Difference between revisions of "Conversion metrics"
Kevin Wang (talk | contribs) |
Kevin Wang (talk | contribs) |
||
| (3 intermediate revisions by the same user not shown) | |||
| Line 1: | Line 1: | ||
| − | <onlyinclude> | + | {{confuse|[[Conversion stats]]}} |
| − | '''Conversion metrics''' are a measure of how hard a given tournament is compared to the field it attracted. While no single conversion metric has been promoted as the best indicator of difficulty, several different conversion metrics combine to give an overall picture of the tournament.</onlyinclude> | + | <onlyinclude>'''Conversion metrics''' are a measure of how hard a given tournament is compared to the field it attracted based on how many [[questions]] were [[converted]]. While no single conversion metric has been promoted as the best indicator of difficulty, several different conversion metrics combine to give an overall picture of the tournament.</onlyinclude> |
Conversion metrics are often cited to prove a tournament's relative [[accessibility]]. | Conversion metrics are often cited to prove a tournament's relative [[accessibility]]. | ||
| − | ==Tossup Conversion Rate== | + | ==Examples== |
| + | ===Tossup Conversion Rate=== | ||
The tossup conversion rate simply gives the percentage of tossups correctly answered over the entire tournament, by all teams participating. Many people choose to leave out tiebreaker and finals games when computing this as only a small percentage of the field plays these games. | The tossup conversion rate simply gives the percentage of tossups correctly answered over the entire tournament, by all teams participating. Many people choose to leave out tiebreaker and finals games when computing this as only a small percentage of the field plays these games. | ||
| − | ==Average Bonus Conversion== | + | ===Average Bonus Conversion=== |
The average bonus conversion adds up the total number of bonus points earned by all teams at the tournament and divides by the total number of bonuses earned. | The average bonus conversion adds up the total number of bonus points earned by all teams at the tournament and divides by the total number of bonuses earned. | ||
| − | ==Median Bonus Conversion== | + | ===Median Bonus Conversion=== |
Because the average bonus conversion can be severely skewed by a few extremely good or extremely poor teams, the median bonus conversion is often used as a substitute for average bonus conversion. Median bonus conversion is found by taking the [[bonus conversion]] of every team participating at the tournament and computing the median. | Because the average bonus conversion can be severely skewed by a few extremely good or extremely poor teams, the median bonus conversion is often used as a substitute for average bonus conversion. Median bonus conversion is found by taking the [[bonus conversion]] of every team participating at the tournament and computing the median. | ||
| − | ==Average/Median Points Per Game== | + | ===Average/Median Points Per Game=== |
The average points per game adds up the total number of points scored by all teams and divides by the number of games played. As with bonus conversion, a median points per game is sometimes used as a more accurate conversion metric. | The average points per game adds up the total number of points scored by all teams and divides by the number of games played. As with bonus conversion, a median points per game is sometimes used as a more accurate conversion metric. | ||
| − | ==APPK== | + | ===APPK=== |
APPK, or Adjusted Points per Thousand Available, is a conversion metric popularized by [[Matt Weiner]] that allows comparisons across formats. The total points scored by the field, discounting all powers and negs, is divided by the number of games. The result is then divided by the theoretical maximum total score possible in a single game (again, discounting any powers and negs) and multiplied by 1000. | APPK, or Adjusted Points per Thousand Available, is a conversion metric popularized by [[Matt Weiner]] that allows comparisons across formats. The total points scored by the field, discounting all powers and negs, is divided by the number of games. The result is then divided by the theoretical maximum total score possible in a single game (again, discounting any powers and negs) and multiplied by 1000. | ||
| − | ==Words per Buzz/Adjusted Words per Buzz== | + | ===Words per Buzz/Adjusted Words per Buzz=== |
The most promising yet-to-be-developed conversion metric, Words per Buzz quantifies exactly how long it takes players to buzz in by averaging the number of words it takes for the first player to buzz in. A Words per Buzz metric allows individual tossups to be scrutinized to check whether certain clues were placed too early, diagnose [[difficulty cliff|difficulty cliffs]], and provide data for placement of [[powers|power marks]] at future tournaments. | The most promising yet-to-be-developed conversion metric, Words per Buzz quantifies exactly how long it takes players to buzz in by averaging the number of words it takes for the first player to buzz in. A Words per Buzz metric allows individual tossups to be scrutinized to check whether certain clues were placed too early, diagnose [[difficulty cliff|difficulty cliffs]], and provide data for placement of [[powers|power marks]] at future tournaments. | ||
| Line 26: | Line 27: | ||
[[Category: Quizbowl lingo]][[Category: Statistics]] | [[Category: Quizbowl lingo]][[Category: Statistics]] | ||
[[Category:Original QBWiki Page]] | [[Category:Original QBWiki Page]] | ||
| + | {{c|Quizbowl concepts}} | ||
Latest revision as of 10:12, 1 July 2021
- Not to be confused with Conversion stats.
Conversion metrics are a measure of how hard a given tournament is compared to the field it attracted based on how many questions were converted. While no single conversion metric has been promoted as the best indicator of difficulty, several different conversion metrics combine to give an overall picture of the tournament.
Conversion metrics are often cited to prove a tournament's relative accessibility.
Examples
Tossup Conversion Rate
The tossup conversion rate simply gives the percentage of tossups correctly answered over the entire tournament, by all teams participating. Many people choose to leave out tiebreaker and finals games when computing this as only a small percentage of the field plays these games.
Average Bonus Conversion
The average bonus conversion adds up the total number of bonus points earned by all teams at the tournament and divides by the total number of bonuses earned.
Median Bonus Conversion
Because the average bonus conversion can be severely skewed by a few extremely good or extremely poor teams, the median bonus conversion is often used as a substitute for average bonus conversion. Median bonus conversion is found by taking the bonus conversion of every team participating at the tournament and computing the median.
Average/Median Points Per Game
The average points per game adds up the total number of points scored by all teams and divides by the number of games played. As with bonus conversion, a median points per game is sometimes used as a more accurate conversion metric.
APPK
APPK, or Adjusted Points per Thousand Available, is a conversion metric popularized by Matt Weiner that allows comparisons across formats. The total points scored by the field, discounting all powers and negs, is divided by the number of games. The result is then divided by the theoretical maximum total score possible in a single game (again, discounting any powers and negs) and multiplied by 1000.
Words per Buzz/Adjusted Words per Buzz
The most promising yet-to-be-developed conversion metric, Words per Buzz quantifies exactly how long it takes players to buzz in by averaging the number of words it takes for the first player to buzz in. A Words per Buzz metric allows individual tossups to be scrutinized to check whether certain clues were placed too early, diagnose difficulty cliffs, and provide data for placement of power marks at future tournaments.
Adjusted Words per Buzz is a variant of Words per Buzz in which the Words per Buzz for each tossup is divided by the total word count of that tossup. This allows for comparisons across different tossup lengths.