[USER (data scientist)]: That's perfect! Now I'd like to add each player's performance data for each round to the list we made earlier. Please generate and display a list containing performance data, including matches played, won, and win rate for each top 10 ranked player in specific rounds of grass surface matches in the ATP tennis dataset.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd
import numpy as np
import pickle
from decision_company import read_csv_file,

# please import the necessary private functions from decision_company first

atp_tennis = read_csv_file('atp_tennis.csv')

# YOUR SOLUTION BEGIN:
<code1>
[COMPLETE YOUR CODE] 
</code1>
# YOUR SOLUTION END

print(performance_data_list)

# save data
pickle.dump(performance_data_list,open("./pred_result/performance_data_list.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: You got it! You can add the performance data to your list with a dictionary like this:
'''
import pandas as pd
import numpy as np
import pickle
from decision_company import read_csv_file,

# please import the necessary private functions from decision_company first

atp_tennis = read_csv_file('atp_tennis.csv')

# YOUR SOLUTION BEGIN:
