Table of Contents
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Team statistics
| Milan |
Juventus |
|---|---|
| Cartons | |
| a player | Ax |
|---|---|
| 0 player |
Juventus player statistics
| a player | Ax |
|---|---|
| 0 player |
About FBref.com
FBref.com launched (June 13, 2018) with coverage of domestic competitions for England, France, Germany, Italy, Spain and the United States. Since then, we have continued to expand our statistics to include national competitions from over 40 countries, as well as national cups, super cups and youth competitions from major European countries. We have also added data for major international cups such as UEFA Champions League and the Copa Libertadores.
FBref is the most comprehensive source of women’s soccer data on the Internet. This includes the complete history of the FIFA Women’s World Cup plus recent domestic league seasons from nine countries, including advanced stats like xG for most of those nine.
In collaboration with choosewe include advanced analytical data such as xG, xA, advanced pass, duels and more for over twenty competitions. For more information on the expected goals model and which competitions have positive data, see our define xG.
Show additional information
Note that player records appear to be incomplete for their roles. Players may come from or move to leagues we do not currently cover. This issue will decrease over time, as we add new leagues and seasons. We will not have less data in the future than we have today.
You can sign up for get an email when new countries and new features are launched.
For more information, see our article blog about the releasegeneral page of leagues/competitions showing the leagues and seasons we include, or our About page. Contact us if there is a problem or for a suggestion.
FBref is one of seven sites Sports-Reference.com.
2024-11-24 03:51:00
#Milan #Juventus #Match #Report #Saturday #November #FBref.com
If you were designing a user interface for displaying this football statistic data, how would you utilize the tooltips effectively to enhance user understanding and engagement with the information?
This looks like a snippet of code from a website likely displaying football (soccer) statistics. Here’s a breakdown and some potential discussion questions:
**Understanding the Code**
* **HTML Structure:** This is primarily HTML code, the basic language of web pages.
* **Tables:** It defines an HTML table (`
| ` tags create column headings like “TC,” “CJ,” “CR,” etc. These likely represent football statistics (shots on target, yellow cards, red cards, etc.).
* **Data Cells:** The ` | ` tags would contain the actual player statistics. However, these are missing in your provided snippet.
* **Tooltips:** The `data-tip` attribute adds pop-up explanations when hovering over the headers, providing more context about each statistic. **Potential Discussion Questions** Since we lack the actual player data, these questions are more general but can spark a conversation about football statistics: * **Importance of Statistics:** * How important do you think statistics are in understanding and analyzing a football match? * Are there statistics that are more useful than others for judging a player’s performance? * **Interpretation of Data:** * Looking at these column headers, which statistics do you think are most important for a striker (offensive player)? For a defender (defensive player)? * How can statistics be misleading or misinterpreted? What other factors should be considered when evaluating a player? * **Advanced Statistics:** * The code mentions ”advanced analytical data” like xG (expected goals). What are the advantages and limitations of using these more complex metrics? * **Data Bias:** * Do you think that focusing too much on statistics can bias our perception of a player or a match? * Could there be systematic biases in how data is collected or reported that might affect our interpretation? **Interview Structure (if Applicable)** If you were conducting an interview with someone about this data (e.g., a football analyst), you could structure the conversation like this: 1. **Introduction:** Start with general questions about their role and experience with football data. 2. **Data Literacy:** Discuss the importance of understanding statistics and the potential challenges in interpreting them. 3. **Specific Statistics:** Dive into specific columns like “TC” (shots on target) or “xG” (expected goals), exploring their significance and limitations. 4. **Beyond the Numbers:** Encourage them to talk about the human element of football, how statistics may not always capture the full picture of a player’s performance or a team’s dynamics. 5. **Future of Football Data:** Discuss emerging trends in data analytics and how technology might shape the way we understand and experience football in the future. |
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