Introduction
Welcome, and thank you for participating in this survey.
In this survey, you will be presented with pairs of years, each representing a possible date when SpaceX’s Starship might successfully land a crewed mission on Mars. For each pair, we ask you to choose the year that you believe is more likely to mark this milestone.
Your selections will help us identify collective expectations about the timeline for interplanetary travel, based on current knowledge, technological progress, and developments in the space industry.
There are no right or wrong answers—please base your choices on your best judgment. Your responses will contribute to a clearer picture of public and expert opinion on this important topic.
Let’s begin.
Your Opinion?
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Current Results
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Understanding the Elo Algorithm in Pairwise Surveys
The Elo algorithm, originally developed to rank chess players, is commonly used in pairwise comparison surveys to assess the relative likelihood, strength, or preference of different options. In a survey focused on predicting the year Starship might reach Mars, the Elo algorithm helps rank each year based on collective judgment from participants.
Core Idea
Each year in the survey starts with the same initial rating. When two years are presented, and a participant selects the one they believe is more likely for a Mars landing, the Elo algorithm updates both ratings. The chosen year gains points, while the other loses points.
The size of the rating change depends on:
- The difference between the two ratings at the time of comparison
- Which year is selected as more likely
- Whether the outcome is expected or surprising based on current ratings
If a lower-rated year wins, it gains more points than if a higher-rated year wins again. This allows the system to adapt dynamically to changing perceptions.
How the Process Works
- Initialization: Every year begins with the same default Elo rating.
- Pairwise Comparison: The user is shown two years and asked which is more likely.
- Score Update: The Elo algorithm updates the ratings of both years based on the comparison result.
- Ongoing Adjustment: As more users participate, ratings continue to evolve, gradually forming a consensus-based ranking.
Benefits of Using the Elo Algorithm
- Efficient Data Use: Rankings can be formed with far fewer total comparisons than traditional methods require.
- Handles Incomplete Data: Not every possible pair needs to be compared, making it ideal for large option sets.
- Dynamic and Self-Correcting: Ratings improve in accuracy as more comparisons are made.
- Captures Strength of Preference: Elo scores not only reflect what options are favored but how decisively they are chosen.
Interpreting Elo Scores
Years with higher Elo scores are considered more likely to be the date when Starship reaches Mars. These scores reflect consistent performance in head-to-head matchups across all participants’ inputs. The final ranking provides a data-driven view of group expectations, revealing both consensus and uncertainty in a clear, quantitative format.
Through this adaptive approach, the Elo algorithm transforms simple user choices into a meaningful prediction model grounded in collective reasoning.
