Statistics for Sports League Qualification

Question

How can one quantify and predict the needed points for qualify in a league given an up-to-date results registry?

For instance, regarding Basketball Euroleague, there's 8 teams in a league with direct crosses, twice for team (local/visitor). A victory is a point, and draws are not possible. Only the first four scorers after all direct crossings, pass to next round.

So some final table possibilities (P*) could be:

TEAM  P1 P2 P3  P4 ...
A    12  7  14  10
B    12  7  12  10
C    12  7  10  10
D     4  7   8  10  -> X: Price of qualification
     --------------
E     4  7   6  10
f     4  7   4   2
G     4  7   2   2
H     4  7   0   2

How can I quantify X? Perhaps as a coefficient of qualification hardness? I already deducted that a team cannot qualify if it does not win at least 4 matches (then goalaverage/basketaverage takes part), and that it would be qualified mathematically if it wins 11 matches, without historic data.

In some way hardness could be mesured by median, but, there is no function or progression here. How can I put in, historical info?

For instance,current table is 7,7,6,5,5,4,4,2 with 10 games played per team (missing only 4). But according to median, they still could tend to 7,7,7,7,7,7,7 at the end of the league.

How can I quantify accurately the hardness of qulification in current situation and/or predict the expected cost of qualification? Considering itstatistically, 7.5 victories are needed to qualify, but I guess the 4 previous column alternatives must be scoped different variable.

I know my question is vague, but I am not mathmeatical, I am wondering how an statistics man would approach this, and what tools would use to quantify and predict that wieght.

Thanks!!

EDIT: In the end, I look for a mathematical tool to say that given 2 possible current tables, measure the relative hardness (between themselves, or over a reference as a coefficient, to finishing qualifying, by current or milestone points)

Answer 1

You could compute ELO ratings (https://chess.stackexchange.com/questions/1377/is-there-any-software-or-web-service-for-club-level-elo-ratings) for the teams based on the outcomes of the games already played. Then, determine the most probable outcomes for the remainder of the schedule to determine the most probable final standings.