| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Mark DeSaulnier | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jeff Frese | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Angela Griffiths | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Joshua Hamilton | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Mitchell Maisler | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Katherine Piccinini | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Bob Rowland | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market tracks which candidates will emerge from the California 10th Congressional District primary to secure a spot in the general election. It is a critical indicator of voter sentiment and party strength in this specific district.
California utilizes a 'top-two' primary system where all candidates, regardless of party, appear on the same ballot. The two candidates who receive the most votes advance to the general election, regardless of whether they represent different parties or the same one. The 10th District has historically been a focal point for competitive House races.
Market participants aggregate information regarding campaign fundraising, candidate endorsements, and local polling to forecast which candidates are most likely to advance to the general ballot.
Because the two most popular candidates move forward regardless of party, it is possible for two members of the same party to face each other in the general election.
The market typically reflects the likelihood of a candidate remaining on the ballot and successfully advancing; candidate withdrawal usually impacts their perceived viability immediately.
The market resolves based on the official certification of the primary election results by the California Secretary of State.
Unless specifically listed as a primary option, the market focuses on established candidates qualified for the ballot; write-ins rarely secure enough votes to shift outcomes in CA-10.
The 10th District encompasses specific regions in California as defined by the most recent redistricting cycle, which can significantly alter the partisan lean compared to historical data.