Exploring SHIBUYA CITY FC's performance through data!: Utilizing Data in Sports part 4
For the fourth installment of our series on data utilization in sports, we will conduct a roundtable discussion with the players and staff of SHIBUYA CITY FC, for whom we serve as the official partner.
We will compare tracking data from the 2023 and 2024 seasons to uncover the reasons behind this season's strong performance.
Today's Attendees.
Genki Daido - Sales Developer @Morph
Sales Developer for Morph, responsible for the sports sector in data utilization.
Shunsuke Iwanuma - Soccer Player @SHIBUYA CITY FC
Player for SHIBUYA CITY FC.
Naohide Hatama - Content Director @SHIBUYA CITY FC
Content Director for SHIBUYA CITY FC, creating various content to attract fans.
Visualizing Insights Through Data
Daido:
First of all, congratulations on qualifying for the National Amateur Soccer Championship!
I've attended several of your matches since this spring and felt that the new players are gradually fitting in. I feel that the number of goals conceded is about the same as last year, while the number of goals scored has increased. Let's start by using data to validate these observations.
On the left is the average number of goals conceded per match, and on the right is the average number of goals scored per match.
Daido:
Although we originally had a low number of goals conceded, this year it's even lower at an average of 0.5 goals per match. However, goals scored has increased by more than 1.5 times to an average of 3.625 goals per match.
Hatama:
Amazing. Indeed, I had the feeling that the number of goals scored has increased compared to last year, but I hadn't compared the data side by side. Seeing the data now, the numbers are astonishing.
The Reasons Behind SHIBUYA CITY FC's Strong Performance
Daido:
The impact of this season's strength is clear from the data. I'd like to ask you, Iwanuma, from a player's perspective, what do you think are the reasons behind this strength and good performance?
Iwanuma:
I think one key factor is the transition between offense and defense, which all the players are more conscious of compared to last year. For SHIBUYA CITY FC, we often face opponents who drop back to defend. When we lose the ball and immediately win it back, our opponents are trying to move forward, which disrupts their formation. This allows us to start our attacks closer to the opponent's goal, increasing our scoring opportunities.
Daido:
I see, so defense for the sake of offense and starting attacks closer to the opponent's goal are key factors in your good performance. Now, let's compare the indicators that might reflect this transition, the number of sprints and sprint distance, between last year and this year.
Hatama:
It's clearly increased! This is fascinating...
Daido:
Yes, the number of sprints has increased by about 7, and the sprint distance by about 200 meters. The data shows that the team's focus is reflected in the numbers and results. Next, let's look at the sprint numbers and sprint distances for individual players.
Positional Changes Reflected in Data
Daido:
Forward Masamori leads in both indicators, with his numbers more than doubling. Iwanuma, from your perspective as a center back, do you feel that Masamori's sprint numbers and distances have increased compared to last year?
Iwanuma:
Yes, I do feel that there have been more breakthroughs behind the defense during attacks. Also, when transitioning from attack to defense, we apply pressure starting from the forwards, which also contributes to the increased numbers. By having the forwards press from the front, we can start our attacks closer to the opponent's goal and prevent them from making good passes even if we don't win the ball, leading to increased scoring opportunities and fewer goals conceded.
Hatama:
In recent matches, the pressing has been impressive. We saw you defending close to our goal after losing the ball.
I’m curious about the changes for Tsuchida, considering his position change from a defensive midfielder to a side back this year.
Daido:
Tsuchida's numbers have increased by 1.5 times in both indicators. Honda and Uematsu, who have continued as defensive midfielders, haven't shown much change in their numbers, but they cover the most distance in total.
From this, we can infer that defensive midfielders are expected to cover the entire pitch both defensively and offensively, while Tsuchida, who transitioned to a side back, has been given a different role.
Generating Individual Performance Reports with AI
Daido:
So far, we've analyzed the tracking data. Now, let's use Morph's reporting feature to create individual tracking data reports for players. This time, we asked AI to generate a comparative report on Iwanuma's 2023 and 2024 tracking data (sprint numbers, sprint distance, impact count, top speed, and distance covered per minute), including advice based on the data.
Daido:
The report shows overall performance improvement.
Hatama:
Still improving at 36 years old? Nice!
Iwanuma:
We've been focusing a lot on sprint training this year, so that might be showing results.
I've actually wanted something like this. Currently, we get Catapult data for each match, but it's sent on a match-by-match basis, so we can't compare it...
Daido:
As a player, the data you want to see is a comparison with your past performance, right?
Do you think such reports would be useful for the staff as well?
Hatama:
Yes, as team staff, knowing the current condition of our players is valuable information. Even if we don't share all of it with the players, it's very important for team development.
Adding Player Age as Additional Information
Daido:
Indeed, there are many ways to use this. For example, creating reports comparing tracking data from past matches can be useful for coaches.
Also, we currently publish match summaries on the official site. It might be interesting to have AI write a data-based report alongside the human-written one.
Additionally, Morph's reports can be customized with additional information. Let's generate a new report with the added information that Iwanuma is 36 years old.
Hatama:
Wow, it's properly suggesting training adjustments to reduce load and prevent injuries considering the age!
Daido:
It's very capable in that regard. By providing more information, it can create more accurate reports. Even with general use of ChatGPT, it's often used for brainstorming rather than producing ready-to-use content in one go. Viewing it with that mindset, it can be very useful.
We aim to continue these new initiatives, so please stay tuned!
I'll be at the home game this weekend! Good luck!
Iwanuma:
Thank you. I'll do my best!
Hatama:
Thank you!
