This chapter takes an integrative, multi-methodological approach to the analysis of political attacks during presidential debates. Using continuous response measures (CRM) recorded from viewers in real time during the third and final US presidential debate between Donald Trump and Hillary Clinton in 2016, we identify an equal number of Trump’s character and issue attacks on Clinton. We then analyze the mean differences in CRM response to these episodes and subject each segment to nonverbal coding to determine candidate display behavior at the time of the incident. Results indicate that viewers, regardless of political party affiliation, penalize Trump more for character attacks than issue attacks. Independents show the most aversion to attacks overall. Several instances of Trump standing behind and appearing to “hover over” Clinton from the second debate were then shown to focus groups to probe the boundaries of norm violations and discern how nonverbal displays exhibited by Trump intensified the perceived aggression of his verbal attacks.