{
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  "Package": "shorts",
  "Type": "Package",
  "Title": "Short Sprints",
  "Authors@R": "c(person(given = \"Mladen\",\nfamily = \"Jovanović\",\nrole = c(\"aut\", \"cre\", \"cph\"),\nemail = \"coach.mladen.jovanovic@gmail.com\",\ncomment = c(ORCID = \"0000-0002-4013-6530\"))\n)",
  "Version": "3.3.0",
  "Description": "Create short sprint acceleration-velocity (AVP) and\nforce-velocity (FVP) profiles and predict kinematic and kinetic\nvariables using the timing-gate split times, laser or radar gun\ndata, tether devices data, as well as the data provided by the\nGPS and LPS monitoring systems. The modeling method utilized in\nthis package is based on the works of Furusawa K, Hill AV,\nParkinson JL (1927) <doi: 10.1098/rspb.1927.0035>, Greene PR.\n(1986) <doi: 10.1016/0025-5564(86)90063-5>, Chelly SM, Denis C.\n(2001) <doi: 10.1097/00005768-200102000-00024>, Clark KP,\nRieger RH, Bruno RF, Stearne DJ. (2017) <doi:\n10.1519/JSC.0000000000002081>, Samozino P. (2018) <doi:\n10.1007/978-3-319-05633-3_11>, Samozino P. and Peyrot N., et al\n(2022) <doi: 10.1111/sms.14097>, Clavel, P., et al (2023) <doi:\n10.1016/j.jbiomech.2023.111602>, Jovanovic M. (2023) <doi:\n10.1080/10255842.2023.2170713>, Jovanovic M., et al (2024)\n<doi: 10.3390/s24092894>, and Jovanovic M., et al (2024) <doi:\n10.3390/s24196192>.",
  "URL": "https://mladenjovanovic.github.io/shorts/",
  "BugReports": "https://github.com/mladenjovanovic/shorts/issues",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "RoxygenNote": "7.2.3",
  "Config/testthat/edition": "3",
  "Config/pak/sysreqs": "make libicu-dev",
  "Repository": "https://mladenjovanovic.r-universe.dev",
  "Date/Publication": "2024-10-27 08:36:17 UTC",
  "RemoteUrl": "https://github.com/mladenjovanovic/shorts",
  "RemoteRef": "HEAD",
  "RemoteSha": "5f8ce5554b5aca0e857199e0eb50bf66d7089130",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-01 10:05:21 UTC",
    "User": "root"
  },
  "Author": "Mladen Jovanović [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0002-4013-6530>)",
  "Maintainer": "Mladen Jovanović <coach.mladen.jovanovic@gmail.com>",
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  "_created": "2026-06-01T10:05:21.000Z",
  "_published": "2026-06-01T10:08:41.304Z",
  "_distro": "noble",
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    "author": "Mladen Jovanović <coach.mladen.jovanovic@gmail.com>",
    "committer": "Mladen Jovanović <coach.mladen.jovanovic@gmail.com>",
    "message": "In the `model_in_situ()` function, when `velocity_threshold` is not provided (i.e., `NULL`), the finding of the peak acceleration and thus velocity threshold is applied *after* `filter_func`. This is to avoid outliers to specify `velocity_threshold`. The same `velocity_threshold` is used to train and test data sets when performing cross-validation.\n",
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    "name": "Mladen Jovanović",
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    "description": "PhD, Strength and Conditioning Coach, Performance Manage, Data Analyst",
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      "role": "Imports"
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    },
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      "package": "tidyr",
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    "description": "PhD, Strength and Conditioning Coach, Performance Manage, Data Analyst"
  },
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/shorts"
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  "_devurl": "https://github.com/mladenjovanovic/shorts",
  "_pkgdown": "https://mladenjovanovic.github.io/shorts/",
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  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "extra/shorts.html",
    "manual.pdf"
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  "_homeurl": "https://github.com/mladenjovanovic/shorts",
  "_realowner": "mladenjovanovic",
  "_cranurl": true,
  "_releases": [
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      "date": "2020-04-23"
    },
    {
      "version": "1.0.0",
      "date": "2020-05-05"
    },
    {
      "version": "1.0.1",
      "date": "2020-05-09"
    },
    {
      "version": "1.1.0",
      "date": "2020-07-28"
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    {
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      "date": "2020-09-11"
    },
    {
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      "date": "2020-10-13"
    },
    {
      "version": "1.1.3",
      "date": "2020-10-29"
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      "version": "1.1.4",
      "date": "2020-11-29"
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    {
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      "date": "2021-07-02"
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      "date": "2021-07-19"
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      "date": "2022-07-07"
    },
    {
      "version": "2.1.0",
      "date": "2022-09-26"
    },
    {
      "version": "2.3.0",
      "date": "2022-10-29"
    },
    {
      "version": "2.4.0",
      "date": "2023-03-13"
    },
    {
      "version": "2.5.0",
      "date": "2023-11-21"
    },
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      "version": "3.0.0",
      "date": "2024-01-13"
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      "date": "2024-01-21"
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    "convert_FVP",
    "create_FVP",
    "create_sprint_trace",
    "create_timing_gates_splits",
    "find_acceleration_critical_distance",
    "find_acceleration_critical_time",
    "find_optimal_distance",
    "find_peak_power_distance",
    "find_peak_power_time",
    "find_power_critical_distance",
    "find_power_critical_time",
    "find_velocity_critical_distance",
    "find_velocity_critical_time",
    "format_splits",
    "get_air_resistance",
    "model_in_situ",
    "model_laser_gun",
    "model_radar_gun",
    "model_tether",
    "model_tether_DC",
    "model_time_distance",
    "model_time_distance_DC",
    "model_time_distance_FD",
    "model_time_distance_FD_fixed",
    "model_time_distance_TC",
    "model_time_distance_TC_DC",
    "model_timing_gates",
    "model_timing_gates_DC",
    "model_timing_gates_FD",
    "model_timing_gates_FD_fixed",
    "model_timing_gates_TC",
    "model_timing_gates_TC_DC",
    "optimal_FV",
    "optimal_MSS_MAC",
    "predict_acceleration_at_distance",
    "predict_acceleration_at_time",
    "predict_acceleration_at_velocity",
    "predict_air_resistance_at_distance",
    "predict_air_resistance_at_time",
    "predict_distance_at_time",
    "predict_force_at_distance",
    "predict_force_at_time",
    "predict_force_at_velocity",
    "predict_kinematics",
    "predict_power_at_distance",
    "predict_power_at_time",
    "predict_relative_power_at_distance",
    "predict_relative_power_at_time",
    "predict_time_at_distance",
    "predict_time_at_distance_FV",
    "predict_velocity_at_distance",
    "predict_velocity_at_time",
    "predict_work_till_distance",
    "predict_work_till_time",
    "probe_FV",
    "probe_MSS_MAC"
  ],
  "_datasets": [
    {
      "name": "dynaspeed",
      "title": "DynaSpeed Single Sprint Data",
      "object": "dynaspeed",
      "class": [
        "data.frame"
      ],
      "fields": [
        "time",
        "distance",
        "velocity",
        "raw_velocity"
      ],
      "rows": 7251,
      "table": true,
      "tojson": true
    },
    {
      "name": "jb_morin",
      "title": "JB Morin Sample Dataset",
      "object": "jb_morin",
      "class": [
        "data.frame"
      ],
      "fields": [
        "time",
        "velocity"
      ],
      "rows": 232,
      "table": true,
      "tojson": true
    },
    {
      "name": "laser_gun_data",
      "title": "Laser Gun Data",
      "object": "laser_gun_data",
      "class": [
        "data.frame"
      ],
      "fields": [
        "time",
        "distance",
        "velocity",
        "raw_velocity",
        "raw_acceleration",
        "butter_acceleration"
      ],
      "rows": 4805,
      "table": true,
      "tojson": true
    },
    {
      "name": "LPS_session",
      "title": "LPS Basketball Session Dataset",
      "object": "LPS_session",
      "class": [
        "data.frame"
      ],
      "fields": [
        "time",
        "x",
        "y",
        "velocity",
        "acceleration"
      ],
      "rows": 91099,
      "table": true,
      "tojson": true
    },
    {
      "name": "radar_gun_data",
      "title": "Radar Gun Data",
      "object": "radar_gun_data",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "athlete",
        "bodyweight",
        "time",
        "velocity"
      ],
      "rows": 3000,
      "table": true,
      "tojson": true
    },
    {
      "name": "split_times",
      "title": "Split Testing Data",
      "object": "split_times",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "athlete",
        "bodyweight",
        "distance",
        "time"
      ],
      "rows": 30,
      "table": true,
      "tojson": true
    },
    {
      "name": "vescovi",
      "title": "Vescovi Timing Gates Sprint Times",
      "object": "vescovi",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "Team",
        "Surface",
        "Athlete",
        "Age",
        "Height",
        "Bodyweight",
        "BMI",
        "BSA",
        "5m",
        "10m",
        "20m",
        "30m",
        "35m",
        "10m-5m split",
        "20m-10m split",
        "30m-20m split",
        "35m-30m split"
      ],
      "rows": 52,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "coef.shorts_model",
      "title": "S3 method for extracting model parameters from 'shorts_model' object",
      "topics": [
        "coef.shorts_model"
      ]
    },
    {
      "page": "confint.shorts_model",
      "title": "S3 method for providing confidence intervals for the 'shorts_model'",
      "topics": [
        "confint.shorts_model"
      ]
    },
    {
      "page": "convert_FVP",
      "title": "Convert Force-Velocity profile back to Acceleration-Velocity profile",
      "topics": [
        "convert_FVP"
      ]
    },
    {
      "page": "create_FVP",
      "title": "Create Force-Velocity Profile",
      "topics": [
        "create_FVP"
      ]
    },
    {
      "page": "create_sprint_trace",
      "title": "Create Sprint Trace",
      "topics": [
        "create_sprint_trace"
      ]
    },
    {
      "page": "create_timing_gates_splits",
      "title": "Create Timing Gates Splits",
      "topics": [
        "create_timing_gates_splits"
      ]
    },
    {
      "page": "dynaspeed",
      "title": "DynaSpeed Single Sprint Data",
      "topics": [
        "dynaspeed"
      ]
    },
    {
      "page": "find_functions",
      "title": "Find functions",
      "topics": [
        "find_acceleration_critical_distance",
        "find_acceleration_critical_time",
        "find_functions",
        "find_peak_power_distance",
        "find_peak_power_time",
        "find_power_critical_distance",
        "find_power_critical_time",
        "find_velocity_critical_distance",
        "find_velocity_critical_time"
      ]
    },
    {
      "page": "find_optimal_distance",
      "title": "Function that finds the distance at which the sprint, probe, or FV profile is optimal (i.e., equal to 100 perc)",
      "topics": [
        "find_optimal_distance"
      ]
    },
    {
      "page": "fitted.shorts_model",
      "title": "S3 method for returning predictions of 'shorts_model'",
      "topics": [
        "fitted.shorts_model"
      ]
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      "page": "format_splits",
      "title": "Format Split Data",
      "topics": [
        "format_splits"
      ]
    },
    {
      "page": "get_air_resistance",
      "title": "Get Air Resistance",
      "topics": [
        "get_air_resistance"
      ]
    },
    {
      "page": "jb_morin",
      "title": "JB Morin Sample Dataset",
      "topics": [
        "jb_morin"
      ]
    },
    {
      "page": "laser_gun_data",
      "title": "Laser Gun Data",
      "topics": [
        "laser_gun_data"
      ]
    },
    {
      "page": "LPS_session",
      "title": "LPS Basketball Session Dataset",
      "topics": [
        "LPS_session"
      ]
    },
    {
      "page": "model_functions",
      "title": "Model functions",
      "topics": [
        "model_functions",
        "model_in_situ",
        "model_laser_gun",
        "model_radar_gun",
        "model_tether",
        "model_tether_DC",
        "model_time_distance",
        "model_time_distance_DC",
        "model_time_distance_FD",
        "model_time_distance_FD_fixed",
        "model_time_distance_TC",
        "model_time_distance_TC_DC",
        "model_timing_gates",
        "model_timing_gates_DC",
        "model_timing_gates_FD",
        "model_timing_gates_FD_fixed",
        "model_timing_gates_TC",
        "model_timing_gates_TC_DC"
      ]
    },
    {
      "page": "optimal_functions",
      "title": "Optimal profile functions",
      "topics": [
        "optimal_functions",
        "optimal_FV",
        "optimal_MSS_MAC"
      ]
    },
    {
      "page": "plot.shorts_model",
      "title": "S3 method for plotting 'shorts_model' object",
      "topics": [
        "plot.shorts_model"
      ]
    },
    {
      "page": "predict_kinematics",
      "title": "Kinematics prediction functions",
      "topics": [
        "predict_acceleration_at_distance",
        "predict_acceleration_at_time",
        "predict_acceleration_at_velocity",
        "predict_air_resistance_at_distance",
        "predict_air_resistance_at_time",
        "predict_distance_at_time",
        "predict_force_at_distance",
        "predict_force_at_time",
        "predict_force_at_velocity",
        "predict_kinematics",
        "predict_power_at_distance",
        "predict_power_at_time",
        "predict_relative_power_at_distance",
        "predict_relative_power_at_time",
        "predict_time_at_distance",
        "predict_time_at_distance_FV",
        "predict_velocity_at_distance",
        "predict_velocity_at_time",
        "predict_work_till_distance",
        "predict_work_till_time"
      ]
    },
    {
      "page": "predict.shorts_model",
      "title": "S3 method for making predictions using 'shorts_model'",
      "topics": [
        "predict.shorts_model"
      ]
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      "page": "print.shorts_model",
      "title": "S3 method for printing 'shorts_model' object",
      "topics": [
        "print.shorts_model"
      ]
    },
    {
      "page": "probe_functions",
      "title": "Probe profile functions",
      "topics": [
        "probe_functions",
        "probe_FV",
        "probe_MSS_MAC"
      ]
    },
    {
      "page": "radar_gun_data",
      "title": "Radar Gun Data",
      "topics": [
        "radar_gun_data"
      ]
    },
    {
      "page": "residuals.shorts_model",
      "title": "S3 method for returning residuals of 'shorts_model'",
      "topics": [
        "residuals.shorts_model"
      ]
    },
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      "page": "split_times",
      "title": "Split Testing Data",
      "topics": [
        "split_times"
      ]
    },
    {
      "page": "summary.shorts_model",
      "title": "S3 method for providing summary for the 'shorts_model' object",
      "topics": [
        "summary.shorts_model"
      ]
    },
    {
      "page": "vescovi",
      "title": "Vescovi Timing Gates Sprint Times",
      "topics": [
        "vescovi"
      ]
    }
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