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  1. 1

    Augmented intelligence for FIFA predictions

    Jethuri, K., Emmadi, S. C., Samudrala, S., Natarajan, J., Ghotkar, P., Natu, M.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2024. Communications in Computer and Information Science (2025)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  2. 2

    Mathematical models for off-ball scoring prediction in basketball

    Kono, R., Fujii, K.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2024. Communications in Computer and Information Science (2025)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  3. 3

    GraphEIV: A framework for estimating the expected immediate value in basketball using graph neural networks

    Sá-Freire, B. M., Barbosa, G. R. G., Gonçalves, J. L. L., Schuster, J., Rios-Neto, H.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2024. Communications in Computer and Information Science (2025)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  4. 4

    Characterizing serves in table tennis

    Eradès, A., Papon, T., Vuillemot, R.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2024. Communications in Computer and Information Science (2025)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  5. 5

    Identifying player roles in ice hockey

    Säfvenberg, R., Carlsson, N., Lambrix, P.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2023. Communications in Computer and Information Science (2024)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  6. 6

    Elite rugby league players` signature movement patterns and position prediction

    Adeyemo, V. E., Palczewska, A., Jones, B., Weaving, D.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2023. Communications in Computer and Information Science (2024)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  7. 7

    Boat speed prediction in SailGP

    Zentai, B., Toka, L.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2023. Communications in Computer and Information Science (2024)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  8. 8

    Masked autoencoder pretraining for event classification in elite soccer

    Rudolph, Y., Brefeld, U.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2023. Communications in Computer and Information Science (2024)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  9. 9

    Pass receiver and outcome prediction in soccer using temporal graph networks

    Rahimian, P., Kim, H., Schmid, M., Toka, L.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2023. Communications in Computer and Information Science (2024)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  10. 10

    Field depth matters: Comparing the valuation of passes in football

    de Sá-Freire, L. M., Vaz-de-Melo, P. O. S.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2023. Communications in Computer and Information Science (2024)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  11. 11

    Momentum matters: Investigating high-pressure situations in the NBA through scoring probability

    Mihalyi, B., Biczók, G., Toka, L.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2023. Communications in Computer and Information Science (2024)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  12. 12

    The big three: A practical framework for designing decision support systems in sports and an application for basketball

    Bautiste, F. J. S., Brunner, D., Koch, J., Laborie, T., Yang, L., El-Assady, M.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2023. Communications in Computer and Information Science (2024)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  13. 13

    What data should be collected for a good handball expected goal model?

    Mortelier, A., Rioult, F., Komar, J.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2023. Communications in Computer and Information Science (2023)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  14. 14

    Towards expected counter - using comprehensible features to predict counterattacks

    Biermann, H., Wieland, F. G., Timmer, J., Memmert, D., Phatak, A.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2022. Communications in Computer and Information Science (2022)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  15. 15

    Shot analysis in different levels of German football using expected goals

    Raudonius, L., Seidl, T.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2022. Communications in Computer and Information Science (2022)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  16. 16

    Analyzing passing sequences for the prediction of goal-scoring opportunities

    McCarthy, C., Tampakis, P., Chiarandini, M., Randers, M. B., Jänicke, S., Zimek, A.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2022. Communications in Computer and Information Science (2022)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  17. 17

    Let's penetrate the defense: a machine learning model for prediction and valuation of penetrative passes

    Rahimian, P., da Silva Guerra Gomes, D. G., Berkovics, F., Toka, L.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2022. Communications in Computer and Information Science (2022)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  18. 18

    Evaluation of creating scoring opportunities for teammates in soccer via trajectory prediction

    Teranishi, M., Tsutsui, K., Takeda, K., Fujii, K.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2022. Communications in Computer and Information Science (2022)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  19. 19

    Cost-efficient and bias-robust sports player tracking by integrating GPS and video

    Kim, H., Kim, C. J., Jeong, M., Lee, J., Yoon, J., Ko, S. K.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2022. Communications in Computer and Information Science (2022)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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  20. 20

    Predicting tennis serve directions with machine learning

    Zhu, Y., Naikar, R.
    Published in Machine Learning and Data Mining for Sports Analytics. MLSA 2022. Communications in Computer and Information Science (2022)
    Collective title: “…Machine Learning and Data Mining for Sports Analytics. …”
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