College application research evidence · understanding and original contribution · Seoul and online
Project courseThe student keeps the work and the record they made.
Player Tracking Data: Analyze Movement and Team Tactics
Grades 9-12: team shape on the pitch, defensive line...
- Free consultation and level check
- Apgujeong classroom or online
- One-to-one or small group
- Registered academy no. 11882
Is Player Tracking Data: Analyze Movement and Team Tactics a good fit for high school students in Grades 9-12?
Player Tracking Data: Analyze Movement and Team Tactics is a good fit for students in grades 9-12 who are interested in team shape on the pitch and defensive line height. CIT offers online or in-person lessons in Apgujeong, Gangnam, Seoul, in one-to-one or small-group formats. Students make a tracking-data quality table, team-shape graphs after lost possession, and a Streamlit tactics app with a report.
Students choose one of ten public SkillCorner matches and a single tactical question, read player, team, and ball positions frame by frame, and check for missing frames and position jumps before analyzing anything. They calculate team centroid, width, length, player spacing, and defensive line height, and compare how team shape changes in the five seconds after the ball is lost. A tactical metric of the student's own design is tested against high, low, and counterexample scenes, then built into a Streamlit app with a time slider for comparing scenes. The student sets their own question, then designs and tests a feature, model, interface, or solution of their own. In an application or interview, the student separates the material they drew on from their own decisions, results, failed attempts, revisions, and limits.
Google sign-in is required. Existing account permissions determine access.
My child found the AI classes interesting and stayed with them. It made for a worthwhile school break. Thank you for teaching so attentively.
- Age group
- Grades 9-12
- Academic subject
- AI & DataBrowse subject
- Course type
- Course
- Format
- Online or Apgujeong in person · one-to-one or small group
- Teaching language
- Korean by default, with complete English materials
- Curriculum status
- Lesson-readyEvery learning item includes the evidence, worked example, practical work, and tutor guidance required by CIT's lesson-ready standard.
From open research to student-owned work
Students inspect a relevant public source, reproduce the idea, then add an original question, feature, or test. Every source is public, and each lesson names the exact page it opens.
How can I explain this course to my child?
If questions about team shape on the pitch or defensive line height keep making you ask why, Player Tracking Data: Analyze Movement and Team Tactics lets you investigate the question with evidence, then build and defend an extension of your own.
Which interests suggest this course?
- team shape on the pitch
- defensive line height
- the seconds after losing the ball
What does the student finish?A tracking-data quality table, team-shape graphs after lost possession, and a Streamlit tactics app with a report.
Is this a good fit?
A strong fit for students who want to understand, build, test, or responsibly use AI systems.
Course placement follows current subject and coding readiness.
Students should be ready to document sources, methods, and limits.
Advanced tools are introduced after a clear baseline.
What will my child learn?
- Before any analysis, check frame gaps, coordinate ranges, and vanishing IDs, and record data quality in a table.
- Calculate team centroid, width, length, spacing, and defensive line height, and explain them in football terms.
- Smooth small position jitter before computing speed and compare results before and after each cleaning rule.
- Test a self-designed tactical metric on high-value, low-value, and counterexample scenes.
How does the course progress?
- 1Tracking Data and Time
Read player, team, and ball coordinates for each frame and find missing data and ID mismatches first.
- 2Movement and Team Shape on the Pitch
Replay player movement as an animation and compute team centroid, width, length, and the defensive line from coordinates.
- 3Error Cleanup and Tactical Scenes
Flag impossible speeds, link phases of play and events to frames, and compare the five seconds after losing the ball.
- 4Tactical Metric Web App
Check the metric's distribution and key scenes, then finish a scene-selection web app, result CSV, and GitHub report.
What counts as useful evidence?
A tracking-data quality table, team-shape graphs after lost possession, and a Streamlit tactics app with a report.
What should an admissions reader be able to see?
The student sets their own question, then designs and tests a feature, model, interface, or solution of their own. In an application or interview, the student separates the material they drew on from their own decisions, results, failed attempts, revisions, and limits.
Useful evidence may include a documented dataset, baseline comparison, model evaluation, error analysis, and a clear record of the student's own decisions.
The evidence an application reads is what the student understood, completed, and can explain.
The real research project this course reads
- SkillCorner/opendata
- pinned commit
c1e17a0cc3e0 - licence MIT
- text files 88
The student folds match tracking data on their own terms and sees how the choice of what to count changes the answer. In class the project is separated into five boxes (input, memory, process, output, control). The lesson opens one of them, changes one value, and leaves the rest closed.
- InputWhat comes in?
The per-frame coordinate file that arrives for each match, and the match information file
- MemoryWhat persists?
Player positions frame by frame, and the record that cuts the match into phases
- Processopened hereWhat transforms?
Reading the coordinates and folding them into values like team centre, width and length
- OutputWhat leaves, and who uses it?
The tables and charts that put players and teams side by side
- ControlWhat decides when anything runs?
The notebook that decides which match and which stretch gets read again, and when
The files the lesson opens, by name. The course is not a walk through the repository; it opens a chosen few and says which.
One value moves and everything else stays. The right-hand column is the prediction written before the run, not a result; the work is reconciling the two.
On a narrow screen, swipe the picture sideways.
The universities and labs named here made the open projects this course reads. CIT designed the course independently; it is not an official, affiliated, or endorsed course.
Which sources were reviewed?
Catalog reviewed: 2026-09-30
Questions parents search before choosing this course
Is Player Tracking Data: Analyze Movement and Team Tactics a good fit for high school students in Grades 9-12?
Player Tracking Data: Analyze Movement and Team Tactics is a good fit for students in grades 9-12 who are interested in team shape on the pitch and defensive line height. CIT offers online or in-person lessons in Apgujeong, Gangnam, Seoul, in one-to-one or small-group formats. Students make a tracking-data quality table, team-shape graphs after lost possession, and a Streamlit tactics app with a report.
Can my child take Player Tracking Data: Analyze Movement and Team Tactics online or in person, one-to-one or in a small group?
Yes. CIT offers online and in-person lessons at its Apgujeong academy in Gangnam, Seoul, with one-to-one and small-group options. A readiness consultation confirms the available format and starting point for the course.
Does my child need prior subject knowledge or coding experience for Player Tracking Data: Analyze Movement and Team Tactics?
Course placement follows current subject and coding readiness. Students should be ready to document sources, methods, and limits. Advanced tools are introduced after a clear baseline.
What will my child make or practice in Player Tracking Data: Analyze Movement and Team Tactics?
The main evidence is a tracking-data quality table, team-shape graphs after lost possession, and a Streamlit tactics app with a report. Students also document decisions, tests, feedback, and limits in age-appropriate language.
How can a student describe work from Player Tracking Data: Analyze Movement and Team Tactics in a college application?
The student sets their own question, then designs and tests a feature, model, interface, or solution of their own. In an application or interview, the student separates the material they drew on from their own decisions, results, failed attempts, revisions, and limits. Useful evidence may include a documented dataset, baseline comparison, model evaluation, error analysis, and a clear record of the student's own decisions.
How are the schedule and tuition for Player Tracking Data: Analyze Movement and Team Tactics determined?
CIT confirms the student's readiness, goal, location, class size, and current availability before recommending a course plan. The consultation and level check are free; tuition is explained before enrollment.
When should a student start?
There is no fixed intake month. CIT reviews the student's current school term, readiness, and available hours, then names the point in the course where they should begin.
I appreciated that a simple early idea was extended into an 'AI debate tool'. My child has always been interested in debate and social issues, so seeing that interest connect to the project makes me expect a more complete and distinctive result.
Where else parents check CIT
Choose the course after a readiness check
CIT can compare this course with nearby options by age, subject, and current preparation.