A technical and tactical assessment of lineouts in National 2 SE Rugby Union: Can successful lineout performances be predicted?

The lineout is one of rugby union's most decisive set pieces, frequently shaping both possession and scoring opportunities, yet research into its technical determinants remains limited. This study was conducted to identify key variables (pitch location, match time, how stolen, catch type, weather, pitch type, rep time, lineout numbers, lineout formation, plus one, dummies & switches, dummies & switches type, hooker, throw location, throw type, delivery type, calling language, tempo, defence jump, defence jump location) that influence the lineout in terms of success in a semi-professional league combining performance analysis frameworks with coach-driven insight. A mixed methods approach was utilised, involving qualitative insights from five experienced coaches that went on to inform the process of building a tagging panel on Dartfish (Dartfish 2024, Dartfish, Fribourg, Switzerland). The panel and Dartfish video analysis software was then used to process 660 lineouts from the 2024/25 National 2 South East League using footage taken from the 26 games played by Tonbridge Juddians RFC. Categorical values were converted into nominal values and descriptive statistics (counts and percentages). The data were then imported into SPSS (IBM SPSS software, Chicago, IL) for multinomial logistic regressions to be performed in order to examine associations between each variable and outcome category (won, won-scrappy, loss). Model fit and predictive power were assessed using chi-squared statistics, Nagelkerke pseudo-R2 and standard regression outputs including B coefficients, odds ratios, standard errors, Wald statistics and 95% confidence intervals. Results demonstrated that lineouts involving 6-8 players increased odds of success when compared to formations including 3-5 players (OR = 1.94, 95% CI [1.21-3.10], p = .006). The inclusion of a "plus one" significantly improved outcomes (OR = 1.68, 95% CI [1.12-2.51], p = .014) while front throw locations were also favourable (OR = 1.73, 95% CI [1.05-2.85], p = .031). In contrast, the presence of a defensive jump reduced the likelihood of winning clean possession (OR = 0.56, 95% CI [0.37-0.84], p .005). External variables such as weather, pitch type, and time in match were all non-significant (p >.05). These findings highlight the tactical advantages of larger formations, strategies involving plus-ones and throws to the front, while confirming the disruptive influence of defensive contesting. Despite limitations relating to categorical sparsity due to a wide set of variables and single league sampling, this study offers a comprehensive quantitative evaluation of lineout performance, providing practical insights for coaches and validated framework for future research.