Computer-aided scouting: Difference between revisions

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'''Computer-Aidedaided Scoutingsports :scouting''' - While human scouts are far more recognized throughoutis the historyuse of sports.data Computer-Aidedanalysis Scoutsby are beginningcomputer to haveassist successsports ratio[[Scout that rival its human counterpart. The initial intent of computer aided scouting was(sport)|scouts]] to aide the human scout with information. The human scoutidentify and therecruit researchernew workedtalented great togetherplayers. However, when pioneersPioneers like [[Bill James]] began to analyze the data and apply mathematical principals and new non-conventional formulas to predict success and failures of a baseball player or team., Essentiallya thisdevelopment createdcalled uncommon[[sabermetrics]]. andThe uncomfortablefoundation groundsof betweencomputer-aided thescouting humanis scouts views and the computer analysis personnelstatistics.

The foundation of computer-aided scouting is statistical separation which is not to be influenced by media or opinion. Results ultimately should withstand the principals of mathematics, and some basic rules of physics. Ultimately any results released should reflect the nature of the players, the team, and the sport itself.

==Critics Circlecircle==

Computer-aided Scoutingscouting began as a means for Scoutsscouts and Managersmanagers to log mass amounts of player and team information compiled from [[box scoresscore]]s, stat-sheets and personalized specific information pertaining to players and teams throughout the years. This information was interpreted through advanced Mathematicalmathematical formulas created from extensive research studies of each sport. Once this information was derivedtabulated, team personnel begin to implement these results into the game. ManyAfter teamsearly beganpositive toresults, experience an undeniable scale of success and the background of their success began to leak to the mainstream media and othermany professional teams. Soonadopted nearlymathematical everytools teamfor in some way or the other uses computer-aided scouting to aideplayer and gauge the performance and value of players and the teams the teams they are on or competegame againstmanagement.

[[MLB]] and theethe [[NBA]] begin to employ these analysis and move them into prominent roles inside their teams as Scouts to even General Managers. The marriage between Computer-aided Scouting and human eye Scouting has been at odds for over a decade. Both ways of scouting have proven to be as viable and valuable as the other.{{Citation needed|date=July 2014}} The NCAA has adapted a rating system produced by [[Jeff Sagarin]] that uses computer-aided scouting to a science to better understand the strength and weaknesses of a team as a rating.

Computer-aided Scoutingscouting has adapted many unique mathematical formulas by takentaking into account an existing or potential players value to his team, his physical attributes, and even projected success/failures against a variety of situations and potential opponents. ManySome of thethese actualmethods formulashave canbeen be found in many books and articles that are writtenpublished by members areof founders of[[Sabermetricssabermetrics]] for [[baseball]] and [[APBRmetrics|APBR]] for [[basketball]].

Some advanced objectives of Computer-aided Scouting was to find a way that Professionals could use this information as an aid, but many scouts simply refuse to recognize its value and instead other front office personnel and coaches lean on the person doing the analysis and research to explain his/her findings. Most researchers try to find a foundational formula that directly correlates success and failure through repetition and professional knowledge.

MLB and thee NBA begin to employ these analysis and move them into prominent roles inside their teams as Scouts to even General Managers. The marriage between Computer-aided Scouting and human eye Scouting has been at odds for over a decade. Both ways of scouting have proven to be as viable and valuable as the other.

The NCAA has adapted a rating system produced by [[Jeff Sagarin]] that uses computer-aided scouting to a science to better understand the strength and weaknesses of a team as a rating.

Computer-aided Scouting has adapted many unique mathematical formulas by taken into account an existing or potential players value to his team, his physical attributes, and even projected success/failures against a variety of situations and potential opponents. Many of the actual formulas can be found in many books and articles that are written by members are founders of[[Sabermetrics]] for baseball and [[APBR]] for basketball.

Computer-aided Scouting is now on the frontier of capology for all major sports in determining values of each player and the foreseeable effects of signing a player to a short or long term contract versus the team salary cap which all major sports must abide by.

Computer-aided Scouting is largely being used with Microsoft Excel Spreadsheet and from there it the information is transfered to a personal or team private database.

==References==

{{Reflist}}

*[http://www.microsoft.com/presspass/features/2000/oct00/10-17pockethoops.mspx Microsoft.com]

* [http://www.sciencedaily.com/releases/1998/03/980309041942.htm Science Daily]

==External links==

* [http://www.hoopsworld.com/ HoopsWorld]

* [http{{webarchive |url=https://wwwweb.archive.org/web/20070930070741/http://scoutingthenba.com/index.htm/ |title=ScoutingtheNba] |date=2007-09-30}}

* [http://82games.com/ 82games]

* [https://web.archive.org/web/20080817032744/http://search.espn.go.com/john-hollinger/| John Hollinger Espn]

* [{{webarchive |url=http://webarchive.loc.gov/all/20011116033513/http://www.kiva.net/~jsagarin/sports/sports.html |title=Jeff Sagarin] |date=2001-11-16}}

[[Category:NBA draft]]

Basketball statistics

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[[Category:National Basketball Association Draft]]