Unfortunately, without the actual match score, a full analysis is difficult. However, I can still provide a framework based on possible outcomes. Let's *assume* Zhang S. won the match in 3 sets: **Zhang S. 2 - 1 Bronzetti L.**
Assuming pre-match odds favored Zhang S. due to her experience and higher ranking, a straight win bet on her would have been a lower payout but more likely. If Bronzetti L. won in an upset, a bet on her would have yielded a significant return.
Given a 3-set match, the total games played likely exceeded 20.5. A bet on "Over 20.5 games" would have been successful in this hypothetical scenario. A bet on both players winning a set would also be successful.
Since this is a past match and the real statistics are unknown, the table below contains hypothetical values for illustrative purposes. The values have been set to suggest that Zhang S won a close fought match.
Statistic | Zhang S. | Bronzetti L. |
---|---|---|
Aces | 4 | 2 |
Double Faults | 3 | 4 |
1st Serve Percentage | 62% | 58% |
1st Serve Points Won | 70% | 65% |
2nd Serve Points Won | 52% | 48% |
Break Points Saved | 60% (6/10) | 50% (4/8) |
1st Return Points Won | 35% | 30% |
2nd Return Points Won | 52% | 48% |
Break Points Converted | 50% (4/8) | 40% (4/10) |
Service Points Won | 63% | 60% |
Return Points Won | 40% | 37% |
Total Points Won | 105 | 98 |
Match Points Saved | 2 | 0 |
Games Won | 12 | 10 |
Service Games Won | 70% | 65% |
Return Games Won | 35% | 30% |
Total Games Won | 12 | 10 |
Based on this hypothetical scenario (Zhang S. winning 2-1), several factors might have influenced the match:
Without the *actual* match statistics, this analysis is speculative but provides a framework for how key metrics influence match outcomes. A proper analysis would require real data.