Pete Tucker, a writer in Washington, D.C., writes about a peculiar phenomenon: Opinion polls consistently underrate candidates who are progressive and who are black or Hispanic.

Predicting the winner (falsely) and underreporting the support for a candidate is a form of voter suppression, he writes.

Ayanna Pressley, a progressive African American congressional candidate from Boston, was predicted to lose by 13 points in the Democratic primary, but she won by 18 points. In the primary for a New York congressional seat, the final poll showed Latina socialist Alexandria Ocasio-Cortez trailing the Democratic incumbent by 36 points; she won by 15 points. In Georgia, polls showed gubernatorial candidate Stacey Abrams, the African American former minority leader of the State House of Representatives, well ahead in the Democratic primary, but nowhere near the 53 points she won by.

In Florida, the nation’s third largest state, polls for the Democratic gubernatorial primary showed Andrew Gillum, the progressive African American mayor of Tallahassee, finishing fourth, with around 12 percent of the vote. But Gillum won 34 percent of the vote, nearly three times what most polls had him at, and captured the nomination.

Then there’s Maryland, where the Democratic gubernatorial primary was supposed to be neck-and-neck, but the more progressive candidate, Ben Jealous, walked away with it, beating his chief challenger by over 10 points and taking all but two counties.

While primaries are difficult to predict, today’s polls are not just failing, they seem to be doing so in a way that makes progressive candidates of color appear to have less support than they do.

These polling errors are far from harmless. Faulty polls can turn into real losses by suppressing both votes and funding. It’s not hard to see why: Who is excited to back a sure-loser? This applies to potential voters, who are more likely to stay home on election day if their preferred candidate has no shot, as well as to potential donors, who would rather support a winner.