It’s probably not good for the athletes.

On a 95 degree afternoon in the Round of 64, Jack Sock and Augie Ge were required to essentially play a play-in game against local Arizona favorite Kyle Koszuta and Elliott Schupp. Sock/Ge controlled game one.

That’s where Jack Sock hit the wall. Read more here on a Facebook post from The Kitchen.

Apparently suffering from an illness or heat exhaustion or dehydration, Sock was essentially immobilized. He took a medical timeout. He took timeouts when one team hit five points because he knew he was getting another timeout at the six point end switch. We walked a turtle-like speed to towel off between points. He was treated with incredible grace by the referee, who gave him more time than he likely deserved.

He was so exhausted he couldn’t stack with the left-handed Ge. So they played straight up.

Sock/Ge got hammered in game two. One wondered how he’d ever get through game three.

Sock had two things he could do.

1. If he was hit the ball, he could end the point quickly.

2. He could use his fast hands to hit counters.

Somehow his opponents failed to hit the majority of balls to him in game three … to me it looked like Kyle/Elliott were being courteous to Jack - they could have made him look very bad if they wanted to. I don’t think they wanted to win that way.

When they did hit the ball to Jack, he used his hand speed to end points. Quickly. Effectively … ultimately winning the third game.

I’m not sure why the PPA is playing outdoors in North Carolina and in Mesa in two weeks. I mean, there are players who played in the MLP final in New York on Sunday and are asked to play in mid-90s heat in North Carolina approximately forty-eight hours later.

The PPA/UPA is asking their biggest asset … their players … to put their bodies through an awful lot for … money, I guess.

The lesson for the reader is to use whatever tools you have at your disposal to do the best you can when conditions are not optimal.

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Every player contributed negatively on offense, positively on defense. It was hard to score in this match!

Look at defense and Max Freeman.

What did Max do well?

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Here’s summarized results.

A slightly different outcome than I expected.

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First: The quality of amateur players in Asia.

Second, the “Defensive Drive”. In my community there are a group of women who work on this several times a month. Watch what he does between 7:19 and 7:38.

Here’s another pointer about hitting the ball back to the same spot.

Collin Johns may not be as talented as his brother, but he sure has a nicely functioning CPU in his brain.

This time I evaluate Townsend/Ge vs. Kawamoto/Newman, a game won by Townsend/Ge 11-2. Did Danni-Elle control this match, partnered with Augie Ge?

She did well! Both Danni-Elle and Augie added a similar number of points. Notice that Danni-Elle added points on serves, thirds, fifths … Augie added points on returns of serve and fourth shots. It’s good to have a team that plays in a complementary manner!

Let’s look at some of the details of the game.

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Here are the high-level stats from their 11-4 win over Kawamoto/Blatt.

One player added points, the other three players were neutral or negative. That player? Danni-Elle Townsend.

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I measured rally length, categorized into 1-5 shot, 6-10 shot, 11-20 shot, 21-35 shot, and 36+ shots.

There weren’t huge differences by womens/mens/mixed format, but I’ll share what I learned regardless.

Women’s Match

• 29% 1-5 Shots.

• 34% 6-10 Shots.

• 20% 11-20 Shots.

• 17% 21-35 Shots.

• 0% 36+ Shots.

First of all, isn’t Danni-Elle Townsend a revelation? Spicy play, deception, heavy top spin, mixing up shot directions, looping balls, it’s all so much fun to watch! One would think she’s only going to get better.

63% of rallies ended in 1-10 shots. Not a lot of dinking. The game has changed so much in the past three years. The days of watching Lindsey Newman grind it out with dinks while defending/blocking are long gone. The days of defending from the baseline over and over and over again are alive and well.

Let’s go to the Men’s match.

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I decided to measure something different. I decided to measure what I call “Scramble Efficiency”. When is a player in “Scramble” mode?

• Hitting a 7th/9th/11th etc. shot from the back 2/3rd of the court.

• Defending an ATP.

• Running down a lob.

If a player hits the ball over the net and scores a point, or hits the ball over the net resulting in another shot, the player scrambled “efficiently”.

I also measured if the player’s team ultimately scores a point when the player “scrambles” (this is going to become important in a moment). If a player is in scramble mode three times in a point and his/her team wins the point, the player earns 3-for-3 credit (probably not the best definition but that’s where I am at right now).

This was a best-of-five match easily won by Ben Johns and Anna Leigh Waters over Christian Alshon and Rachel Rohrabacher in three games.

Which players were most efficient? If you guessed Ben Johns, you guessed correctly.

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Each column in the table below was simulated 1,000,000 times. The “your team” row represents your chance of winning any individual serving point. The “their team” row represents the chance the opponent has of winning any individual serving point.

If the two teams are equal, you will pickle the opponent 5,484 times out of 500,000 wins (just over 1%). Similarly, your opponent will pickle you 5,478 times out of 500,000 wins (just over 1%). Also fascinating … the most common score when two teams are equal is 11-9 … but this is even better, the median score is 11-6. If two teams are equal, just over half of the games will be 11-10 / 11-9 / 11-8 / 11-7 … just under half of the games will be 11-6 / 11-5 / 11-4 / 11-3 / 11-2 / 11-1 / 11-0. Let that fact sink in for a moment. The fact you lost a game 11-5 is not necessarily reflective of you being a lot worse than your opponent.

In pickleball, small advantages lead to big increases in the probability of winning a match.

• If your scoring advantage when serving is 46% vs. 40%, you will win 67% of games.

• If your scoring advantage when serving is 49% vs. 37%, you will win 80% of games.

• If your scoring advantage when serving is 52% vs. 34%, you will win 90% of games.

Your probability of pickling the opponent increases as your probability of winning a game increases.

• 50/50 = 0.54% chance of a pickle.

• 67/33 = 1.16% chance of a pickle.

• 80/20 = 2.24% chance of a pickle.

• 90/10 = 4.16% chance of a pickle.

Believe it or not, if you aren’t supposed to win, you can still pickle your opponent.

• 33/67 = 0.24% chance of a pickle.

• 20/80 = 0.09% chance of a pickle.

• 10/90 = 0.04% chance of a pickle.

Yes, if you only have a 10% chance of beating an opponent, you can expect to pickle that opponent 355 times of of 1,000,000.

1. 90 of 1,000,000 games.

2. 270 of 1,000,000 games.

3. 1,115 of 1,000,000 games.

4. 3,483 of 1,000,000 games.

If you answered one (1) … 90 out of 1,000,000 games, you are correct!

I simulated one million games across different serving/win probabilities. The table below shows the results.

The column at the far right shows how often you win the game 11-0 via a Golden Pickle. If you only score a point 28% of the time (like what happens when some pros have to play against Anna Leigh Waters) you can expect 2 Golden Pickles. If you score a point 63% of the time when serving (like what happens to Anna Leigh Waters early in tournaments), you can expect a whopping 6,191 Golden Pickles out of a million games … 0.6% of the time.

The rest of us? If we’re playing competitive rec games against players of similar skill levels, we’ll earn a Golden Pickle 90 times out of 1,000,000.

By the way … starting the game with at least a 2-0 lead is difficult! Under normal circumstances (43% chance of winning a point while serving) you can expect to jump out to at least a 2-0 lead 18.5% of the time.

Now it’s time for your comedy break for the day.

Is the math different for pro players?

I charted four mixed matches in MLP NYC last weekend … Dallas vs. Brooklyn and SoCal vs. Palm Beach. I measured whether the serving team scored a point, segmented by whether the opposition played straight-up or chose to unwind the stack.

The results did not align with my pre-conceived hypothesis.

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I charted a 3.5 Mens 60+ Gold Medal match at the US Open, I charted a group of 4.0 league/tournament men in their 50s/60s. In both cases, 89% of third shots resulted in the opposition hitting a fourth shot. In other words, balls hit the net, went out the side out of bounds or out the back out of bounds just 11% of the time.

If there is a theme I’m trying to communicate this summer, it is this.

• Balls must stay in play.

When I chart transition zone outcomes, about 75% of transition zone shots are “in” for 4.0ish players, about 95% are “in” for professional players … and if you watch Anna Leigh and Anna Bright, they don’t hit perfect transition zone balls. Their shots are frequently “live to fight another day” shots at head/shoulder level.

I kept track of my third shots today … across 7 games I attempted 70 third shots and hit three into the net (96% were “in”). Before charting this topic, I was generally in the 80% - 85% range (not good enough).

Keep balls in play!

By my count (and I may have counted incorrectly or missed shots as the gate opened/closed or the video missed shots), the four players attempted 86 third shots.

What percentage of the 86 third shots were “in”, resulting in a 4th shot attempt by the opposition?

I’ll post the results in three days … vote your answer now!

The metrics from the match are bonkers.

Blue Team either scored or got to the kitchen a whopping 91% of the time.

White Team either scored or got to the kitchen a whopping 85% of the time!

That’s crazy!

When Blue Team Woman served, her team scored 68% of the time.

The Blue Team attempted 34 third shots … Blue Team Guy attempted 31 of the 34 thirds! He also attempted 18 of the 25 fifth shots. But if Blue Team Woman hit the fifth, her team scored 6 out of 7 times, dissuading people from hitting the ball to her. She had a nasty inside-out shot that really flummoxed her opposition.

Blue Team Guy hit 3rd Shot Drips (faster drops with top spin) nearly exclusively, forehand or backhand. He rolled his fifths as well, mostly going to the backhand of the woman across the court from him. Seriously, watch the match, and watch how he hits the ball. It’s a different playing style than what you usually see. Pair his style with his partner’s inside-outs, and woo-boy do you have trouble!

Shot combination statistics:

When the Blue Team Woman served and the Blue Team Guy hit the third, their team scored a whopping 63% of the time (12 for 19). When White Team Guy served and hit the third, his team only scored 27% of the time (3 for 11).

Here are the defensive statistics.

It’s fascinating how dominant the Blue Team Woman was on defense … the opposition only scored 36% of the time when she returned the serve … her partner was at 50%.

Meanwhile, when the White Team Woman returned the serve, the Blue Team scored 76% of the time (13 for 17). Honestly, we should be out there practicing serves and returns of serve until the cows come home, both are that important to the setup of a point.

Finally, we have kitchen points and “points added”.

When I watched the match, I was dazzled by what the Blue Team Guy was doing.

When I look at the stats, I should have been dazzled by what the Blue Team Woman was doing!! She was the better player of the two on serves, returns, and fifth shots. The guy completely controlled the match with his third shot drips.

Both Blue Team players had an ample amount of deception as part of their games. Yes, they made mistakes … certainly not at the level I make them.

I’ve been preaching drips in recent practice sessions. It was gratifying to see an excellent player execute them so well. It was also fabulous to see a woman expertly employ inside-outs and assorted wizardry in her play.

Here’s video of the match, won by the team in green/white shirts by a score of 11-9 / 11-2.

I charted rally length, getting to the kitchen, and whether the serving team scored a point or not.

Ready for something interesting?

Green and White Shirts (Winners): 15 of their 22 points were scored on rallies that lasted 1-5 shots. They scored on 60% of their short rallies. The guy was bangin’! 25 of their 38 rallies lasted just 1-5 shots (66%).

Black and White Shirts: 5 of their 11 points were scored on rallies that lasted 1-5 shots. They scored on just 30% of their rallies. 21 of their 30 rallies lasted just 1-5 shots (70%). This team played better on extended rallies … scoring 6 times out of 9 (67%) on 6-20 shot rallies (their opposition scored 7 times out of 13 … 54% … on rallies of 6-20 shots).

The game was won on shots 1-5 … Green/White scored on 60% of short rallies while serving, Black/White scored on 24% of short rallies while serving. Green/White scored ten more points here in a match they won by a combined 22-11 score. This was the difference.

Why share this information?

Most of you reading this are not at a 4.5 level and are not competing for medals in the US Open. Given this reality, where should your focus be?

• Serves

• Returns of Serve

• Third Shot / Fifth Shot Combinations

• Fourth Shot / Sixth Shot Placement

• Transition Zone Effectiveness

Only 30% of the points in this match ever got to the kitchen.

If you have a group you practice / drill with, focus on Serve, Returns of Serve, Third Shot / Fifth Shot Combinations, Fourth Shot / Sixth Shot Placement, and Transition Zone Effectiveness. That’s where the majority of your points are decided.

I counted how many shots comprised each rally, as well as whether the serving team won the rally.

We’d expect Parenteau / Kawamoto to have a high scoring rate.

• Parenteau / Kawamoto: 22 points on 34 serves, 65% scoring rate.

• Truong / Dizon: 7 points on 20 serves, 35% scoring rate.

The average scoring rate is typically between 42% and 44%, so Parenteau / Kawamoto were highly successful on their serves!

Let’s look at the average rally length of each team when they served, and the average rally length of each team when they won a point.

• Parenteau / Kawamoto: 16.2 rally length, 16.9 rally length when they won the point.

• Truong / Dizon: 13.2 rally length, 11.0 rally length when they won the point.

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The team in the white uniforms lost the match 11-6 / 13-11.

Each team did something good in this match.

The Winning Team got to the kitchen after their third shots. They only hit 32 balls while in the Transition Zone.

The team that lost struggled on their third shots. This meant they had to be fabulous at constantly getting Transition Zone shots over the net. Were they fabulous at this skill?

Yes! Yes they were. Here are the outcomes of Transition Zone shots for each team.

The White Shirt Team only hit five (5) errors out of 101 attempts in the Transition Zone. Let me repeat the last part of that sentence … they hit 101 balls while in the Transition Zone in the 40 minute match, three times as many as the Winning Team. They only made mistakes 5% of the time. That’s stupid good!

They also lost. Watch their third shots and then their progress to the kitchen vs. the team that won the match. The team that won the match effortlessly got to the kitchen, so they generally didn’t have to deal with making mistakes in the transition zone.

There are many ways to win pickleball games. Here we saw two approaches that netted the teams Gold / Silver medals in the US Open last month. If your thirds aren’t great, practice your Transition Zone skills to make up for a deficiency elsewhere.

You can watch the match here.

There was a stark difference in effectiveness of returns of serve between Anna Leigh and Kate Fahey. Opponents only scored on 31% of Anna Leigh’s return of serve … opponents scored on 72% of Kate Fahey’s return of serve.

I decided to chart the landing point of each return of serve from Kate Fahey and Anna Leigh Waters. Here is the chart for Kate Fahey.

What do you observe?

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