<![CDATA[Learning the 50 meter sprint in Physical Education, Sports, and Health (PJOK) at the elementary school level is still predominantly monotonous, which has resulted in low student learning outcomes. This study aims to examine the effectiveness of deep learning based traditional games, the differences between this approach and conventional learning, and the magnitude of improvement in the learning outcomes of fifth-grade students. The study employed a Pretest–Posttest Control Group Design, involving an experimental class of 32 students and a control class of 30 students. The research instruments consisted of cognitive tests, affective questionnaires, and a 50 meter sprint performance test, with data analyzed using the SPSS program. The results indicate that deep learning based traditional games are effective and significantly improve 50 meter sprint learning outcomes, as shown by a significance value of 0.000 (p < 0.05). The improvement in the experimental group was higher than in the control group, with an N-Gain percentage of 67.87% (moderate to high category), while the control group achieved only 26.00% (low category). These findings confirm that deep learning based traditional games are more effective than conventional learning. The implications of this study highlight the importance of PJOK teachers integrating traditional games as a contextual and meaningful alternative learning strategy to enhance student motivation, active engagement, and the overall quality of learning experiences. Keywords: 50 Meter Sprint, Deep Learning, Traditional Games]]>
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