THE POWER RANK

3 steps to predicting the Women’s World Cup 2023

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You want to bet on the World Cup even though you don’t follow women’s soccer. It isn’t easy with the media coverage that focuses on the United States but has less on other contenders.

Let’s look at the three step process I’ve developed to get an overview of the World Cup and identify a futures bet. It will involve analytics on the team level and wisdom of crowds on the player level.

Almost always, women get less than the men in sports. However, I will highlight one way in which women get an edge on the men. Let’s get started.

1 – World Women’s Rankings – For a quant like myself, I always start with a data driven approach.

Based on match results in top international competition since the last World Cup in 2019, I ranked teams by taking margin of victory and adjusting for strength of schedule (referred to as TPR for The Power Rank below). I did the same for xG, or expected goals based on shot quality, although the data was limited to the last World Cup and European Championship.

These were the results I shared in 5-Nuggets that had the United States as the favorite with England and France as strong contenders. I debated expanding this calculation and including friendly matches. However, injuries and player absences suggested that more data would only be so useful.

Except for Germany and Sweden, all the top contenders are dealing with injuries. For example:

  • Mallory Swanson, United States, 32 goals in 88 caps, knee.
  • Marie-Antoinette Katoto, France, 108 goals in 113 matches with club PSG, knee.
  • Vivianne Miedema, Netherlands, 95 goals in 115 caps, knee.

While the rankings suggest value in France at 11-1, the injury to Katoto should make one cautious about this bet. With these changing rosters, it is more important to expand the set of metrics than make any one more accurate.

2 – FIFA Rankings – Women almost always get worse treatment than men in sports. The lone exception is the FIFA rankings.

While both the men and women use an Elo type updating, the women’s rankings uses goals and goal difference in the calculation. Even though this data enhances the accuracy of rankings, the men’s rankings do not use it.

The men’s rankings have Germany as the 14th best team in the world, behind the United States at 11th. That’s more of a joke than giving $25M per year to an NFL running back. In contrast, the women’s FIFA rankings actually make sense.

Let’s look at the top 10 teams by the markets to win the World Cup and compare with the three different rankings I’ve discussed. The market data is from FanDuel as of Wednesday morning.

  • United States +240 (1st TPR, 1st FIFA, 1st xG)
  • England +430 (2nd TPR, 4th FIFA, 3rd xG)
  • Spain +550 (11th TPR, 6th FIFA, 5th xG)
  • Germany +750 (3rd TPR, 2nd FIFA, 4th xG)
  • Australia +900 with home advantage (12th TPR, 10th FIFA, 14th xG)
  • France +1100 (5th TPR, 5th FIFA, 2nd xG)
  • Sweden +1800 (6th TPR, 3rd FIFA, 6th xG)
  • Netherlands +2300 (4th TPR, 9th FIFA, 11th xG)
  • Brazil +3200 (7th TPR, 8th FIFA, 12th xG)
  • Canada +3400 (8th TPR, 7th FIFA, 8th xG)

A team that stands out is Sweden, as they have the 7th best odds to win but have higher rankings by the numbers.

3 – Player rankings – With all the injuries to top teams, it’s also important to look at the top players for each team. Taking a wisdom of crowds approach, let’s look at a few different sources:

In addition, the two rankings have Sam Kerr of Australia as the top player. She will have home advantage in this World Cup.

These player lists also show a strong set of core players for Sweden:

  • Fridolina Rolfo – full back for Barcelona but plays a more attacking role for Sweden (25 goals in 78 caps).
  • Kosovare Asllani – a midfielder and play making #10 that plays for AC Milan.
  • Stina Blackstenius – a striker for Arsenal that has 28 goals in 90 caps for Sweden.

Along with the lack of injured players, these metrics suggest value in Sweden at 18-1 to win the World Cup (available on FanDuel).

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The one thing about soccer analytics, Champions League final prediction

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Matthew Benham made a lot of money betting on soccer. After getting a physics degree from Oxford and more than a decade in the financial industry, he used predictive analytics to win at soccer betting.

After his financial success, Benham did what all little boys dream of doing: he bought his favorite soccer team. Benham became the owner of Brentford in 2012, a third league team back then.

Benham wanted to apply the quantitative tools he used at betting to win at actual soccer matches. However, this was difficult at an English club with decades of inertia.

This prompted Benham to buy FC Midtjylland, a soccer team in Denmark. As Ryan O’Hanlon describes in his excellent book Net Gains, the team got to work on the primary suggestion from analytics: scoring goals on set pieces.

Back then, there was controversy about this approach. If a team spends practice time on these scripted plays that start with a dead ball (corners, free kicks), then the team won’t score as many goals in open play. There is only so much practice time, and it should be spent on the unscripted nature of open play.

Benham, as with most professional bettors, didn’t care about this conventional wisdom. FC Midtjylland scored 25 goals from set pieces in 2014-15, the first year they won the Danish first league. No other team had more than 11 set piece goals.

Instead of keeping their strategy a secret, they went full Billy Beane and told everyone. A few years later, every Danish team was working set pieces. In 2017-18, FC Midtjylland won the league with 25 set piece goals, but two other clubs also had 20 or more.

From 2014-15 to 2017-18, the rate of set piece goals rose from 0.55 to 0.75 per game in the Danish league. However, total goals per game also increased. The increase of 0.5 goals per game meant an increase in open play goals despite the emphasis on set pieces.

This one thing about soccer analytics continues to apply to the game today.

Heading into the 2022-23 season, the Guardian predicted Brentford to finish 16th in the Premier League. The sports writers figured they would slump in their second season in the top league. 

Instead, Brentford finished 9th. Matthew Benham’s team had 16 set pieces goals, 2nd best in England’s top league.

In 2022, famous NBA bettor Haralabos Voulgaris bought CD Castellon, a Spanish team in the third league. Like Benham, he promised to use player analytics and set piece goals to improve the fortunes of the team.

This season, CD Castellon finished third in Group 2. This makes them one of eight teams in a playoff fighting for two promotion spots to the second league. Set pieces almost certainly played a role in their advance.

How about the absolute top level of the game? Manchester City faces Inter in the Champions League final on Saturday, but neither team excelled at set piece goals.

The Analyst, an excellent site from Opta, has set piece data. For any shot off a set piece, they calculate the xG, or the probability of that shot to become a goal. The total xG for the season gives an expected number of goals. 

  • Manchester City, 13.6 xG, 9th in Premier League (14 goals)
  • Inter, 14.1 xG, 3rd in Serie A (11 goals)

In my adjusted xG, Man City has a 56.1% chance to win in regulation. Assuming a coin toss in a penalty shoot-out, Man City has a 67.7% chance to win over Inter. 

The markets are higher on Man City. As of Thursday, Pinnacle has a 81.8% break even probability to win over Inter.

Summer reading that makes you smarter

Soccer is twenty years behind baseball in the analytics revolution, but that’s what makes the sport such an opportunity.

Ryan O’Hanlon of ESPN writes about soccer analytics in his awesome book Net Gains, which includes stories about:

  • The religion PhD who did seminal work in xG
  • The sports bettor from Indiana who might be making a bigger contribution to soccer analytics than Matthew Benham

I loved every page of this book. It will not only make you smarter the minute you crack it open but also entertain you the entire way.

Check out Net Gains for an awesome summer read.

Podcast: Ted Knutson on betting, soccer and American football

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Ted Knutson, the CEO of StatsBomb who has also worked a professional bettor and book maker, joins the show for a wide ranging conversation. Highlights include:

  • Magic the Gathering as an entry into the betting world (6:06)
  • How to improve yourself (11:24)
  • Ted’s process as a professional bettor (14:23)
  • Working at Pinnacle sports book (17:20)
  • The soccer market at Pinnacle (23:52)
  • From betting to soccer data and analytics (26:41)
  • The xG model of StatsBomb (33:10)
  • Set pieces in soccer (36:12)
  • World Cup 2022 (40:52)
  • American football data and analytics (43:23)

This was an amazing conversation that has something for everyone, whether your primary interest in data, analytics or betting. To listen here, click on the right pointing triangle.

This episode of The Football Analytics Show is also available on:

Support the podcast on Patreon.

Podcast: Ryan O’Hanlon on soccer, analytics and World Cup 2022

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Ryan O’Hanlon of ESPN joins the show for a wide ranging conversation on soccer, analytics and the World Cup. Highlights include:

  • The evolution of soccer analytics over the past decade (5:54)
  • His new book Net Gains (14:00)
  • The optimal way to play soccer (19:25)
  • The World Cup favorite (32:26)
  • A World Cup dark horse to win (41:08)
  • USMNT (45:43)
  • The critical concept of xG (54:04)

Ryan’s book Net Gains is amazing, and I think it’s a must read for anyone interested in soccer or analytics. To listen, click on the right pointing triangle.

This episode of The Football Analytics Show is also available on:

Podcast: Mike Goodman on soccer analytics, Euro 2021

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On this episode of The Football Analytics Show, I’m joined by Mike Goodman, Senior Soccer Editor at CBS and co-host of the Double Pivot podcast.

Among other topics, we discuss:

  • A primer on expected goals, or xG (3:04)
  • The impact of offsides and own goals on xG (10:10)
  • The frontiers of soccer analytics (15:14)
  • Which style of play works best on the international level (18:03)
  • Belgium (24:35)
  • Italy (29:40)
  • Spain (33:25)
  • England (39:40)
  • A surprise team to win Euro (45:00)
  • USMNT (47:08)

Mike is a soccer analytics expert and does an amazing job explaining the concepts.

To listen here, click on the right pointing triangle.

To listen on Spotify, click here.

To listen on Apple Podcasts, click here.