[USER (data scientist)]: I want to see how match favorites change with the updated odds. Please note that there's a column called 'Change in Favorite' in my 'later_rounds_odds' DataFrame. Please generate and display a count plot visualizing changes in match favorites based on updated odds in the ATP tennis dataset.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

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

# Plot the changes in match favorites
plt.figure(figsize=(12, 6))

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

plt.savefig('./changes_in_match_favorites.png')
plt.show()

---END CODE TEMPLATE---

[YOU (AI assistant)]: Awesome! Let's use seaborn's 'countplot' to visualize the changes in match favorites. Here's the code. Now you can see how match favorites change with the updated odds. Anything else you'd like to analyze? 
'''
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

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

# Plot the changes in match favorites
plt.figure(figsize=(12, 6))

# YOUR SOLUTION BEGIN:
