The first part of the 2022/23 Serie A Women season has just come to a close. Roma have looked like the best team so far. However the recent clash between them and Juventus has reopened the race for the top spot. The table already sees stark differences between the top 5 and the bottom 5 teams which are separated by 9 points. In this analysis, we look into the league structure and at the best team and player performances at the season break.
Since the current season, the women’s Serie A has become a professional league. The league now consists of 10 teams (down from the previous 12) who face each other twice (home and away). After these 18 games the league will be divided into two blocks of 6. The top 5 feature against each other in a poule which is worth the title (each team will face the other four teams twice), whilst the bottom 5 feature in a poule to determine relegation (also in this case each team will face the others twice). Each team will start the poule with their regular season points total. At the end of the poule, the 2 top teams obtain qualification to the following season’s Champions League. The last team will be directly relegated to the Serie B, while the penultimate team faces a playout against the 2nd classified Serie B team.
Current standings: Actual vs. Expected performance
After finishing first for five consecutive seasons, Juventus find themselves with 27 points, chasing the league leaders AS Roma, who have accumulated 30 so far. Roma have showcased the best performances in the league so far, ranking as the best for xG (Expected Goals, 23.6) and xGA (Expected Goals Against, 6.0). However, the clash against Juventus during the last matchday has halved their lead from 6 to 3 points, leaving everything to fight for in the remaining part of the season. While Juventus have the best attack in the league with 32 goals scored (and the most significant outperformance of xG in the league, +8.7), Roma have the best defence in Serie A with just 7 goals conceded (not to mention they conceded 4 in their last clash against Juve which means they conceded only 3 in 11 games prior to that).
Fiorentina (coached by the legendary Italian striker Patrizia Panico) trails with 25 points in third place. Their performance in terms of goals scored (21) and conceded (16) is in line with their respective Expected Goals (19.8) and Expected Goals Against (15.9). Internazionale follows in 4th place with 22 points. The team coached by Rita Guarino has the second best attack (28 goals scored) and the second most significative outperformance of xGD (Expected Goals Difference, +6.7) behind Juventus. An SGA (Shooting Goals Added, explanation can be found further on) value of +7.8 can partly explain such outperformance.
AC Milan conclude the top 5 with 19 points. With 25 goals scored they have the 3rd best attack in the league and they have the second highest outperformance of xG in the league (+6.6). The majority of the offensive burden lays on the shoulders of Asllani, Piemonte and Thomas.
Sassuolo, Como, Sampdoria and Pomigliano all trail with 10 points each. With just 6 games left in the first phase it will be difficult for these teams to regain 9 points from the 5th spot currently held by AC Milan.
Sassuolo are just one of 3 teams in the league (Internazionale and Sampdoria being the others) who have managed to outperform their Expected Goals Against. Como and Pomigliano are performing in line with their Expected Goals Difference (-6.1 and -10.7 respectively).
Sampdoria are severely underperforming their xG (-8.3) and are one of 3 teams in the league to do so (however Roma and Parma have only slight underperformances). Part of their underperformance can be explained by Shooting Goals Added (-1.78). Consequently, their underperformance of Expected Goals Difference by -6.6 is the 2nd highest value in the league after Parma’s one (-11.3). The team from Emilia has currently the worst defense (33 goals conceded) and the worst goal difference in the league (-22), however their Expected Goals Difference (-10.7) is comparable to those of the other 4 teams in the bottom 5.
Comparison with the 2021/22 season
Among the teams who have played in the last two Serie A seasons, only 3 teams have improved their underlying performances (Roma, Sampdoria and Internazionale). On the other hand, teams such as Sassuolo, AC Milan and Juventus have suffered a significant drop from last season.
Sassuolo has suffered the greatest drop in underlying defensive performance (-0.68), followed by AC Milan (-0.48), Fiorentina (-0.28) and Juventus (-0.26)
Sampdoria emerges as the most improved team with regards to xGD, however they haven’t managed to translate the better underlying performances in better results considering their strong underperformance. Internazionale and Roma, instead have been able to improve their performances from last season.
Juventus have been able to compensate the drop in Expected Goals Difference by overperforming their Expected Goals. Fiorentina have had a slight drop in Expected Goals Difference but are achieving much better results, considering that last season they were among the greatest underperformers. AC Milan and Sassuolo, on the other hand, suffer a significant drop from last season. Although AC Milan’s drop has been less significant thanks to an overperformance of Expected Goals by part of their forwards Asllani, Piemonte and Thomas, who have also accumulated a combined Shooting Goals Added value of +1.8 between the three of them.
Roma, Juventus and Internazionale are the most dominant teams in possession (61.4%, 60.3% and 57.4% respectively), considerably above 4th ranked Sassuolo (50.7%). These teams are those who try to maneuver the most (as can also be seen by their Field Tilt and passing numbers).
Other teams such as AC Milan, tend to adopt a more vertical style characterized by high pressure and bursts into space taking advantage of the physicality of players such as Piemonte and Thomas.
Pomigliano, Parma and Sampdoria have the lowest values of Field Tilt, suggesting that they tend to leave possession to their opponents and adopt a counterattacking strategy (many passes conceded in their defensive third and/or few passes made in the opposition third).
Shooting and finishing
Tabitha Chawinga has emerged as perhaps the brightest prospect in Serie A during her debut season. The Angolan is currently the top scorer in the league with 9 non-penalty goals (greatly outperforming her 4.6 non-penalty Expected Goals, 0.62 npxG per 90 minutes) or 1.2 non-penalty goals per 90 minutes. Not only is she the top goalscorer, she also ranks 1st for assists served (tied with Grosso) with 5 (2.6 Expected Assists) or 0.67 assists per 90 minutes showing what a truly devastating impact she has had.
Her teammate Polli follows with 7 goals (1st in the league for non-penalty Expected Goals per 90 minutes with 0.64) tied with Juventus forward Girelli (3rd for non-penalty Expected Goals per 90 minutes with 0.61) and Asllani who is the 2nd greatest outperformer of non-penalty Expected Goals in Serie A (+4.0). Beerensteyn is the 3rd greatest Expected Goals outperformer in the league with 6 goals in front of 2.8 non-penalty Expected goals (+3.2).
Giacinti and Gago are also among those players who have accumulated the most chances P90 (0.57 and 0.54 non-penalty Expected Goals per 90 minutes respectively). Unluckily for Lázaro, she is yet to score despite having accumulated 0.59 non-penalty Expected Goals per 90 minutes. Shooting Goals Added partly explain her underperformance (-1.5 the 5th lowest value in the league).
Shooting Goals Added (SGA) are a good indicator of a player’s shooting ability. They are calculated as Expected Goals on Target minus Expected Goals. It is important to underline that all blocked shots or shots which finish outside of the goalmouth have a value of 0 for xGoT (Expected Goals on target or Post-Shot Expected Goals) computation and that we have excluded penalties. This allows to partly give credit to the shooting ability of players and justify part of a given players outperformance or underperformance of non-penalty Expected Goals.
The top ranking players feature 2 Pomigliano players in the top 5 (Tatiely and A. Martinez with values of +2.4 and +1.6 respectively). Girelli ranks 2nd with a value of +2.1. While surprisingly Chawinga has a Shooting Goals Added value of just +0.1, Asllani and Beerensteyn partly explain their outperformance of xG thanks to their shooting ability (+1.1 Shooting Goals Added for both of them). Giugliano and Andressa complete the top 5 with values of +1.6 and +1.3 respectively.
Chawinga and Grosso lead the assists chart with 5 assists each. Grosso is greatly outperforming her 0.7 Expected Assists, which will make it difficult to sustain her current rate of 0.74 assists per 90 minutes. Mascarello has found her form in recent weeks serving numerous assists thanks to her crosses and set-piece delivery.
Cernoia ranks 1st for Expected Assists per 90 minutes with an average of 0.61 and 6th overall despite having played just 445 minutes. Karchouni, Caruso, Giugliano, Boquete and Chawinga make the top 5 for overall Expected Assists. Despite ranking 7th overall with 2.4 Expected Assists, Rincon is yet to have one of her chances converted into an assist by her teammates, who are the greatest underperformers of Expected Goals in the league.
Stefanie van der Gragt has the highest aerial duel win % (81% on an average of 3.7 aerial duels per 90 minutes) among Serie A players well above 2nd placed (Ceccotti and Rosucci with 75% who have contested significantly less aerial duels, 1.5 and 1.4 P90 respectively). Julia Karlernäs also stands out in terms of aerial duels contested and won (5.3 and 3.8 respectively with a success rate of 72.5%, 4th overall and the highest among midfielders). With a success rate of 61.5% on her 4.7 aerial duels per 90 minutes, Martina Piemonte is the forward with the highest percentage of aerial duels won. Her success rate is particularly impressive considering she is a forward and defenders are usually advantaged by their positioning and other factors during aerial duels.
Martina Piemonte, who has scored 3 goals and provided 2 assists in 751 minutes played so far in Italian Serie A Women, signed an agreement to become XSEED Key Female Player. In the agreement, Soccerment become the player’s official Sports Tech Partner. In the link below, the Instagram post related to the agreement.
As part of the agreement, Martina Piemonte and her staff receive detailed data-driven reports after every league match or any selected timeframe. Here is a link to the match report of her performance against Fiorentina, when she scored a brace in Fiorentina – Milan 1-6.
Sophie Haug is by far the player who contests and consequently wins the highest number of aerial duels per 90 minutes (8.4 and 4.8 respectively with a success rate of 57.1%).
Goals prevented are a measure of a keeper’s ability or luck in preventing the shots which they face. They are calculated as Expected Goals on Target (or psxG) minus goals conceded.
Francesca Durante of Inter has been the keeper who has been able to prevent the highest amount of goals with +4.2 followed by Magnin of Juventus with +3.3. Baldi would feature in the top 3 but doesn’t reach the minimum amount of minutes played (270) to feature in the list. The other keepers with positive values are Beretta of Como and Tampieri of Sampdoria.
Main data differences vs Serie A Men
To put the data we presented in context, we looked at the main differences between men’s and women’s football which emerge from this season’s Serie A. We collected a sample of 150 matches for men and 90 matches for women.
Our main results are summarized in the bar chart below. Naturally, a full statistical comparison between men’s and women’s football would require a much more in-depth study and would have to consider many biases, such as the one related to sample size and league structure, which go beyond the scope of this post. Here we simply outline a brief comparison of basic stats.
Shooting and finishing
What emerges is that in women’s football there is a higher number of goals (3.08 vs 2.52 per match), resulting from a slightly higher number of shots (29.02 vs 25.79 per match) and a higher conversion rate (10.63% vs 9.77%).
With regards to passing, we noticed a significant difference in the average passing completion rate (73.4% for women, 80.8% for men). It is important to notice that the average number of attempted passes is actually slightly higher for women than for men (859.3 vs 853.8), so the difference in completed passes (631.0 vs 689.7) is driven mainly by accuracy rather than the volume of passes.
Another significant difference lays in the number of accurate crosses completed (4.43 vs 8.81) per match. While men complete on average 26.0% of their crosses, women complete an average of just 12.5%. This means that women actually attempt more crosses than men (35.5 vs 33.8), so once again the main difference actually comes down to accuracy.
Another very significant difference lies in aerial duels. Women’s football features just over half the amount of aerial duels as men’s football (16.4 vs 26.2). Instead, the number of fouls per match is almost identical in women’s football (24.7 vs 24.7).
In this blog post we have reviewed the current state of women’s Serie A league as it stands at the winter break. Advanced metrics and stats confirm the clear divide between the top five and bottom five teams in the table, with table leaders Roma showing the best Expected Goals difference (xGD), followed by Juventus, who are significantly outperforming expectations in front of goal, and Inter. The same three teams lead the league in terms of territorial dominance, being the only teams with Field Tilt values well above 50%. In terms of individual player performances, top scorer Chawinga of Inter is greatly outperforming her 4.6 xG with 9 goals, while Juventus’ Girelli has had the best scoring chances (5.5 xG with 7 goals). In terms of chance creation, Chawinga’s and Grosso’s assist tally of 5 is not reflected in their underlying Expected Assist (xA) numbers, which see Cernoia as the best creator for her teammates. Stefanie van der Gragt has the highest aerial duel win rate, while Martina Piemonte stands out among forwards. Finally, we outlined a simple comparison of some basic stats between men’s and women’s Serie A. While a full comparison between the leagues would require a more in-depth analysis taking into account several possible biases, we can see that women’s football tends to record more goals thanks to a higher shot volume and conversion rate, while at the same time it shows lower pass and cross completion rates and aerial duels volume, and an almost identical number of total fouls.