Editor’s note: This will begin our annual season in review. Over the next week, we will be dishing out or position by position ratings as well as looking back at the job done by Juventus’ manager. So, please, keep a look on both the website as well as the podcast for what we have in store as we look back on a tumultuous 2022-23 season.
Without question, the major talking points about the 2022-23 season are those that happened off the field, but I won’t be covering those in this season review. I am going to present the season’s on-field team and player performance statistics.
(All data unless otherwise indicated were from fbref.)
Juventus ended the season with a record of 22 wins, six draws, and 10 losses, and 56 goals scored and 33 goals against (72 points before the penalty), which was very similar to last season’s 20 wins, 10 draws, and eight losses, and 57 goals scored and 37 goals against (70 points), and did not represent an improvement.
According to WhoScored, the highest-rated formation this season was a 3-5-1-1 (see Figure 1 below), which had a 6.8 rating. The players included are those deemed the best performing player for each position. (WhoScored creates a player rating using their comprehensive statistical algorithm.)
Note that the players included in the figure were the best performing player at that position according to WhoScored and are not necessary the players that were used in all the games.
The second-highest rated formation was a 3-5-2 (see Figure 2 below) with a 6.7 rating, which was just a tenth of a point below the 3-5-1-1.
In total, Juventus used nine different formations across the 38 games in Serie A in the 2022-23 season, with the above two being the most used, followed by a 4-3-3 that was used in six games (which had a 6.5 rating, 1-4-1 W-L-D record). This lack of consistency is similar to last season when Juventus used eight different formations (the most being 19 games in 4-4-2, 8 games in 4-3-3, and 5 games in 4-2-3-1). For comparison, in this Serie A season, Napoli was much more consistent, playing in 4-3-3 in 34 of the 38 games. Last year, one could perhaps understand Max Allegri not being so consistent since it was his first year back, but now in his second year it seems a little less excusable (although he did have some different players to work with).
Comparison Across Serie A Teams
Key Performance Indicators: The number of shots and shots on target are several key performance indicators for Serie A teams to make it into the top 3 of the league. When comparing these metrics (plus goals) across the top 4 Serie A teams this season and Juventus (although technically in the top 4), Juventus is pretty comparable to Milan, whereas Napoli and Inter are higher in both shots and shots on target (see Figure 3 below). Lazio are in their own world, defying the performance indicators with their relatively lower metrics and getting second place regardless. However, Lazio was just more efficient with their shooting having the highest percentage of shots on target by shots attempted (37.4%) and goals per shot ratio (0.12) followed by Napoli (35%, 0.11). Below them Milan (32.6%, 0.10), Juventus (32.3; 0,10) and Inter (31.5%, 0.10) were very similar in their shot efficiency.
Style of Play: According to the Opta Analyst metrics of how quickly the ball is progressed upfield [direct speed (meters/second)] and the average number of passes per sequence [passes per sequence], Juventus’ team sequence style of play this season had an average speed-wise and was slightly above average for passes per sequence (see Figure 4 below). Compared to the top 4 Serie A team this season, Juventus tended to have less passes per sequence (with the exception of Milan), and progressed the ball upfield just slightly faster than Inter and Milan and a bit faster than Lazio and Napoli. Compared to the 2021-22 season, Juventus decreased its passes per sequence and sped up its progression upfield (but only marginally).
It will likely not be surprising that no Juventus player made the Best XI in Serie A, according to OPTA data.
The team at Opta Analyst used a variety of metrics to base their decisions for the best players in a 4-3-3 formation. I wanted to examine how Juventus players matched up to the Opta best and below are the comparisons. (Note: I only looked at players that played in at least 18 matches and that in some cases I could not find the metrics that they used, so in those instances I used comparable ones I could find on fbref.)
Note the distinction between absolute numbers of a metric and its per90: Per90 is the total number for a metric divided by the 90s played (which is the total number of minutes played by a player divided by 90). So it gives you a sort of average for the metric per game. For instance, below is an example for touches on the ball in Serie A this season for Danilo, who played 35.4 90s:
- Matches played: 37
- Minutes played: 3184
- 90s: 3184/90 = 35.4
- Touches: 2597
- Touches per90: 2597/35.4 = 73.3
Opta selected Lazio’s Ivan Provedel as their best goalkeeper. He played 38 games and had 21 clean sheets (55.2%), saving 77% of shots on target (99/128). They also reported that he prevented 3.6 goals based on their expected goals on target (xGOT). I couldn’t find that specific metric, so instead I used the ‘post-shot expected goals – goals allowed’ on fbref to get a post-shot expected goal prevented, which was 2.4 for Provedel. Here is how Wojciech and Mattia Perin compare (see Figure 5 below):
Szczęsny had less clean sheets than Provedel, and his saves percentage (67/93=75.3%) and prevented goals (0) were also lower. Granted Perin played way less games, but his numbers were overall better than both Provedel and Szczęsny, with an 85% save percentage (32/40) and 4.2 prevented goals. However, it is impossible to say that if Perin had played all the 38 games as Provedel did that he would have been consistently better.
Left back / Right back
Opta selected Carlos Augusto (Monza) and Giovanni Di Lorenzo (Napoli) for the left and right backs, respectively. Augusto had the most goal involvements with six goals and five assists (11 involvements), while Di Lorenzo had three goals and four assists (seven involvements). Di Lorenzo also had 256 progressive passes (7.07 per90) and 47 key passes (1.3 per90).
Since Opta selected their best XI in a 4-3-3 formation, it is a bit uncomparable to Juventus’ formation that typically had back three and five midfielders. But I went ahead and compared Filip Kostić and Juan Cuadrado’s metrics to Augusto and Di Lorenzo (see Figure 6 below). Kostić matched Augusto with his goal involvements and had more key passes than Di Lorenzo (both in total and per90), but fell short of Di Lorenzo’s progressive passes. Cuadrado had lower metrics than both, but completed 84.1% (1113/1323) of his attempted passes which almost exactly matched Di Lorenzo’s 84.6%.
Opta selected Kim Min-jae (Napoli) and Chris Smalling (Roma) for the best center backs. Kim had 3142 touches (92.7 per90), 2552 completed passes (90.8% successfully completed passes), won 63% of aerial duels, and only lost four challenges (number of unsuccessful attempts to challenge a dribbling player). Smalling won 74.4% of aerial duels and only lost eight challenges.
For Juventus center backs, Danilo and Gleison Bremer played the most minutes (3,184 and 2,633, respectively), but I also included Alex Sandro and Federico Gatti for comparison (see Figure 7 below). Danilo far and away had the most touches for Juventus center backs, but did not surpass Kim, and his successful aerial duels were also lower (58.2% out of 91 total). Bremer was closer for aerial duels with 61.2% won (and he was also the only Juventus center back that had over 100 aerial duels with 129 in total). Bremer was very comparable with Kim with 90.1% completed passes, and was also successful in 73.1% of his tackles. Given these statistics, I would say Bremer should be considered one of the top defenders in Serie A this season.
Opta selected Sergej Milinkovic-Savic (Lazio), Stanislav Lobotka (Napoli), and Nicolò Barella (Inter) as the best midfielders in Serie A in the 2022-23 season. These players were heavily involved in attacking sequences and completing and receiving passes. I couldn’t find most of the metrics they report in their article on fbref so I used several other metrics that closely represent these factors. For example, they reported the total attacking sequence involvements for Milinkovic-Savic (146), which I converted into looking at number of shots and shot-creating and goal-creating actions (which for Milinkovic-Savic was 64 shots, 79 shot-creating and 12 goal-creating actions, totaling 155).
The Juventus midfielders I examined were Adrien Rabiot, Manuel Locatelli, Nicolò Fagioli, Fabio Miretti, and Leandro Paredes. They definitely varied in their minutes played, from Rabiot’s 2748 down to Paredes’ 977, so some of the difference are based on that (see Figure 8 below). Also note: the per90 stats seem to get a bit unrepresentative when players don’t play many minutes, so I assume that might be why Paredes’ per90 metrics were almost all higher than the other midfielders (or maybe he was just really the best midfielder!).
The only Juventus midfielder that comes close to the numbers the Opta best had selected was, unsurprisingly, Rabiot. His involvement in shots and goals totaled 148 (compared to Milinkovic-Savic’s 155) and he completed 81.5% of his passes compared to Barella’s 81.6% (although Lobotka beat all of them out with 94% completed passes!).
For forwards, unsurprisingly Opta selected two Napoli players: Victor Osimhen and Khvicha Kvaratskhelia. Osimhen was Serie A capocannoniere (with 26 goals, four assists, and 52/132=39.4% shots on target) and Kvaratskhelia was Serie A player of the year (with 12 goals, 10 assists and 30/83=36.1% shots on target). Osimhen had 789 touches (27.7 per90) with 232 of them in the opponent’s penalty area, and Kvaratskhelia had 1548 touches (55.3 per90) and 175 in the opponent’s penalty area. For the third forward, they selected Inter’s Lautaro Martínez who had 21 goals, 6 assists, 40.8% shots on target (31/125), and 1085 touches (37.9 per90).
For Juventus, I looked at Dušan Vlahović, Arkadiusz Milik, Ángel Di María, Moise Kean, and Federico Chiesa. When looking at the numbers (see Figure 9 below), you should account for the fact that positionally Di María and Chiesa played a greater variety of positions. Di María had the most touches for Juventus forwards and more so that Osimhen but not Martínez or Kvaratskhelia; however, Di María’s touches per90 was the highest of all these players (56.4) and his shot-creating actions was quite high, too.
For the three truer forwards, Milik had the best shot on target rate (51.2%), which was also better than the Opta’s selected three. He also had the most touches, but Vlahović had more touches in the opposition penalty box. It is really too bad Kean was injured and didn’t get more minutes, as he scored the most goals per minute played. Overall, I think the Opta’s best three forwards outperformed Juventus’ and Juventus was forwards were not really in contention to be the best in Serie A in the 2022-23 season. Let’s hope that changes next season!