{"id":285,"date":"2022-02-04T14:43:02","date_gmt":"2022-02-04T18:43:02","guid":{"rendered":"https:\/\/iterudio.com\/?p=285"},"modified":"2022-02-04T14:43:02","modified_gmt":"2022-02-04T18:43:02","slug":"statistics-vs-analytics-sports-in-general-and-bowling-in-particular","status":"publish","type":"post","link":"https:\/\/www.iterudio.com\/?p=285","title":{"rendered":"statistics vs analytics, sports in general and bowling in particular"},"content":{"rendered":"\n

what a title – first the youtube video demo\/pitch for the “bowling analytics” product …<\/p>\n\n\n

\nhttps:\/\/www.youtube.com\/watch?v=0JKbL4_UEwc&t=1385s\n<\/div><\/figure>\n\n\n

statistics vs analytics<\/h2>\n\n\n

Yes, there is a difference between “statistics” and “analytics” – maybe not a BIG difference but there is a difference.<\/p>\n\n\n

“Statistics<\/a>” is about collecting and interpreting “masses of numerical data.” “Analytics<\/a>” is about logical analysis – probably using “statistics”.<\/p>\n\n\n

Yeah, kinda slim difference – the point being that there is a difference between “having the numbers” and “correctly interpreting the numbers.”<\/p>\n\n\n

“Data analysis” becomes an exercise in asking questions and testing answers – which might have been how a high level “statistician” described their job 100 years ago – i.e. I’m not dogmatic about the difference between “statistics” and “analytics”, just establishing that there are connotations<\/a> involved. <\/p>\n\n\n

Analytics and Sports<\/h2>\n\n\n

Analytics as a distinct field has gained popularity in recent years. In broad strokes the fields of “data science”, “artificial intelligence”, and “machine learning” all mean “analytics.”<\/p>\n\n\n

For a while the term “data mining” was popular – back when the tools to manage “large data sets” first became available. <\/p>\n\n\n

I don’t want to disparage the terms\/job titles – the problem is that “having more data” and having “analysis to support decisions” does not automatically mean “better leadership.”<\/p>\n\n\n

It simply isn’t possible to ever have “all of the information” but it is very easy to convince “management types” that they have “data” supporting their pet belief.<\/p>\n\n\n

e.g. I always like to point out that there are “trends” in baby name popularity (example site here<\/a>) – but making any sort of conclusion from that data is probably specious.<\/p>\n\n\n

What does this have to do with “sports” – well, “analytics” and sports “management” have developed side by side.<\/p>\n\n\n

Baseball’s word for the concept of “baseball specific data analysis<\/a>” dates back to 1982 – about the time that “personal computers” where starting to become affordable and usable by “normal” folks.<\/p>\n\n\n

My round about point today is that most “analytics” fall into the “descriptive” category by design\/definition.<\/p>\n\n\n

e.g. if you are managing a ‘sportball’ team and have the opportunity to select players from a group of prospects – how do you decide which players to pick? <\/p>\n\n\n

Well, in 2022 the team is probably going to have a lot of ‘sportball’ statistics for each player – but do those statistics automatically mean a player is a “good pick’ or a “bad pick”? Obviously not – but that is a different subject.<\/p>\n\n\n

The team decision process will (probably) include testing players physical abilities and watching the players work out – but neither of those 100% equates to “playing the game against other skilled opponents.”<\/p>\n\n\n

That player with great statistics might have been playing against a lower level of competition. That player that has average “physical ability test scores” might be a future Hall of Famer because of “hidden attributes”<\/p>\n\n\n

i.e. you can measure how fast an athlete can run, and how high they can jump – but you can’t measure how much they enjoy playing the game.<\/p>\n\n\n

MEANWHILE back at the ranch<\/h2>\n\n\n

Now imagine that you are an athlete and you want to improve your ‘sportball’ performance. How do you decide what to work on?<\/p>\n\n\n

Well, the answer to that question is obviously going to be very sport AND athlete specific. <\/p>\n\n\n

However, your ‘sportball’ statistics are almost certainly not going to help you make decisions on how\/what you should be trying to develop – i.e. those statistics will be a reflection of how well you have prepared, but do not directly tell you how to prepare.<\/p>\n\n\n

Bowling<\/h2>\n\n\n

Full disclosure – I am NOT a competitive bowler. I have participated\/coached other sports – but I’m a “casual bowler.” i.e. if I have misinterpreted the sport, please let me know \ud83d\ude09<\/p>\n\n\n

Now imagine that someone has decided that they want to improve their “bowling average” – how should they approach the problem?<\/p>\n\n\n

  • Step 1 would be to establish a baseline from which improvements can be measured.<\/li>
  • Step 2 would be to determine what you need to “work on” to improve your scores from Step 1.<\/li>
  • Step 3 would be to establish a session of “practices” to work on the items from Step 2.<\/li>
  • Step 4 would be to re-test the items from Step 1 and adjust steps 2 and 3 accordingly.<\/li><\/ul>\n\n\n

    Sure, I just described the entire field of “management” and\/or “coaching” – but how well a manager\/coach helps athletes through the above (generic) process will be directly reflected in wins\/losses in competition. <\/p>\n\n\n

    Remember that the old axiom that “practice makes perfect” is a little misleading:<\/p>\n\n\n

    Practice does not make perfect. Only perfect practice makes perfect.<\/p>-Vince Lombardi<\/cite><\/blockquote><\/figure>\n\n\n

    Back to bowling – bowling every week might be fun, but won’t automatically mean “better performance.”<\/p>\n\n\n

    Keeping track of your game scores might be interesting, but also won’t automatically mean “better scores.”<\/p>\n\n\n

    I’m told that the three factors for the “amateur bowler” to work on are:<\/p>\n\n\n

    1. first ball pin average<\/li>
    2. single pin spare %<\/li>
    3. multipin spare %<\/li><\/ol>\n\n\n

      In a “normal” game there are 10 pins possible each frame. The bowler gets two balls to knock down all 10. <\/p>\n\n\n

      If your “first ball pin average” is 10, then you are a perfect bowler –and knock all the pins down every frame with your first ball. <\/p>\n\n\n

      To be honest I haven’t seen any real data on “first ball pin averages” – it probably exists in much the same manner that “modern baseball statistics” can be derived from old “box scores” – but I’m told that a first pin average around 9 is the goal. <\/p>\n\n\n

      If you consistently average 9 pins on your first throw – then you have a consistent “strike” delivery.<\/p>\n\n\n

      Which then means that IF you consistently knock down 9 pins – you will have to pickup “single pin spares” on a regular basis.<\/p>\n\n\n

      Then “multipin spares” are going to be an exercise in statistics\/time and fate. Obviously if you average 9 pins on your first ball, the number of “multipin spare” opportunities should be relatively small.<\/p>\n\n\n

      SO those are the data points being tracked with my “bowling analytics” application.<\/p>\n","protected":false},"excerpt":{"rendered":"

      what a title – first the youtube video demo\/pitch for the “bowling analytics” product … statistics vs analytics Yes, there is a difference between “statistics” and “analytics” – maybe not a BIG difference but there is a difference. “Statistics” is about collecting and interpreting “masses of numerical data.” “Analytics” is about logical analysis – probably […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2,3,5,12],"tags":[],"class_list":["post-285","post","type-post","status-publish","format-standard","hentry","category-business","category-computers","category-gaming","category-sports"],"_links":{"self":[{"href":"https:\/\/www.iterudio.com\/index.php?rest_route=\/wp\/v2\/posts\/285","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.iterudio.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.iterudio.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.iterudio.com\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.iterudio.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=285"}],"version-history":[{"count":0,"href":"https:\/\/www.iterudio.com\/index.php?rest_route=\/wp\/v2\/posts\/285\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.iterudio.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=285"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.iterudio.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=285"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.iterudio.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=285"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}