Game-related statistics that discriminate winning from losing in NCAA Division-I men's basketball

被引:0
|
作者
Cabarkapa, Dimitrije [1 ]
Cabarkapa, Damjana V. [1 ]
Fry, Andrew C. [1 ]
机构
[1] Univ Kansas, Jayhawk Athlet Performance Lab, Wu Tsai Human Performance Alliance, Dept Hlth Sport & Exercise Sci, Lawrence, KS 66045 USA
来源
关键词
sport; performance; analysis; shooting; rebounding; assists; turnovers; PERFORMANCE; SEASON; TEAMS; INDICATORS; ACB;
D O I
10.3389/fspor.2024.1387918
中图分类号
G8 [体育];
学科分类号
04 ; 0403 ;
摘要
The purpose of the present study was to examine differences in game-related statistics between winning and losing game outcomes and determine which performance parameters have the greatest impact in classifying winning from losing game outcomes at the National Collegiate Athletic Association (NCAA) Division-I men's basketball level of competition. The data scraping technique was used to obtain publicly available data over a 2018-2019 season span. The total number of games examined was 5,147. Independent t-tests were used to examine statistically significant differences between winning and losing game outcomes, while a full model discriminant function analysis was used to determine the relative contribution of each game-related statistic and its ability to classify winning from losing game outcomes (p < 0.05). Alongside scoring a greater number of points at the end of the game, the findings of the present study indicate that winning teams: (a) attempted and made more field goals, three-point, and free-throw shots, (b) accumulated more defensive and total rebounds, assists, steals, and blocks, (c) had fewer turnovers and personal fouls, and (d) secured greater field goal, three-point, and free-throw shooting percentage. Moreover, the top three performance parameters discriminating winning from losing game outcomes were field goal percentage, defensive rebounds, and assists, accounting for 16.8%, 12.2%, and 12.0% of the total percentage of explained variance, respectively (i.e., 41.0% combined). Overall, these findings support the expected roles of offensive and defensive game-related statistics and provide further insight into how they work together to optimize the chances of securing the desired game outcome.
引用
收藏
页数:6
相关论文
共 33 条
  • [1] Investigating the game-related statistics and tactical profile in NCAA division I men's basketball games
    Conte, Daniele
    Tessitore, Antonio
    Gjullin, Aaron
    Mackinnon, Dominik
    Lupo, Corrado
    Favero, Terence
    [J]. BIOLOGY OF SPORT, 2018, 35 (02) : 137 - 143
  • [2] Differences in game-related statistics of basketball performance by game location for men's winning and losing teams
    Gomez, Miguel A.
    Lorenzo, Alberto
    Barakat, Ruben
    Ortega, Enrique
    Palao, Jose M.
    [J]. PERCEPTUAL AND MOTOR SKILLS, 2008, 106 (01) : 43 - 50
  • [3] Game-related statistics that discriminated winning and losing teams from the Spanish men's professional basketball teams
    Angel Gomez, Miguel
    Lorenzo, Alberto
    Sampaio, Jaime
    Jose Ibanez, Sergio
    Ortega, Enrique
    [J]. COLLEGIUM ANTROPOLOGICUM, 2008, 32 (02) : 451 - 456
  • [4] Differences in game-related statistics between winning and losing teams in women's basketball
    Gomez, M. A.
    Lorenzo, A.
    Sampaio, J.
    Ibanez, S. J.
    [J]. JOURNAL OF HUMAN MOVEMENT STUDIES, 2006, 51 (05): : 357 - 369
  • [5] Game-Related Statistics Discriminate between Winning and Losing Teams in the Field Hockey
    Bagchi, Amritashish
    Singh, Shailesh
    Raizada, Shiny
    Reddy, Anurag
    Nimkar, Nayana
    [J]. ANNALS OF APPLIED SPORT SCIENCE, 2023, 11
  • [6] Effects of consecutive basketball games on the game-related statistics that discriminate winner and losing teams
    Ibanez, Sergio J.
    Garcia-Rubio, Javier
    Feu, Sebastian
    Lorenzo, Alberto
    Sampaio, Jaime
    [J]. JOURNAL OF SPORTS SCIENCE AND MEDICINE, 2009, 8 (03) : 458 - 462
  • [7] The home-court advantage in NCAA Division-I men's basketball
    Cabarkapa, Dimitrije
    Deane, Michael A.
    Ciccone, Anthony B.
    Jones, Grant T.
    Cabarkapa, Damjana V.
    Fry, Andrew C.
    [J]. JOURNAL OF HUMAN SPORT AND EXERCISE, 2023, 18 (02): : 420 - 427
  • [8] Game statistics that discriminate winning and losing at the NBA level of basketball competition
    Cabarkapa, Dimitrije
    Deane, Michael A.
    Fry, Andrew C.
    Jones, Grant T.
    Cabarkapa, Damjana, V
    Philipp, Nicolas M.
    Yu, Daniel
    [J]. PLOS ONE, 2022, 17 (08):
  • [9] Rugby game-related statistics that discriminate between winning and losing teams in IRB and Super twelve close games
    Vaz, Luis
    Van Rooyen, Michele
    Sampaio, Jaime
    [J]. JOURNAL OF SPORTS SCIENCE AND MEDICINE, 2010, 9 (01) : 51 - 55
  • [10] Modeling the winning seed distribution of the NCAA Division I men's basketball tournament
    Khatibi, Arash
    King, Douglas M.
    Jacobson, Sheldon H.
    [J]. OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2015, 50 : 141 - 148