Throughout the history of this site, it has always been my intention to create a ranking system that did what most people want it to do - show the current strengths of teams as accurately as possible.  It should be noted before I go further that no ranking system will ever reach 100% accuracy, as this would mean it was static and teams could never change position.  The whole idea of a ranking system is to create a dynamic list of teams whose order changes over time based on the results of the matches they play.

    My first attempts were based solely on the elo model, a description of which can be found at the elo ratings site here.
    This had been the best attempt at ranking teams that I had seen at that time, and I employed it with a few changes as the ranking for The Roon Ba.  However, it soon became clear that the elo ratings had some disadvantages, which I will outline below.

    1) - A team's start rating must be estimated - introducing a great deal of subjectivity every time a new team enters the ranking.
    2) - Teams cannot gain points for 'good' defeats.  So, if Tuvalu play the game of their lives and lose only 1-0 to Brazil, they would actually lose points while Brazil would gain points (admittedly, a very very small number, very close to zero points).  However, the cumulative effect of this can be seen with teams who consistently play against good teams and lose often (for example, Luxembourg) when compared to teams who win a few games against poorer opposition (for example, Papua New Guinea). 

    In recent elo rankings, for example, Papua New Guinea have been rated higher than Luxembourg.  It is debatable whether Papua New Guinea could hold France or Germany to a 3-0 or 4-0 defeat.  And it is also debatable whether Luxembourg would lose 9-0 or 10-0 against Australia.  I would certainly think Luxembourg belonged above Papua New Guinea on current strength, but the cumulative effect of not awarding teams for 'good' defeats and awarding teams for poor wins against lowly opposition means that teams like Luxembourg will always be held ransom by the confederation to which they belong.  If Luxembourg played in the OFC, for example, they would have a much higher elo rating.  This kind of situation led me to seek another way to rank the teams.

    		 Without discarding the elo system altogether (it has its merits), I now use a modified version of it on the site.  The main differences between The Roon Ba elo formula and the standard elo formula are that matches are divided into only 2 types - competitive (for regional, continental and world tournaments) and non-competitive (for friendly matches and friendly tournaments). A competitive match has twice the weight of a non-competitive match.  Also, the formula has been altered slightly to allow teams to gain points for losing 'well' and to lose points for winning 'badly'.  This ensures that the ratings change reflects what is actually the case as shown by the result of the match - the teams are getting closer together.  The third difference, and perhaps the part that was most difficult to implement - is the automatic assigning of a start rating for each team.

    Only one team is given a start rating (which can be any number - I have generally chosen it to be around 2500 points so as to avoid negative points totals at the bottom of the ranking).  From this one team's start rating - all other start ratings can be calculated.  Let's use a simple example - say Team A is given a start rating of 2500 points, and in their first match, they draw 1-1 with Team B at a neutral venue.  Team B's start rating will thus be 2500, and this rating will be used in the calculation for their next match.  If Team B had lost 1-0 to Team A, they would have a lower start rating (let's say 2400).  In this way, there is hardly any subjective input at all.  The elo system is applied to the entire database of results (from 1872 onwards) and is repeated in 101 iterations to increase the accuracy.

    One further modification to the assignment of start elo ratings is that the start rating is dynamic until that team has played 10 matches.  That is to say, it is not fixed.  The elo formula for that team does not start until after its 10th game.  Until then, the team is given numerous start ratings, and these start ratings are added together and divided by the number of games that team has played.  This allows a team to settle into a more realistic position before their rating is fixed.


    The same program (written in Python, with a lot of help from Martin Arenlind of Sweden, with significant advice from and discussions with Norbert Jäger of Germany) is used also for futsal and beach soccer.