The Jammer Quotient

The JQ is a statistical comparison of jammers based on their rankings in five categories. The maximum JQ a jammer can receive is 50. The table below illustrates the evaluation of a JQ for the February 27th bout between ToRD’s CN Power and the Rideau Valley Vixens (only the top 5 are shown)*.

Jammer Total Points Points Per Jam Plus/ Minus Jam % Lead % JQ
Lunchbox (CNP) 48 (9) 4.36 (9) +36 (9) 23.4 (8) 72.7 (9) 44
Land Shark CNP) 53 (10) 3.78 (7) +45 (10) 29.7 (9) 57.1 (7) 43
Defecaitlin (CNP) 45 (8) 4.5 (10) +29 (8) 21.2 (6) 70 (8) 40
Marvel S. Maven (CNP) 25 (7) 4.16 (8) +20 (7) 12.7 (3) 100 (10) 35
Soul Rekker (RVV) 19 (6) 1.18 (4) -35 (5) 34 (10) 50 (6) 31

CN Power’s Lunchbox received the highest JQ. Interestingly, she didn’t actually lead in any of the five categories but placed second in four and third in the fifth (the numbers in brackets designate the ranking points, 10 for first place, etc). So for this bout, consistency was rewarded, as I imagine it always will be. Overall, all of the CN Power jammers had their way with the Vixens; despite a huge effort by Soul Rekker, the difference was in the jammers. The game was essentially over after the fourth jam when Defecaitlin (that’s Dust Bunny to all you Gore Gore fans) skated to a double grand slam and more than doubled the lead to 19-2.

This particular example doesn’t provide ideal data for a number of reasons. For one, it’s just one game, and there were only eight skaters who jammed a statically significant amount of times (I cut it off at 6 jams). The more data available, the more accurate the JQ, so during ToRD’s regular season, the teams will play enough games and get in enough jams to make a much more accurate judge of the statistical significance a jammer has to her team.

The data in this example are also skewed heavily in CN Power’s favour given the one-sided nature of the bout (199-49). I wouldn’t expect such high JQs over an extended period of time or among a much more even playing field. .

In the next post I’ll look at each category in more detail and justify the decision to include it.

* These stats are unofficial and are based on post bout analysis of video shot by Layer9.

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7 comments

  1. Interesting approach to game analysis and what the game needs more of if it’s to attract more fans

    The ToRD scoreboard appears to run Derbyboard 2.2 software, one of it’s features is the creation of a log file which records jammer names and scores per jam per doc “Every time a jam stops, the results of that jam (start time, stop time, jammers, LJ status, points) are recorded to a stats page, and automatically exported to an external text file” – you might be able to use the data to automate your analysis if you ask for a copy of the stats file at the end of the bout.

    Nice to know that people watch the videos 🙂

  2. The numbers in parentheses next to the stat represent points gained based on a top-ten ranking in each category (10 points for first, 9 for second, etc…). This model gives equal weighting to each stat. It’s clearer when you look at each category individually, as I did in a subsequent post: https://derbynerd.wordpress.com/2010/03/11/the-jammer-quotient-explained/

    I showed only the top five for space reasons (and because the stats were from a single, one-sided bout and dropped off considerably.)

    Are you applying this? To a league? A single game or cumulative? I would love to hear the results if you are!

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