The increased amount of soccer data challenges performance evaluation using classical methods. Therefore, recent machine learning approaches can help address complex datasets in sports. The present study aims to determine which performance variables most strongly contribute to game outcomes in elite male soccer by using machine learning models trained under different venue conditions. Technical, tactical, and physical variables obtained from 542 matches played over two consecutive seasons were used to predict results for three venue conditions (all, home, and away). Variance Inflation Factor analysis and BorutaPy were applied before extreme gradient boost (XGBoost) modeling. Feature importance rankings and SHAP analysis were used to identify variables affecting model performance and outputs across different conditions. The models showed high accuracy on game outcome predictions, especially in the win and loss conditions (between 93.38-95.93%), while lower results in the draw (between 68.99-88.46%). The variables that most impacted the model's predictions were the Conversion rate, the Opponent's xG per goal, the Opponent's xG, and xG Conversion. The teams’ performance predictions for game outcomes differ, and draws are difficult to predict in this study's competition. The technical variables contributed the most to the models and outputs. Coaches should consider the structure and needs of their competitions while evaluating the data they possess. Future research could develop models for different tournaments, especially using time-related variables, if applicable.

This study investigates the effects of coach encouragement (CE) on the physical and technical performance of young tennis players. Twenty nationally ranked male tennis players (age: 13.6 ± 0.3 years, height: 160.9 ± 7.9 cm, body mass: 52.5 ± 7.6 kg,) participated in the present study. The physical and technical tests were conducted both with and without CE, using a randomized crossover design. Participants attended two sessions for performance assessments, undergoing a series of tests, including the hit and turn tennis test (HTTT), international tennis number test (ITN), counter-movement jump (CMJ) test, 20-m sprint tests, and the T-drill agility test. A paired t-test results demonstrated significant improvements in VO2max, CMJ height, 20-m sprint times, T-drill agility, and ITN scores under CE conditions compared to tests conducted without CE (p < 0.05). These findings suggest that CE positively influences physical and technical performances. Moreover, the effects of CE were more pronounced in long-duration exercises (HTTT and ITN), highlighting the crucial role of motivational support from coaches in the development of young athletes.

Velocity loss (VL) approach during squat exercise may increase post-activation potentiation enhancement effect on squat jump performance. If this method succeeded, then different conditions of VL should be researched before its implementation to the field. This study hypothesized that squat jump performance will be increased after different volumed VL conditions during half-squat exercise. Eighteen resistance-trained men (mean ± SD; age: 24.0±3.5 years; body mass: 78.3±5.5 kg; height: 179.3±7.0 cm; one-repetition maximum half squat: 110.8±11.9 kg) voluntarily performed squat jump under unloaded and four different VL conditions (R6: six repetitions, Ruf: repetitions until failure, VL10: velocity loss thresholds 10%, VL20: velocity loss thresholds 20%) after a set of half-squat exercises at 80% of one-repetition maximum separated by at least 72 hours. The results show that subjects demonstrated significantly better squat jump performance in VL10, VL20 and R6 conditions compared to the unloaded and Ruf conditions (p<0.05). According to these findings, if coaches and sports scientists desire to increase the post-activation potentiation enhancement effect, following heavy resistance training with a VL approach, VL10 and VL20 conditions instead of the traditional repetition method for squat jump performances are recommended.

Leg-spring hysteresis quantifies the mechanical energy dissipated within the force–length loop during ground contact and serves as a proxy for stretch-shortening cycle (SSC) efficiency. Whether international-level track-and-field athletes and club-level multi-sport athletes differ in their hysteresis responses to increasing drop height, and whether hysteresis predicts jump height, remains unclear. Forty athletes (15 international-level, 25 club-level) performed bilateral (BLJ), dominant-leg (DOM), and non-dominant-leg (NDOM) drop jumps from 0.26 m and 0.42 m. Three-dimensional kinematics (500 Hz) and ground reaction forces were used to compute leg-spring stiffness, hysteresis, and jump height. Significant group × drop-height interactions emerged for hysteresis in all three conditions (η²p = 0.647, 0.507, 0.466; p < .001): international-level athletes became increasingly negative (greater SSC enhancement) at 0.42 m, whereas club-level athletes showed positive hysteresis (net dissipation). Between-group hysteresis differences at 0.42 m were large (DOM d = −1.73; NDOM d = −1.95), and jump height was consistently higher in international-level athletes (d = 1.14–1.77). Pooled across groups, hysteresis was associated with jump height (R² = 0.44–0.60), although this estimate is inflated by caliber differences and within-group associations were moderate and condition-dependent. Leg-spring hysteresis is a mechanically meaningful and practically relevant discriminator of reactive-jumping capacity.

Amaç: Voleybolda başarılı olmak için maç analizlerinde elde edilen veriler kadar bu verilerin değerlendirilmesi için kullanılan metotların da güçlü ve geçerli sonuçlar ortaya çıkarmasının önemi büyüktür. Bu sebeple bu araştırma Türkiye Erkekler Voleybol Efeler Ligi'nde normal sezonda oynanan müsabakalarda set kazanma ve kaybetmeyi ayrıştıran teknik değişkenleri belirlemek amacı ile yapılmıştır. Gereç ve Yöntemler: Araştırmaya 2022-2023 sezonunda mücadelen eden 14 takımın normal sezonda oynadığı 169 müsabaka dâhil edilmiştir. Müsabakalara ait Türkiye Voleybol Federasyonu web sayfasından elde edilen veriler Data Volley 4.0 yazılımı ile analiz edilmiş, daha sonra yazılım dışına çıkarılıp Microsoft Excel'e aktarılmış, çalışma dâhilinde incelenen değişkenler filtrelenmiş ve verilerin analizinde kullanılacak istatistiksel metotlara uygun hale getirilmiştir. Araştırma kapsamındaki veriler diskriminant analizi ile değerlendirilmiş, bu analize dâhil edilmeyen değişkenler için bağımsız iki örneklem t-testi ile uygulanmıştır. Analizlerde anlamlılık düzeyi (p<0,05) olarak belirlenmiş ve bütün verilerin analizi için SPSS 21.0 yazılımı kullanılmıştır. Bulgular: Araştırma sonucunda diskriminant analizi ile elde edilen fonksiyonun %88,6 doğrulukla set kazanmayı, %90,4 doğrulukla da set kaybetmeyi sınıflandırdığı belirlenmiştir. Araştırmada set sonucunu anlamlı şekilde ayrıştıran değişkenler, BLOCKEDSo, WPOINTSBp, ERRORSo, WPOINTServe, LPOINTSReception ve WPOINTSBlock olarak bulunmuştur. Sonuç: Bu araştırma ile 2022-2023 Türkiye Erkekler Voleybol Efeler Ligi normal sezonunda set sonucunu en iyi ayrıştıran değişkenler belirlenmiş ve set sonuçları literatürdeki çalışmalara kıyasla yüksek doğrulukta sınıflandırılmıştır. Voleybol branşına özgü müsabaka gereksinimleri zamana ve popülasyona göre farklılık göstermektedir. Branşın ihtiyaçlarının gruba özgü belirlenebilmesi için müsabaka verilerinin güçlü istatistiksel yöntemlerle değerlendirilmesi önemlidir. Bu sebeple kazanmakaybetme arasındaki farklar zamana ve gruba göre değerlendirilirken basit karşılaştırmalar yerine daha kuvvetli ayrıştırma ve modellemeler ile analiz edilmelidir.

This study aimed to investigate how score status and playing position affect the most demanding passages (MDPs) in elite women’s football. Data from ten matches from eighteen outfield players of the Turkish Women’s National Team were collected during UEFA Nations League fixtures in the 2024–2025 seasons. Players were monitored using wearable GPS sensors, and all locomotor variables were segmented into one-minute windows to identify peak demands. The analysed variables included total distance (TD), high-speed running (HSR), sprint distance (SD), high-acceleration distance (HIAccD), high-deceleration distance (HIDecD), high metabolic power distance (HMPD), and player load (PL). Generalised Estimating Equations (GEE) were used to assess the effects of score status and playing position. Wingers (WG) showed the highest TD, HSR, and HMPD values, while centre backs covered less TD and HSR than WG. Full-backs and forwards (FW) also recorded lower TD, although FW exceeded WG in sprinting (p = 0.045, d values = 0.66 [moderate effect]). Score status influenced MDPs, with TD decreasing when the match was tied and further declining when the team was behind; similar reductions occurred in HSR, HIAccD, HIDecD, and HMPD. In conclusion, both score status and position significantly shaped peak locomotor and mechanical demands. These findings may inform individualised training, recovery programmes, and score-dependent tactical planning in elite women’s football.