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Trump score How often Steel votes in line with Trump’s position | Trump margin Trump’s share of the vote in the 2016 election in the member’s state or district minus Clinton’s | Predicted score How often Steel is expected to support Trump based on Trump’s 2016 margin | Trump plus-minus Difference between Steel’s actual and predicted Trump-support scores | |
|---|---|---|---|---|
| Career | 100.0% | -1.7 | 29.1% | +70.9 |
| 117th Congress | 100.0% | -1.7 | 29.1% | +70.9 |
Trump score How often Steel votes in line with Trump’s position | 100.0% |
|---|---|
| Trump margin Trump’s share of the vote in the 2016 election in the member’s state or district minus Clinton’s | -1.7 |
Predicted score How often Steel is expected to support Trump based on Trump’s 2016 margin | 29.1% |
Trump plus-minus Difference between Steel’s actual and predicted Trump-support scores | +70.9 |
| Date | Measure | Trump Position | Steel Vote | Agree with Trump? | Likelihood of agreement | Plus-minus |
|---|---|---|---|---|---|---|
| Jan. 13 | Impeaching President Trump on a charge of incitement of insurrection (232-197) | Trump Position oppose | Steel Vote No | Agree with Trump?  | Likelihood of agreement 29.1% | Plus-minus +70.9 |
| Average | 100.0% | 29.1% | +70.9 | |||
See more about Michelle Steel at ProPublica
Members’ “likelihood of agreement” scores on each vote are calculated using a regression for which the input is Trump’s 2016 vote margin in every member’s state or district and the output is the probability that a member will vote for the bill. The plus-minus on each vote is the difference between the member’s vote (100 percent for a “yes,” 0 percent for a “no”) and the likelihood of agreement. Averages do not include missed votes. How this works »
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