How We Rate Every Pro Pickleball Player
Our Sheet Rating™ system, explained — built from 7,500+ PPA matches
7,500+PPA Matches
665+Rated Players
3Formats Tracked
What is Sheet Rating™?
SR™ is a mathematical rating system originally developed for chess by Arpad Elo in the 1960s. The core idea is simple: your rating goes up when you beat someone, down when you lose, and the amount it moves depends on who you beat or lost to.
Beat a higher-rated player? Big gain. Lose to someone ranked way below you? Big drop. It's a self-correcting system that, over time, converges on a player's true skill level. We apply this same logic to professional pickleball.
Our Data
Every rating on The Dink Sheet is built from actual PPA Tour match results — not opinion polls, not vibes, not social media followings. We've processed 7,500+ matches across every PPA event, covering 665+ players in three distinct formats:
- Singles — 1v1 matchups
- Doubles — Same-gender pairs
- Mixed Doubles — Male/female partnerships
Data is updated after every tournament. When the last point is played, we crunch the numbers.
How We Calculate
Every player starts at a baseline rating of 1500. From there, the math takes over:
Expected Outcome
Before every match, we calculate the probability each player wins based on the rating gap between them:
E = 1 / (1 + 10^((R_opponent - R_player) / 400))
A 200-point gap means the higher-rated player is expected to win ~76% of the time. A 400-point gap? ~91%.
Rating Update
After the match, we compare what actually happened to what we expected:
R_new = R_old + K × (Actual - Expected)
The K-factor controls how much ratings swing per match. We use adaptive K-factors — newer players with fewer matches have higher K-values (ratings move faster while the system is still calibrating), while established players have lower K-values (more stable ratings).
Margin of Victory
Not all wins are created equal. A dominant 11-2, 11-3 sweep tells us more than a tight 13-11, 9-11, 11-9 battle. We factor in score margin to weight rating changes — bigger wins move the needle more.
Format-Specific Ratings
A player who dominates singles might be average in mixed doubles. Different formats require different skills — court coverage, partnership chemistry, net play, power vs finesse. That's why we track three separate ratings for every player.
Ben Johns has a different singles rating than his doubles rating. Anna Leigh Waters' mixed doubles number stands on its own. This gives you a much more accurate picture than a single blended number ever could.
You can explore all of them on our Sheet Ratings™ page.
What Makes Ours Different
- Match-based, not opinion-based. Every rating comes from actual PPA results. No voter bias, no popularity contests.
- Updated after every tournament. Not monthly. Not quarterly. After every event.
- Head-to-head records included. Compare any two players to see their full H2H history alongside Sheet Rating™ gaps.
- Upset detection built in. When a lower-rated player beats someone 100+ SR™ points above them, we flag it. These upsets are the storylines that matter.
- Powers our predictions. Our AI-generated brackets and match predictions all run off these ratings.
Current Top 10 — Singles
Live ratings as of the most recent PPA event:
🏆 Men's Singles
- Hunter Johnson 1880
- Christopher Haworth 1850
- Federico Staksrud 1815
- Roscoe Bellamy 1812
- Christian Alshon 1797
- Connor Garnett 1750
- Jack Sock 1750
- Jaume Martinez Vich 1737
- Gabriel Joseph 1735
- John Lucian Goins 1729
🏆 Women's Singles
- Anna Leigh Waters 2028
- Kate Fahey 1867
- Parris Todd 1823
- Kaitlyn Christian 1773
- Brooke Buckner 1752
- Lea Jansen 1742
- Catherine Parenteau 1725
- Judit Castillo 1675
- Jorja Johnson 1664
- Mary Brascia 1618
Minimum 5 singles matches. See full rankings on the Sheet Rating™ page.
How We Use It
- Match Predictions. Before every PPA event, we generate win probabilities for every matchup based on Sheet Rating™ gaps. Check our latest tournament predictions.
- Upset Detection. A 100+ Sheet Rating™ gap between opponents signals a meaningful mismatch. When the underdog wins, that's a real upset — not just a seed number.
- AI Brackets. Our predicted brackets use Sheet Ratings™ to simulate entire tournament draws from round 1 to the final.
- Sharp Sheet Analytics. Our analytical tools use Sheet Rating™ as a foundation for deeper performance metrics.
Limitations
No model is perfect. Here's what ours doesn't do (yet):
- Cold start problem. New players enter at 1500 regardless of skill. It takes 10-15 matches for ratings to calibrate. A top amateur entering their first PPA event will be temporarily underrated.
- Injuries and form. Sheet Rating™ doesn't know if a player is nursing a shoulder injury or just came off a 3-month break. It only sees results.
- Partnership changes. In doubles and mixed, new partnerships need time to gel. A player's rating might dip when switching partners, even if their individual skill hasn't changed.
- PPA-only (for now). We currently process PPA Tour matches only. APP Tour and MLP match data aren't included yet — but they're on the roadmap.
