I did not find any official details on what mathematics was behind the final result. However, my guess is votes were converted into scores (using percentiles for example), and averaged with judges’ scores. This would then yield a result similar to what we got, because judge scores were in the range 23 to 30, whereas prorated vote scores would be in the 0 to 30 range (might not start at zero, but the point is, it would start very low). So, while the worst performer as per judges got a score of 23, the worst voter got a very low score, say 10.
I have written about normalization before. I believe the use of this technique would have yielded more fair results. Normalization brings a set of values to a common mean, and a common standard deviation. Below is a comparison – I have taken guesses on how many votes each contestant received. First, prorating:
|Group||Judges score||Votes||Voting score||Voting score prorata||Final score|
|Manas Kumar Sahu||28||9000||0.0251||2.7||15.35|
Next, with the use of normalization:
|Group||Judges score||Votes||Voting score||Nor Judges score||Nor voting score||Final score|
|Manas Kumar Sahu||28||9000||0.025||26.041667||22.927||24.484|
Several improvements can be seen: Fictitious group has moved deservingly up; Teji Toko has moved down; Acroduo has moved upwards etc. Note again that the number of votes is just a guess (educated one, keeping relative popularities in mind). However, the point is, that with normalization being added to the calculation procedure the same number of votes can bring about a more fair result.