[USER (data scientist)]: Awesome! Now, let's figure out the original and updated match favorites based on the odds. And let's say the player with lower odds is more likely to win. Please generate and display a DataFrame that includes the identification of original and updated match favorites based on odds for later round 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

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

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

print(later_rounds_odds)

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

---END CODE TEMPLATE---

[YOU (AI assistant)]: Got it! Here's the code to calculate the original and updated match favorites: 
'''
import pandas as pd
import numpy as np
import pickle

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

# YOUR SOLUTION BEGIN:
