# This is how well the UK is predicted to do in Eurovision final

Every year we look forward to watching Eurovision – the songs, the costumes, the choreography, the drama of how many points one country gives another. But how things will play out is always highly unpredictable.

One company has crunched the numbers and this is how they think Saturday will unfold for the finale of the Eurovision Song Contest.

## Who is tipped to win?

Using their own research, data from Spotify and Eurovision results from 2012 onwards, clothing company Dance Direct have created an algorithm which they’ve used to predict 2019’s Eurovision winner.

Cross referencing all the data collected, they’ve predicted that Duncan Laurence from the Netherlands will win with his song Arcade.

Duncan Laurence previously participated in The Voice Netherlands, where he made it to the semi-finals.

If the prediction is right, it would be the first time in 44 years that the Netherlands would win Eurovision.

The last time they won was in 1975 with a song called Ding Dong by Teach-In.

## How will the UK do?

The algorithm predicts that the UK’s entry Bigger Than Us performed by Michael Rice will place 15th in the final results.

This places us almost ten spots higher than last years result which saw the UK weigh in at 24th with Storm by SuRie, which famously was the target of a stage invasion.

The last time we won Eurovision was in 1997 with Love Shine A Light by Katrina and the Waves.

## What are the elements of a Eurovision winner?

The algorithm is broken down into eight key factors that make a winning song.

## Gender

Male contestants are more likely to place higher than female singers, but not by much.

A male solo act places on average at 11th, while female solo acts on average place at 15th position.

## Group vs Solo

Solo acts were found to top group acts on average. With a higher percentage of solo entrants, there has been a higher percentage of solo winners.

If an entry does decide to go for a group act, it seems like bigger is indeed better.

Groups made up of six members (the highest number permitted for a group act) were found to do the best, followed by duos.

Whilst the numbers showed that a group is more likely to be made up of a mix of genders, followed by all male and lastly all female, all-female group performers actually score the best.

All-female groups tend to do better than female solo acts, whereas it’s the opposite for male performers.

## BPM

Beats Per Minute (BPM) is the term used for measuring the speed of a piece of music.

According to the data, the perfect tempo for a Eurovision song lies somewhere between 100 – 109 beats per minute.

Toy by Netta, 2018’s winning Eurovision performance comes in a bit higher at 130 beats per minute.

The UK’s 2019 entry, Bigger Than Us, performed by Michael Rice comes in a little lower at just 82 beats per minute.

## Dance-ability

Equated into a numerical score, the higher the score the easier a song is to dance to.

Supposedly the perfect window for dancing lies between 70 – 79.

## Energy

This is different to dance-ability. While the perfect dance-ability is found in the 70’s, the numerical perfection for energy is actually down in the 40’s.

## Loudness

The higher the value of decibels (a unit used to measure the intensity of a sound), the louder a song is.

The perfect amount of loudness allocated to a song by the algorithm is minus nine.

## Valance

In broad terms, valance is used to measure how something makes us feel.

As Spotify explains: “Is an event, situation, or experience going to add to your mood, or detract from it? That’s how you can calculate its emotional valence.

Our reaction to music is also emotional. Some of it makes us happy, and some of it makes us sad, with songs falling all across the spectrum between happy and sad.”

The higher a value given to the valance, the more positive the mood of the song is.

The algorithm has placed optimum valance at between 40 – 49.

## Finally, speech-iness

This is used to measure the amount of spoken word a song contains, versus actual singing.

The algorithm allots a value of 5 – 9 for the level of spoken word in a song.