[USER (data scientist)]: Finally, I'd like to loop through all the matches and update the odds for each one. Can you help me with that? Please calculate the head-to-head win rates for players in the ATP tennis dataset and use these rates, along with individual performance metrics, to update the odds for matches involving a specific player. Then, generate and display a DataFrame containing the original and updated odds for these matches.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd
import numpy as np
import pickle

atp_tennis = pd.read_csv('atp_tennis.csv')

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

print(updated_odds_df)

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: You got it! Here's some code that loops through the matches, updates the odds, and stores the results in a DataFrame: 
'''
import pandas as pd
import numpy as np
import pickle

atp_tennis = pd.read_csv('atp_tennis.csv')

# YOUR SOLUTION BEGIN:
