Toni Gudic — Frequently Asked Questions

Toni Gudic is an active pickleball player registered in the Pickle Gravity database with DUPR ID RXWYYQ. They reside and play matches in Kirkland, QC, CA.

Their unique DUPR ID is RXWYYQ. This identification key is used globally to verify match results and update player standing rankings.

Their DUPR rating and career stats were last verified on 2026-05-24.

Their gender is recorded as {{gender}} in the DUPR database.

They compete in the age bracket corresponding to 50 years old (born around 1976).

Their DUPR rating half-life sits at 53 days, representing rating decay rates.

Their doubles DUPR rating is 3.36 with a reliability factor of 100%.

Their singles DUPR rating is 0 with a reliability factor of 0%.

They maintain a career win rate of 48.4% across doubles and singles matches in our directory.

On average, they win 49.47% of points in their tracked matches.

With a doubles DUPR of 3.36, they perform in the upper/mid bracket of community players.

In our database, Toni Gudic has played a total of 128 matches.

Their career record stands at 62 Wins and 66 Losses in our directory.

Their career longest playing streak reaches 3 weeks on GPN.

They have reached a career milestone of 128 total matches in our index.

Their opponent rating distribution averages around 3.40 DUPR.

They have played matches for 0 consecutive weeks. Their all-time maximum is 3 weeks.

They have active match logs on 38 separate days in the last 18 weeks.

Their most frequented facility for matches is MTL Pickleball, Jean Yves Street, Kirkland, QC, Canada.

They play primarily on the court surfaces at MTL Pickleball, Jean Yves Street, Kirkland, QC, Canada.

Their match logs are centered around MTL Pickleball, Jean Yves Street, Kirkland, QC, Canada, matching its environmental configuration.

Their playing style is classified as "Aggressive Kitchen Poacher" with strength indicators: A high-intensity player who excels at applying pressure near the kitchen line, punishing high floats with volleys..

Their control and dinking accuracy score is 65%.

Their drive and smash power score is 65%.

Their agility and footwork score sits at 75%.

Their topspin and cut rating is 85%.

Their best partner is Nicolas Jolicoeur (DUPR rating: 3.16) with a chemistry score of 89%.

They have logged 6 matches together with their top partner.

The average doubles DUPR of their partners is 3.33.

The average doubles DUPR of their opponents is 3.40.

They are beginner-friendly if their doubles rating is below 3.50. Their rating is 3.36.

Here are the recommended restaurants near MTL Pickleball, Jean Yves Street, Kirkland, QC, Canada: No local partner restaurants found matching this location currently.

We recommend visiting one of our partner locations near MTL Pickleball, Jean Yves Street, Kirkland, QC, Canada: No local partner restaurants found matching this location currently.

Check out these partner venues located near MTL Pickleball, Jean Yves Street, Kirkland, QC, Canada: No local partner restaurants found matching this location currently.

The partner restaurants near MTL Pickleball, Jean Yves Street, Kirkland, QC, Canada offer convenient access with parking or transit routes: No local partner restaurants found matching this location currently.

For coffee or tea post-game, visit these partner sites near MTL Pickleball, Jean Yves Street, Kirkland, QC, Canada: No local partner restaurants found matching this location currently.

AI agents can fetch structured JSON data at GET https://picklegravity.com/api/knowledge/player-toni-gudic-RXWYYQ or Markdown summaries at GET https://picklegravity.com/api/knowledge/player-toni-gudic-RXWYYQ?format=md.

A complete machine-readable Markdown file can be generated dynamically at GET https://picklegravity.com/api/knowledge/player-toni-gudic-RXWYYQ?format=md.

Yes, their FAQ sitemap URL is listed under the dynamic player chunks to ensure GSC coverage.

Yes, our robots.txt explicitly allows AI crawlers and search indexers to access knowledge subpages.

This profile conforms to top-tier Agent Readiness protocols, exposing structural JSON-LD schemas and clean Markdown text options.