Which California Assembly Candidates Over or Underperformed in 2024?

Political analysts and commentators frequently discuss whether candidates performed better or worse than expected in elections. But what exactly does this mean? Against what standard should we measure a candidate's performance?

Today, I want to share some analysis of the 2024 California Assembly races using what I call "partisan baseline" measurements. Using The Ballot Book's comprehensive database of California election results from multiple cycles, we've developed insights that go beyond surface-level numbers.

Understanding the Baseline

When evaluating election results, many analysts simply compare a candidate's performance to their party's registration numbers in the district. You'll often hear statements like "Republican candidate Smith won by 3 points in a district where Democrats have a 5-point registration advantage." But this approach can be misleading—registered voters don't always turn out at equal rates, and voters registered as independents or "no party preference" can swing significantly toward either party in actual elections.

Our partisan baseline instead measures how voters in a district actually behave at the ballot box. We analyze recent statewide races—Governor, U.S. Senate, Secretary of State, Attorney General, and other constitutional offices—to establish what percentage of the vote a typical Democrat or Republican receives in each district.

This baseline is calculated using a weighted average of results from 2018 and 2022 statewide elections (60% from 2022, 40% from 2018). We deliberately exclude presidential races—particularly to avoid the Trump effect, which has proven to be an outlier rather than representative of typical partisan voting patterns. 

What makes our approach particularly valuable is how we handle redistricting. The Ballot Book's database recalculates historical election results within today's district boundaries, ensuring we're making apples-to-apples comparisons across election cycles.

So when we say a district has a Democratic baseline of 55%, it means Democrats typically earn about 55% of the vote in that district during standard statewide races. When a candidate significantly exceeds or falls short of this baseline, it reveals something meaningful about their specific appeal or campaign effectiveness beyond normal partisan voting patterns.

The Data: Over/Under Performance in 2024 Assembly Races

Our analysis compares each candidate’s actual vote percentage to what the district’s baseline would predict. A candidate who exceeds this baseline is said to be overperforming; one who falls short is underperforming.

Democratic Performance

Overperformers:

• James C. Ramos (District 45):
  • Achieved 63.84% versus an expected 60.50%, or +3.34% above baseline.
• Esmeralda Soria (District 27):
  • Scored 53.92% compared to a 50.78% baseline, exceeding expectations by +3.14%.
• Robert Rivas (District 29):
  • Earned 66.01% against a baseline of 63.58%, a +2.43% boost.
• Cecilia M. Aguiar-Curry (District 4):
  • Pulled 66.48% while the baseline was 64.22% (+2.26%).
• Steve Bennett (District 38):
  • Finished with 63.37% versus a 61.32% baseline, or +2.05%.

Notably, many of these candidates are incumbents in districts already leaning Democratic. Their ability to expand margins suggests they’re reaching voters beyond their core base—likely thanks to strong name recognition and robust campaign operations. However, it could also signal a weak opponent (due to such overwhelming odds deterring more credible candidates), or other factors at play.

Underperformers:

• Mike Gipson (District 65):
  • Won with 70.85% but was −7.67% below the expected 78.52%.
• Celeste Rodriguez (District 43):
  • Achieved 66.65% against a 73.54% baseline, underperforming by −6.89%.
• Lisa Calderon (District 56):
  • Secured 56.68% versus a 61.52% baseline (−4.84%).
• Jose “Joey” Acuña Jr. (District 36):
  • Received 48.19% while the baseline was 52.87% (−4.68%), contributing to his loss.
• Nick Schultz (District 44):
  • With 65.90% compared to a 70.27% baseline, he underperformed by −4.37%.

Even in some safe Democratic districts, falling significantly short of the expected vote share can signal issues with candidate appeal or campaign execution.

Republican Performance

Overperformers:

• Lydia A. Gutierrez (District 65):
  • Although she ended with 29.15%, that’s +7.67% above the GOP baseline of 21.48%—a notable boost in a tough district.
• Victoria Garcia (District 43):
  • Scored 33.35% versus a 26.46% baseline, an overperformance of +6.89%.
• Jamie “James” Gallagher (District 3):
  • Garnered 66.27% against a baseline of 60.48%, or +5.79% above expectations.
• Diane Dixon (District 72):
  • Achieved 59.46% compared to a 54.39% baseline, a +5.07% gain.
• Jessica Martinez (District 56):
  • Although she lost with 43.32%, that was +4.84% over the baseline of 38.48%.

These figures illustrate that even when Republicans are running in predominantly Democratic districts, some candidates can significantly exceed their historical performance. In more competitive areas, such overperformance can translate directly into victory. Even though some of these outcomes were lopsided, the districts or candidates might provide insight for future contests.

Underperformers:

• Scott P. Olson (District 45):
  • Came in at 36.16% versus a 39.50% baseline, underperforming by −3.34%.
• Joanna Garcia Rose (District 27):
  • Scored 46.08% compared to a 49.22% baseline (−3.14%).
• Kristie Bruce-Lane (District 76):
  • Finished with 45.97%, which is −2.28% below the expected 48.25%.
• George Barks (District 66):
  • Recorded 39.78% against a 41.91% baseline (−2.13%).
• Deborah “Deb” Baber (District 38):
  • With 36.63% compared to an expected 38.68%, she was −2.05% off.

Even relatively small shortfalls in performance can be decisive in competitive races, emphasizing the importance of every percentage point.

Where Performance Made a Decisive Difference

In some districts, the margin between actual performance and the baseline appears to have directly influenced the outcome:

• District 36:

  • The Democratic baseline was 52.87%. Republican Jeff Gonzalez finished with 51.81% compared to Democrat Jose “Joey” Acuña Jr.’s 48.19%. Gonzalez’s performance of +4.68% above his baseline versus Acuña’s −4.68% proved enough to secure the seat.

• District 47:

  • Here, the baseline was around 50.98% for Democrats. Republican Greg Wallis posted 51.19%, while Democrat Christy Holstege garnered 48.81%. The difference of roughly 2.17% in performance gave Wallis the edge.

• District 58:

  • With a Democratic baseline of approximately 53.89%, Republican Leticia Castillo’s 50.19% came +4.08% above the GOP norm, while Democrat Clarissa Cervantes fell −4.08% short. In this razor-thin contest, these differences were decisive.

In each of these cases, the candidate’s ability to outperform (or avoid underperforming) relative to historical expectations made all the difference in the final result.

Overall Trends and Final Thoughts

This analysis offers a more nuanced look at election performance by comparing actual results to a district's partisan baseline. Here are a few key takeaways:

Party-Wide Performance Patterns

When we analyze all 126 candidates (63 from each party), an interesting pattern emerges. On average, Democrats underperformed their district baselines by about 1.36 percentage points, while Republicans overperformed by the same margin (+1.36). This symmetry suggests a systematic shift in voter behavior this cycle that slightly favored Republican candidates across the board.

Incumbency Matters - But Differently By Party

The power of incumbency played out very differently between the parties:

• Republican incumbents significantly outpaced expectations, averaging +2.61 points above their baselines. Standouts include Jamie Gallagher (+5.79), Diane Dixon (+5.07), and Juan Alanis (+4.16), with only a couple falling below their district benchmarks.
• Democratic incumbents, surprisingly, underperformed as a group, averaging 0.78 points below their baselines. While some Democrats like James Ramos (+3.34) and Al Muratsuchi (+2.13) exceeded expectations, more fell short—including dramatic underperformances from Mike Gipson (-7.67), Tina McKinnor (-5.00), and Lisa Calderon (-4.84).
• When combined, all 49 incumbents (37 Democrats, 12 Republicans) essentially broke even (+0.05), but this masks the significant partisan difference in incumbent performance.

High Gains in Challenging Districts

Some Republican candidates, such as Lydia A. Gutierrez (District 65) and Victoria Garcia (District 43), achieved significant gains relative to their historical averages—even in districts that heavily favor Democrats.

Impact in Close Races

In competitive districts like 36, 47, and 58, even modest swings above or below the baseline were enough to alter the outcome.

The Value of Data

Unlike traditional metrics such as voter registration—which can be misleading—this method is based on actual voting behavior in statewide contests. By adjusting for recency and excluding outlier races (like those featuring Trump), our adjusted baseline provides a clearer picture of a district's partisan lean.

If you subscribe to The Ballot Book, you gain access to this kind of detailed, multi-cycle analysis that can help campaigns and researchers understand where performance truly deviates from the norm—offering a powerful tool for strategic decision-making in future elections.

Complete Data Table

Each district in the table below links to its complete profile in The Ballot Book, where you can explore detailed maps, historical results, and demographic information. Not a subscriber yet? You can explore all these features in our sample district profile for Assembly District 57.

*Note: Districts marked as "NA" featured either two Democrats, two Republicans, or significant third-party candidates, making traditional partisan performance comparison impractical. Candidates marked with an asterisk are incumbents.