The Effect Touches, Post Touches, and Dribbles Have on Offense for Men's Division I Basketball
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Offensive and Defensive Plus–Minus Player Ratings for Soccer
applied sciences Article Offensive and Defensive Plus–Minus Player Ratings for Soccer Lars Magnus Hvattum Faculty of Logistics, Molde University College, 6410 Molde, Norway; [email protected] Received: 15 September 2020; Accepted: 16 October 2020; Published: 20 October 2020 Abstract: Rating systems play an important part in professional sports, for example, as a source of entertainment for fans, by influencing decisions regarding tournament seedings, by acting as qualification criteria, or as decision support for bookmakers and gamblers. Creating good ratings at a team level is challenging, but even more so is the task of creating ratings for individual players of a team. This paper considers a plus–minus rating for individual players in soccer, where a mathematical model is used to distribute credit for the performance of a team as a whole onto the individual players appearing for the team. The main aim of the work is to examine whether the individual ratings obtained can be split into offensive and defensive contributions, thereby addressing the lack of defensive metrics for soccer players. As a result, insights are gained into how elements such as the effect of player age, the effect of player dismissals, and the home field advantage can be broken down into offensive and defensive consequences. Keywords: association football; linear regression; regularization; ranking 1. Introduction Soccer has become a large global business, and significant amounts of capital are at stake when the competitions at the highest level are played. While soccer is a team sport, the attention of media and fans is often directed towards individual players. An understanding of the game therefore also involves an ability to dissect the contributions of individual players to the team as a whole. -
The Evolution of Basketball Statistics Is Finally Here
ows ind Sta W tis l t Ready for a ic n i S g i o r f t O w a e r h e TURBOSTATS SOFTWARE T The Evolution of Basketball Statistics is Finally Here All New Advanced Metrics, Efficiencies and Four Factors Outstanding Live Scoring BoxScore & Play-by-Play Easy to Learn Automatically Tags Video Fast Substitutions The Worlds Most Color-Coded Shot Advanced Live Game Charts Display... Scoring Software Uncontested Shots Shots off Turnovers View Career Shooting% Second Chance Shots After Each Shot Shots in Transition Includes the Advanced Zones vs Man to Man Statistics Used by Top Last Second Shots Pro & College Teams Blocked Shots New NET Rating System Score Live or by Video Highlights the Most Sort Video Clips Efficient Players Create Highlight Films Includes the eBook Theory of Evolution Creates CyberLink Explaining How the New PowerDirector video Formulas Help You Win project files for DVDs* The Only Software that PowerDirector 12/2010 Tracks Actual Rebound % Optional Player Photos Statistics for Individual Customizable Display Plays and Options Shows Four Factors, Event List, Player Team Stats by Point Guard Simulated image on the Statistics or Scouting Samsung ATIV SmartPC. Actual Screen Size is 11.5 Per Minute Statistics for Visit Samsung.com for tablet All Categories pricing and availability Imports Game Data from * PowerDirector sold separately NCAA BoxScores (Websites HTML or PDF) Runs Standalone on all Windows Laptops, Tablets and UltraBooks. Also tracks ... XP, Vista, 7 plus Windows 8 Pro Effective Field Goal%, True Shooting%, Turnover%, Offensive Rebound%, Individual Possessions, Broadcasts data to iPads and Offensive Efficiency, Time in Game Phones with a low cost app +/- Five Player Combos, Score on the Only Tablets Designed for Data Entry Defensive Points Given Up and more.. -
2013 Princeton Football Week 1: #22 Lehigh (2-0) at Princeton (0-0)
Princeton Game Notes 2013 Princeton Tigers Football 2013 Princeton Football WEEK 1: #22 LEHIGH (2-0) AT PRINCETON (0-0) Sept. 21, 2013 • 6 pm • powerS Field at princeton Stadium TV/Video ............................................ NBC Sports Network Last At Site ............................... Lehigh 34, PRINCETON 22 Radio/Audio ................... 103.3 FM/GoPrincetonTigers.com Last Five Years .........................................Lehigh leads 3-2 All-Time Series ............................ Princeton leads 39-15-2 Last Princeton Win .............Princeton 17, LEHIGH 14 (2009) Last Year ...................................... LEHIGH 17, Princeton 14 Current Streak .......................................................Lehigh 3 Following the tigerS on twitter Princeton Athletics ....................................... @PUTigers Princeton Football..............................@PUTigerFootball Lights, Camera, Action Saturday’s season opener for Princeton will be televised live on the NBC Sports Network in the Princeton opening game of the network’s Ivy League package. Randy Moss and former Princeton and NFL offensive lineman Ross Tucker ’01 will call the game. Tigers Last season, Princeton hosted Brown on the NBC Sports Network and recorded a 19-0 shutout Head Coach ........................................ Bob Surace of Brown during the Tigers’ four-game win streak. Opening Night 2013 princeton Schedule The Ivy League schedule changed in 2000, and teams began to open their seasons against non- Sept. 21 Lehigh at Princeton ...................6 pm Ivy opponents, all of whom typically play at least twice before that game. Since Princeton went to Sept. 28 Princeton at Georgetown ...........2 pm that format, the Tigers have gone 3-10 in their season openers, and they have lost each of their last Oct. 5 Columbia at Princeton ...............1 pm six (including the last three to Lehigh). Oct. 12 Lafayette at Princeton ...............1 pm Princeton’s last season-opening victory came in 2006; the Tigers went on to win the Ivy League Oct. -
Difference-Based Analysis of the Impact of Observed Game Parameters on the Final Score at the FIBA Eurobasket Women 2019
Original Article Difference-based analysis of the impact of observed game parameters on the final score at the FIBA Eurobasket Women 2019 SLOBODAN SIMOVIĆ1 , JASMIN KOMIĆ2, BOJAN GUZINA1, ZORAN PAJIĆ3, TAMARA KARALIĆ1, GORAN PAŠIĆ1 1Faculty of Physical Education and Sport, University of Banja Luka, Bosnia and Herzegovina 2Faculty of Economy, University of Banja Luka, Bosnia and Herzegovina 3Faculty of Physical Education and Sport, University of Belgrade, Serbia ABSTRACT Evaluation in women's basketball is keeping up with developments in evaluation in men’s basketball, and although the number of studies in women's basketball has seen a positive trend in the past decade, it is still at a low level. This paper observed 38 games and sixteen variables of standard efficiency during the FIBA EuroBasket Women 2019. Two regression models were obtained, a set of relative percentage and relative rating variables, which are used in the NBA league, where the dependent variable was the number of points scored. The obtained results show that in the first model, the difference between winning and losing teams was made by three variables: true shooting percentage, turnover percentage of inefficiency and efficiency percentage of defensive rebounds, which explain 97.3%, while for the second model, the distinguishing variables was offensive efficiency, explaining for 96.1% of the observed phenomenon. There is a continuity of the obtained results with the previous championship, played in 2017. Of all the technical elements of basketball, it is still the shots made, assists and defensive rebounds that have the most significant impact on the final score in European women’s basketball. -
2008-09 Princeton Men's Hockey
2008-09 PRINCETON MEN’S HOCKEY 2008-09 PRINCETON MEN ’S HOCKEY (2-1-0; 1-1-0 ECAC HOCKEY ) This Week’s Storylines 2008-09 PRINCETON SC H EDULE A ND RESULTS HOWDY PARTNER Princeton plays its first of three games this season Date Opponents .................Time/Results against Quinnipiac, its travel-partner. Tonight’s Oct. 25 WESTERN ONTARIO # .......... W, 6-2 game, as well as the game at Princeton on Nov. 26 will count towards the ECAC standings, while the SH OWC A SE A T MEE ha N Dec. 3 meeting is a non-league game. Oct. 31 at Brown ! ...............................W, 4-1 LAST TIME OUT Nov. 1 vs. Ontario I.T. # .....................W, 8-2 Princeton picked up a 2-1 win over Colgate in overtime on Saturday when sophomore Kevin TONIG H T Nov. 7 #17 CORNELL * ...................... L, 0-1 Lohry scored midway through the overtime period to salvage a weekend split. The Tigers fell to Nov. 8 COLGATE * ........................ W, 2-1 (ot) Cornell 1-0 a day earlier. GAME 4 Nov. 11 at Quinnipiac * ........................7 p.m. Tu e s ., No v . 11 • 7 p.m. Nov. 14 at Rensselaer * ......................7 p.m. CORNE ll RE C A P Nov. 15 at Union *................................4 p.m. Cornell edged the Tigers 1-0 last Friday in front TD BankNorth Center • Hamden, Conn. of a capacity crowd at Baker Rink and a national Nov. 21 at St. Lawrence * ....................7 p.m. television audience. Princeton outshot Cornell 43- #12 PRINCETON Nov. 22 at Clarkson * ..........................4 p.m. 19 by Cornell’s Tyler Mugford scored the game’s (2-1-0, 1-1-0 ECAC) Nov. -
Coaches Clinic Registration Form
FAIRFIELD FAIRFIELD BASKETBALL Fairfield University Basketball Coaches Clinic Registration Form The fee to attend the clinic is: BASKETBALL • $60 if you pre-register by October 21 • $75 if you register during the week of the clinic • $50 per coach for staffs of three or more Each coach must fill out his or her own registration form (copies may be made of this application). Due to NCAA rules, the clinic is for coaches only. Players may not participate. Name ________________________________________ Address _______________________________________ City, State, Zip __________________________________ Home Phone ___________________________________ Work Phone ____________________________________ (Please detach and return) E-mail Address __________________________________ School/Team ___________________________________ Plus, included in your package is a Fairfield University basketball shirt and lunch! Shirt size (please circle) L XL 2X Please make checks payable to: Sydney Johnson, LLC Please detach application and return to: Fairfield Men’s Basketball Fairfield University Men’s Basketball Walsh Athletic Center 1073 North Benson Road Fairfield, CT 06824 COACHES For more information, please call Kyle Koncz at (203) 254-4000, ext. 2791 or e-mail kkoncz@fairfield.edu CLINIC Office Use Only Fairfield University Basketball Fairfield 1073 North Benson Road CT 06824 Fairfield, Sunday, October 28, 2012 Check# ______________________ Cash Amount _______________ Date____________ 34497_8.12 Speakers Tentative Clinic Schedule Skills Development Keynote Speaker Sunday, October 28 PETE CARRIL COACH PETE GILLEN 9 a.m. Registration Naismith Memorial Basketball Hall of Fame Fairfield University Class of 1968 Check in at Alumni Hall for pre-registered Class of 1997 coaches and registration for those who did not After serving as an assistant coach at Hawaii, VMI, pre-register. -
International Journal of Computer Science in Sport a Comprehensive
International Journal of Computer Science in Sport Volume 18, Issue 1, 2019 Journal homepage: http://iacss.org/index.php?id=30 DOI: 10.2478/ijcss-2019-0001 A comprehensive review of plus-minus ratings for evaluating individual players in team sports Lars Magnus Hvattum Faculty of Logistics, Molde University College, Molde, Norway Abstract The increasing availability of data from sports events has led to many new directions of research, and sports analytics can play a role in making better decisions both within a club and at the level of an individual player. The ability to objectively evaluate individual players in team sports is one aspect that may enable better decision making, but such evaluations are not straightforward to obtain. One class of ratings for individual players in team sports, known as plus-minus ratings, attempt to distribute credit for the performance of a team onto the players of that team. Such ratings have a long history, going back at least to the 1950s, but in recent years research on advanced versions of plus-minus ratings has increased noticeably. This paper presents a comprehensive review of contributions to plus- minus ratings in later years, pointing out some key developments and showing the richness of the mathematical models developed. One conclusion is that the literature on plus-minus ratings is quite fragmented, but that awareness of past contributions to the field should allow researchers to focus on some of the many open research questions related to the evaluation of individual players in team sports. KEYWORDS: RATING SYSTEM, RANKING, REGRESSION, REGULARIZATION IJCSS – Volume 18/2019/Issue 1 www.iacss.org Introduction Rating systems, both official and unofficial ones, exist for many different sports. -
Collegian 2006 03 06.Pdf (14.94Mb)
WATER POLO TEAM WINS NINTH GAME | PAGE 12 THE ROCKY MOUNTAIN Fort Collins, Colorado COLLEGIAN Volume 114 | No. 117 Monday, March 6, 2006 www.collegian.com THE STUDENT VOICE OF COLORADO STATE UNIVERSITY SINCE 1891 CSU looks to upgrade locks By VIMAL PATEL ties department, in an e-mail the standard lock hardware outer doors to buildings and “You couldn’t just come to The Rocky Mountain Collegian interview. costs hundreds of dollars (per high-value areas such as com- the key desk and say, ‘I want a “I know that The depart- See page 4 door),” said building services puter labs and research spaces, key,’” Sheahan said. “Someone With more than 50,000 au- ment is working to read the manager Jeff Sutton, adding Chase wrote. has to approve that you would just to change thorized keys in existence and on drawing up a Collegian’s that a recent change in locks be using it for university pur- several doors being left open proposal so com- opinion on on four doors in the Weber THE CURRENT SYSTEM poses.” the standard throughout the night leading panies could pro- this topic. Building ran about $1,300. There are various types of to a spike in the number of on- vide price quotes, There are several thousand The some 50,000 keys is- keys. lock hardware campus computer thefts, CSU Chase wrote. doors on campus, and the fa- sued go back at least 20 years, Some open just outer doors, offi cials are shopping around In cash-strapped times, ad- cilities department is respon- said facilities manager Sandy others offi ce doors and a select costs hundreds for an electronic cardkey sys- ministrators wonder whether sible for locking 107 buildings. -
Australian Basketball Statistics Association
Basketball Statistics Calling Protocol Calling Protocol – April 2009 Edition. Australian Basketball Statistics Committee AUSTRALIAN BASKETBALL STATISTICS COMMITTEE CALLING PROTOCOL APRIL 2009 EDITION 2 Calling Protocol – April 2009 Edition. Australian Basketball Statistics Committee Written by The Australian Basketball Statistics Committee The contents of this manual may not be altered or copied after alteration TABLE OF CONTENTS Calling Protocol ........................................................................................................4 Reasons for a Protocol: ................................................................................................. 4 General Principles: ........................................................................................................ 4 Calling The Action: ....................................................................................................... 5 LiveStats - SPECIFIC CALLS .................................................................................. 7 Time Outs: .................................................................................................................... 7 Substitutions: ............................................................................................................... 7 Player Checks: .............................................................................................................. 7 CALLING IN SEQUENCE ......................................................................................... 8 3 Calling Protocol -
Our Shining Moment: Hierarchical Clustering to Determine NCAA Tournament Seeding
Trunzo Scholz 1 Dan Trunzo and Libby Scholz MCS 100 June 4, 2016 Our Shining Moment: Hierarchical Clustering to Determine NCAA Tournament Seeding This project tries to correctly predict the NCAA Tournament Selection Committee’s bracket arrangement. We look both to correctly predict the 36 at large teams included in the tournament, and to seed teams in a similar way to the selection committee. The NCAA Tournament Selection Committee currently operates in secrecy, and the selection process is not transparent, either for teams or fans. If we successfully replicate the committee’s selections, our variable choices shed light on the “black box” of selection. As basketball fans ourselves, we hope to better understand which teams are in, which are out, and why Existing Selection Process 32 teams automatically qualify for the March NCAA tournament by winning their conference championship tournament. The other 36 “at large” teams are selected by the ten person committee through multiple voting rounds, where a team needs progressively fewer votes from the committee to make the tournament. Once the teams are selected, a similar process follows for seeding, where the selection committee ranks the best eight teams remaining, then the best six, and then the best four as more teams are placed in the bracket. Once all 68 teams are ranked, they are then placed in a bracket. At this point, the actual rank order may be violated to avoid “teams from the same conference… meet[ing] prior to the regional final if they played each other three or more times during the regular season and conference tournament,” or prior to the semifinals if they played at least twice. -
Data-Driven Basketball Web Application for Support in Making Decisions
Data-driven Basketball Web Application for Support in Making Decisions Tomislav Horvat1a, Ladislav Havaš1b, Dunja Srpak1c and Vladimir Medved2d 1Department of Electrical Engineering, University North, 104 Brigade 3, Varaždin, Croatia 2Department of General and Applied Kinesiology, Faculty of Kinesiology, University of Zagreb, Zagreb, Croatia Keywords: Basketball, Information System, Making Decisions, Statistics Analysis, Web Application. Abstract: Statistical analysis combined with data mining and machine learning is increasingly used in sports. This paper presents an overview of existing commercial information systems used in game analysis and describes the new and improved version of originally developed data-driven Web application / information system called Basketball Coach Assistant (later BCA) for sports statistics and analysis. The aim of BCA is to provide the essential information for decision making in training process and coaching basketball teams. Special emphasis, along with statistical analysis, is given to the player’s progress indicators and statistical analysis based on data mining methods used to define played game point’s difference classes. The results obtained by using BCA information system, presented in tables, proved to be useful in programing training process and making strategic, tactical and operational decisions. Finally, guidelines for the further information system development are given primarily for the use of data mining and machine learning methods. 1 INTRODUCTION information for decision making in training process and coaching basketball teams. The first version of Nowadays, sports statistics and analysis, more the BCA information system, called AssistantCoach, particular the information and communication was presented at the International Congress on Sport technologies are omnipresent in sport and have Sciences Research and Technology Support in Lisbon become a very important factor in making decisions (Horvat et al., 2015). -
Official Basketball Statistics Rules Basic Interpretations
Official Basketball Statistics Rules With Approved Rulings and Interpretations (Throughout this manual, Team A players have last names starting with “A” the shooter tries to control and shoot the ball in the and Team B players have last names starting with “B.”) same motion with not enough time to get into a nor- mal shooting position (squared up to the basket). Article 2. A field goal made (FGM) is credited to a play- Basic Interpretations er any time a FGA by the player results in the goal being (Indicated as “B.I.” references throughout manual.) counted or results in an awarded score of two (or three) points except when the field goal is the result of a defen- sive player tipping the ball in the offensive basket. 1. APPROVED RULING—Approved rulings (indicated as A.R.s) are designed to interpret the spirit of the applica- Related rules in the NCAA Men’s and Women’s Basketball tion of the Official Basketball Rules. A thorough under- Rules and Interpretations: standing of the rules is essential to understanding and (1) 4-33: Definition of “Goal” applying the statistics rules in this manual. (2) 4-49.2: Definition of “Penalty for Violation” (3) 4-69: Definition of “Try for Field Goal” and definition of 2. STATISTICIAN’S JOB—The statistician’s responsibility is “Act of Shooting” to judge only what has happened, not to speculate as (4) 4-73: Definition of “Violation” to what would have happened. The statistician should (5) 5-1: “Scoring” not decide who would have gotten the rebound if it had (6) 9-16: “Basket Interference and Goaltending” not been for the foul.