Purpose: We intended to determine predictor variables of anthropometry and training for Marathon race time in recreational female runners in order to predict Marathon race time for future novice female runners.Methods: Anthropometric characteristics such as body mass, body height, body mass index, circumferences of limbs, thicknesses of skin-folds and body fat as well as training variables such as volume and speed in running training were related to Marathon race time using bi- and multi-variate analysis in 29 female runners.Results: The Marathoners completed the Marathon distance within 251 (26) min, running at a speed of 10.2 (1.1) km/h. Body mass (r=0.37), body mass index (r=0.46), the circumferences of thigh (r=0.51) and calf (r=0.41), the skin-fold thicknesses of front thigh (r=0.38) and of medial calf (r=0.40), the sum of eight skin-folds (r=0.44) and body fat percentage (r=0.41) were related to Marathon race time. For the variables of training, maximal distance ran per week (r=-0.38), number of running training sessions per week (r=-0.46) and the speed of the training sessions (r=-0.60) were related to Marathon race time. In the multi-variate analysis, the circumference of calf (P=0.02) and the speed of the training sessions (P=0.0014) were related to Marathon race time. Marathon race time might be partially (r2=0.50) predicted by the following equation: Race time (min) =184.4+5.0 x (circumference calf, cm) –11.9 x (speed in running during training, km/h) for recreational female Marathoners.Conclusions: Variables of both anthropometry and training were related to Marathon race time in recreational female Marathoners and cannot be reduced to one single predictor variable. For practical applications, a low circumference of calf and a high running speed in training are associated with a fast Marathon race time in recreational female runners.

Previous research has indicated that sex, age and performance level of finishers influence pacing strategies in the Marathon. However, the variation of pacing by country of origin and/or nationality of finishers has not been studied. The aim of this study, therefore, was to examine whether runners with different nationality differ in their pacing strategies. Data (women, n = 117, 595; men, n = 180, 487) from the ‘ New York City Marathon’ between 2006 and 2016 were analysed. A small main effect of nationality on age was shown (P < 0. 001,  2 = 0. 032) with Ethiopians being the youngest (30. 2 8. 4 years) and Japanese the oldest (45. 1 10. 9 years). A trivial main effect of nationality on race time was shown (P < 0. 001,  2 = 0. 008) with Ethiopians (2: 49: 24  0: 49: 17 h: min: s) and Kenyans (3: 08: 34  1: 05: 46 h: min: s) being the fastest and Japanese the slowest (4: 30: 43  0: 54: 37 h: min: s). A trivial split  nationality interaction on race speed was observed in women (P < 0. 001,  2 = 0. 004) and men (P < 0. 001,  2 = 0. 005) with Ethiopians and Kenyans showing more even pacing strategies than the other nationalities (P < 0. 001,  2 = 0. 003; P < 0. 001,  2 = 0. 004, respectively). Accordingly, the largest prevalence of end spurt (women,  2 = 646. 2, P < 0. 001, '= 0. 074; men,  2 = 1163. 2, P < 0. 001, '= 0. 080) was found in U. S.-Americans in women (87. 2%) and men (78. 2%), whereas the smallest was in Ethiopians (54. 3%) and Kenyans (45. 8%), respectively. Based on these findings, it was concluded that nationality plays a role on Marathon runners’ pacing, which might be attributed to differences in performance level among nationalities and running tactics.