We’ve studied 2,086 college men’s college matches (women’s case study here) from August 1, 2017, through 2019. Our objective was to answer some of these questions.
- What is the difference between match winners and losers?
- Which statistical categories are most important?
- What should a college coach or player focus on, to improve faster?
Below are the results.
The Stats We Measured
Here’s how we performed this study.
We took data from 2,086 matches and divided the data into two categories.
- Match Winner
- Match Loser
For each match, we collected 230 stats per player. Here are 16 examples.
- Number of 1st Serves In
- Total # of 1st Serves Hit
- 1st Serve %
- 1st Serves Won
- 1st Serves Won %
- # Double Faults – Net
- # Double Faults – Wide
- # Double Faults – Long
- Return Errors – Combined Courts
- Return Errors – Deuce – 1st Serve
- Points Won on Net Appearance
- S+1 FH Point Won
- S+1 FH Point Won %
- 1-4 Contribution %
- 1-4 Win %
- Return Errors – Deuce – 1st Serve – Forehand
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As you can see, we got very detailed.
We were able to find out, for example, “how many more forehand return errors does a match loser average from the deuce court when the opponent makes the first serve?”
Answer: 0.34 more errors
The best way to figure out what to do with all this data is to start with the high-level metrics, then drill down.
The Average Number of Points Per Match in College Tennis
On average, these matches had a total of 130.8 points.
- The match winner averages 71 points won.
- The match loser averages 59.8
So the difference between winning and losing, on average, is 11.2 points. That’s less than 1 point per game, not a huge difference.
Where does this 11 point difference come from?
The Difference Between the Winners & Losers
Next, we studied the high-level metrics to figure out where the match loser is falling short.
Here were the results.
Stat | Winner Average | Loser Average | Point Differential |
1st Serves In | 41.56 | 41.16 | 0.41 |
1st Serves Won | 29.07 | 25.18 | 3.89 |
2nd Serves Won | 12.43 | 10.70 | 1.74 |
# Double Faults | 2.77 | 3.36 | -0.58 |
# of Aces | 3.14 | 2.26 | 0.88 |
Return Errors – Combined Courts | 11.28 | 12.75 | -1.48 |
Return Winners – Combined Courts | 0.87 | 0.63 | 0.24 |
Return Made – Combined Courts | 49.74 | 46.69 | 3.05 |
Points Won at Net Appearance | 14.65 | 12.43 | 2.22 |
When we look at this data, the largest differentials are on:
- 1st serve points won
- Returns made
These three stats combine for 6.94 points. If the match loser can close the gap on these stats, the tables are turned.
When you give the match loser 6.94 extra points, you’re taking away those points from the winner. So the real difference is 13.88 points, more than our total difference of 11.
Below we’ll analyze each of these stats further, and how a coach or player can use this information to practice.
First Serve Points Won
It’s not surprising that 1st serve points won is one of our metrics.
From these 2,086 matches, the first serve percentage for both players was 63.3%, meaning most points started with a first serve in the court.
What we need to do is figure out why the match winner is winning nearly 4 more points on their first serve.
Stat | Winner Average | Loser Average | Point Differential |
1st Serves Won | 29.07 | 25.18 | 3.89 |
What can the match loser do to close this gap? Two things.
- Bring the 29.07 number down = improve returning 1st serves.
- Increase the 25.18 number = improve serving 1st serves.
Your first touch is key to determining the outcome of a match.
We know from our previous lessons that improving the first 4 shots and improving serve strategy is important.
This time we get to look at a larger data set for the serve +1 and return +1 data.
S+1 | Forehand | Backhand | FH – BH |
Match Winner Avg | 15.02 | 6.31 | 8.71 |
Match Loser Avg | 12.92 | 5.74 | 7.18 |
Differential | 2.1 | 0.57 | |
R+1 | Forehand | Backhand | FH – BH |
Match Winner Avg | 9.54 | 8.14 | 1.40 |
Match Loser Avg | 7.22 | 6.37 | 0.85 |
Differential | 2.32 | 1.77 |
S+1 = the server’s 2nd shot, or the 3rd shot of the point.
R+1 = the returner’s 2nd shot, or the 4th shot of the point.
Note: This data accounts for points with 3+ & 4+ shots. So double faults, aces, and return errors are not counted here. Our next stat, returns made, will help account for the return errors. We saw above that double faults have a -0.58 differential.
It’s clear from this table that most points that are 3+ shots are won when the player hits a forehand for their second touch. This is even more true for the serve +1 than the return +1.
A few takeaways from this data.
- Forehands have a larger differential than backhands for both S+1 and R+1.
- The match winner wins the “R+1 – point won” stat by a larger margin than they win the “S+1 – point won” stat. In other words, they create a larger margin on R+1 than they do on S+1.
This shows that college players should be practicing serve +1 forehand patterns, and return +1 forehand and backhand patterns in practice.
Practice more aggressive shots on serves and forehands when you can. Practice defensive shots with the backhand and returning 1st serves.
Again, keep in mind that these stats are interconnected. Improving the next stat on our list will help the previous stat as well.
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Total Returns Made
Next, we look at total returns made.
Stat | Winner Average | Loser Average | Point Differential |
Return Made – Combined Courts | 49.74 | 46.69 | 3.05 |
Match winners are making over 3 returns more per match than losers. Let’s see which areas of the court, and on which serves, making returns made matters most.
Stat | Winner Average | Loser Average | Point Differential |
Return Made – Deuce | 25.67 | 24.29 | 1.38 |
Return Made – Ad | 24.07 | 22.40 | 1.67 |
Return Made – Combined Courts – 1st Serve | 31.58 | 29.53 | 2.05 |
Return Made – Combined Courts – 2nd Serve | 18.16 | 17.15 | 1.01 |
We can see that returns made on first serves have over a 2x bigger point differential than returns made on 2nd serves. This makes sense with the 63% first-serve percentage.
More surprising, the ad court accounts for a larger differential than the deuce court. This is surprising because any game won at 40-15 would have 3 points served to the deuce court and only 2 to the ad. There is never a game won with more points to the ad court.
Note: There could be an exception to this if the matches are no-ad scoring. Many college matches are no-ad scoring, so this could be the difference.
As we drilled down further we found that:
- On first serves, there is a slightly larger differential in backhand returns made.
- On second serves, forehand returns make a bigger difference.
College players should practice improving their returns, we already know that.
But we can now prioritize returning 1st serves, especially to the backhand, and especially on the ad court. This is where match winners are separating themselves.
On second serves, college players should prioritize practicing forehand returns.
What We Could Add to this Case Study
Any statistical analysis of tennis is going to have some gaps. It’s important to recognize those gaps to have a full understanding of what the data means, so we can create actionable steps to apply to our practice time.
This data might change if we focused on matches with left-handed players. Because matches that include lefties are a minority of our data set, we simply don’t know if the data would change for these players.
Perhaps, at some point, we can target data for lefties.
That said, there are some relevant takeaways that college coaches and players should pay attention to.
If you see anything else we may have missed, comment below!
Key Takeaways: How to Win in College Tennis
Tennis is made up of matches, sets, games, and points. Win more points, and you’ll usually win the match.
With over 230 stats, it can be overwhelming to decide what’s important and what isn’t. Focusing on these point differentials is a way to find the most important metrics. By finding these stats, your college team can practice the right things that will lead to winning more points, games, sets, and matches.
We’re not saying to only focus on these things in practice, but they should be a priority based on the data we’ve collected.
- First serves are more important than second serves.
- Practice your S+1 and R+1 forehand patterns most.
- Making returns on first serves is more important than second serves.
- Practice your R+1 backhand pattern, playing defensive or neutralizing shots.
- Practice returning first serves with the backhand in the ad court.
- Practice returning second serves with the forehand.
Next month, we’ll analyze the women’s matches.
Want more stats & data? Sign up for our email newsletter for announcements on a brand new data analytics product coming soon. You will be able to access big data on 10,000’s of matches. It will have match data from juniors, college tennis, all the way to top ATP & WTA pros.
Jose says
Point differentials should be carefully analyzed, as they might show correlation rather than causation. While many aspects of the game are correlated (happen together with being a better player) with being a better player, not all of these actually cause the player to win more. A way of improving the analysis would be comparing matches of the same player, some where certain stats were high and some where they were low, and comparing the change in performance.
Warren Pretorius & Will Boucek says
Great points Jose! We can definitely do more with this data to drill down on what’s affecting the outcome most.