Difference between revisions of "Conversion"

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So for example, [[bonus conversion]] generally refers to performance on all bonuses played across a tournament.</onlyinclude>
 
So for example, [[bonus conversion]] generally refers to performance on all bonuses played across a tournament.</onlyinclude>
  
Various [[conversion metrics]] (like [[points per game]] and [[points per bonus]]) derived from [[conventional statistics]] can offer basic insight into team skill or tournament difficulty.
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Various [[conversion metrics]] (like [[points per game]] and [[points per bonus]]) derived from [[statistics|conventional statistics]] can offer basic insight into team skill or tournament difficulty.
 
On the other hand, [[conversion statistics]], which specifically measure the conversion of individual questions, require more fine-grained data or special tools.
 
On the other hand, [[conversion statistics]], which specifically measure the conversion of individual questions, require more fine-grained data or special tools.
  
 
[[Category: Quizbowl lingo]]
 
[[Category: Quizbowl lingo]]
 
{{c|Quizbowl concepts}}
 
{{c|Quizbowl concepts}}

Revision as of 11:25, 1 July 2021

Not to be confused with downconversion (editing questions to be shorter and easier to use them for another purpose) or upconversion (the opposite).

In quizbowl jargon, conversion (or converting a question) is the act of getting a question correct. The term can be understood as taking the words of a question and "converting" them into points for one's team.

In most contexts, "conversion" refers to aggregate conversion (or conversion rate), usually across an entire tournament. So for example, bonus conversion generally refers to performance on all bonuses played across a tournament.

Various conversion metrics (like points per game and points per bonus) derived from conventional statistics can offer basic insight into team skill or tournament difficulty. On the other hand, conversion statistics, which specifically measure the conversion of individual questions, require more fine-grained data or special tools.