed[t.Item2] = m;
pendingMatches[t.Item1, t.Item2] = false;
yield return t;
}
}
The part that chooses the next match are the two most nested fors. The complexity of that part can be improved if you use some kind of priority queue adapted to adjust the priority of edges that involve the teams of the last picked edge after updating the lastPlayed array.
Hope that helps.