By Ronan Fahy
The author is a currently registered on the MSc in Research (Sports Economics) at University College Cork.
In a flourishing sports economics literature it is fair to say that relatively little attention has been paid to Formula One. With just two races to go in the 2020 season many questions of interest to sports economists exist. Central to these is that of competitive balance.
The story of the season however is the inability of the likes of McLaren, Racing Point and Renault to get past the Mercedes and Red Bull. So far just four drivers secure a race win, which is reflected in race odds. The Haas, Alfa Romeo, and Williams drivers are consistently priced at 500/1, given no chance by the bookies of grabbing a race win.
This is well explained by the odds from the Spanish Grand Prix. Sergio Perez of Racing Point was priced at a very high 40/1 given his fourth place qualification. This was of course as he was starting right behind both Mercedes and a Red Bull of Max Verstappen. In comparison, for the 70th Anniversary Grand Prix in Silverstone, when Max Verstappen had qualified behind Nico Hulkenberg in the Racing Point as well as both Mercedes, he was priced at a much lower 12/1. Which the bookies will have wished was less, as he went on to win the race.
7 time world champion Lewis Hamilton has been consistently priced as favourite for every race this year, with very few fluctuations in this even after some poor qualifying performances. Relating back to outcome uncertainty, with his most recent win in Bahrain, Hamilton has had a win percentage this season of 73%. The highest ever win rate percentage was recorded by Alberto Ascari in 1952 with a 75% win rate. If Hamilton had won the final two races in Bahrain and Abu Dhabi he would have surpassed this and set a new record of 76.4%. However, Hamilton has been forced to withdraw from the race in Bahrain after testing positive for Covid-19.
Previous research has examined the sport. Below are some of the papers that have been published researching both competitive balance and demand in the world of Formula One.
Since the publication of these papers, which all have a common focus of competitive balance and outcome uncertainty we have seen an unprecedented lack of outcome uncertainty in Formula One since 2010. From 2010 to 2020 only three men have managed to lift the World Drivers Championship (WDC) title. Sebastian Vettel (2010,2011,2012,2013), Nico Rosberg (2016), and Lewis Hamilton (2014,2015,2017,2018,2019,2020). As well as that, the World Constructors Championship (WCC) has only been won by two teams, Red Bull Racing (2010,2011,2012,2013) with Mercedes AMG Petronas F1 Team winning it every other year. As a result of this, outcome uncertainty in F1 has never been so low. This lack of outcome uncertainty is reinforced by the fact that Mercedes could have won the WCC this year by only counting Lewis Hamilton’s points and not their second driver Valterri Bottas.
Mastromaro and Runkel (2008) give insight into the effect that rule changes in Formula One have, hypothesising that rule changes reduce the performance of teams and but in turn improve competitive balance between teams. The authors add to this by suggesting that rule changes are only implemented if the FIA’s revenue gain from the introduction of the new rule exceeds that of the existing rule.
Budzinski and Feddersen (2011) note that there are three dimensions to be analysed when looking at competitive balance. These being: race-specific competitive balance, within-season competitive balance and between-season competitive balance. As a result of this research it must be said that although the 2020 season has seen extremely low outcome uncertainty in terms of the WDC and WCC, it has seen one of the highest ever race-outcome uncertainty levels with close to the highest ever number of different drivers seen on the podium in one season.
Schreyer and Torgler (2018) use an interesting revised version of the model used by Budzinski and Feddersen (2011) to proxy outcome uncertainty. The authors describe that although the existing papers method of calculating gini coefficients based on qualifying times to gain a measure of competitive balance is useful, it gives too much weight to the effect that drivers at the back of the grid have on race outcome. For this reason, the authors hypothesize that race outcome uncertainty can be sufficiently estimated using the summed differences between the top three qualifiers.
The author is a currently registered on the MSc in Research (Sports Economics) at University College Cork.
In a flourishing sports economics literature it is fair to say that relatively little attention has been paid to Formula One. With just two races to go in the 2020 season many questions of interest to sports economists exist. Central to these is that of competitive balance.
The story of the season however is the inability of the likes of McLaren, Racing Point and Renault to get past the Mercedes and Red Bull. So far just four drivers secure a race win, which is reflected in race odds. The Haas, Alfa Romeo, and Williams drivers are consistently priced at 500/1, given no chance by the bookies of grabbing a race win.
This is well explained by the odds from the Spanish Grand Prix. Sergio Perez of Racing Point was priced at a very high 40/1 given his fourth place qualification. This was of course as he was starting right behind both Mercedes and a Red Bull of Max Verstappen. In comparison, for the 70th Anniversary Grand Prix in Silverstone, when Max Verstappen had qualified behind Nico Hulkenberg in the Racing Point as well as both Mercedes, he was priced at a much lower 12/1. Which the bookies will have wished was less, as he went on to win the race.
7 time world champion Lewis Hamilton has been consistently priced as favourite for every race this year, with very few fluctuations in this even after some poor qualifying performances. Relating back to outcome uncertainty, with his most recent win in Bahrain, Hamilton has had a win percentage this season of 73%. The highest ever win rate percentage was recorded by Alberto Ascari in 1952 with a 75% win rate. If Hamilton had won the final two races in Bahrain and Abu Dhabi he would have surpassed this and set a new record of 76.4%. However, Hamilton has been forced to withdraw from the race in Bahrain after testing positive for Covid-19.
Previous research has examined the sport. Below are some of the papers that have been published researching both competitive balance and demand in the world of Formula One.
- Mastromarco and Runkel (2008) “Rule changes and competitive balance in Formula One motor racing”.
- Budzinski and. Feddersen (2011) “Measuring competitive balance in Formula One racing”.
- Judde, Booth and Brooks (2013) “Second place is the first of the losers: An analysis of Competitive Balance in Formula One”.
- Schreyer and Torgler (2018) “On the Role of outcome uncertainty of demand in F1”.
Since the publication of these papers, which all have a common focus of competitive balance and outcome uncertainty we have seen an unprecedented lack of outcome uncertainty in Formula One since 2010. From 2010 to 2020 only three men have managed to lift the World Drivers Championship (WDC) title. Sebastian Vettel (2010,2011,2012,2013), Nico Rosberg (2016), and Lewis Hamilton (2014,2015,2017,2018,2019,2020). As well as that, the World Constructors Championship (WCC) has only been won by two teams, Red Bull Racing (2010,2011,2012,2013) with Mercedes AMG Petronas F1 Team winning it every other year. As a result of this, outcome uncertainty in F1 has never been so low. This lack of outcome uncertainty is reinforced by the fact that Mercedes could have won the WCC this year by only counting Lewis Hamilton’s points and not their second driver Valterri Bottas.
Mastromaro and Runkel (2008) give insight into the effect that rule changes in Formula One have, hypothesising that rule changes reduce the performance of teams and but in turn improve competitive balance between teams. The authors add to this by suggesting that rule changes are only implemented if the FIA’s revenue gain from the introduction of the new rule exceeds that of the existing rule.
Budzinski and Feddersen (2011) note that there are three dimensions to be analysed when looking at competitive balance. These being: race-specific competitive balance, within-season competitive balance and between-season competitive balance. As a result of this research it must be said that although the 2020 season has seen extremely low outcome uncertainty in terms of the WDC and WCC, it has seen one of the highest ever race-outcome uncertainty levels with close to the highest ever number of different drivers seen on the podium in one season.
Schreyer and Torgler (2018) use an interesting revised version of the model used by Budzinski and Feddersen (2011) to proxy outcome uncertainty. The authors describe that although the existing papers method of calculating gini coefficients based on qualifying times to gain a measure of competitive balance is useful, it gives too much weight to the effect that drivers at the back of the grid have on race outcome. For this reason, the authors hypothesize that race outcome uncertainty can be sufficiently estimated using the summed differences between the top three qualifiers.
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