Introduction to Sports Performance Analysis and Notational Techniques

Workshop Logistics and Course Introduction

  • Course Personnel and Communication

    • Lecturer: Pete (working at UC for 10 years). Background includes a Bachelor of Commerce (BCom), a Master’s in Sport Management, and industry experience.

    • Tutors: Dom (tutor and part-time employee with the Tactics) and Troy.

    • Office Location: Located on the 200 level.

    • Contact: Email and phone number are provided for students. General rule: do not call late at night; texting is preferred for urgent matters.

  • Computer Lab Access

    • Availability: The lab is accessible 24/7.

    • Entry Requirements: Students must use their student ID card to swipe in. If access is required after 05:00 PM, a PIN is necessary. This PIN is established during student ID setup and is the same as the library PIN.

    • Security: If access issues occur, students should visit UC Security on Island Road.

  • Workshop Reports and Grading

    • Frequency: There will be 9 workshops in total. No reports are required in Week 6 and Week 12 (scheduled breaks) or Week 11 (due to presentations).

    • Grading Weight: Each report is worth approximately 1.25%1.25\%. Successfully completing 8 out of 9 reports equates to 10%10\% of the total course grade.

    • Structure: Reports are one-page, open-book summaries of what was learned during the session, facilitating active recall through writing.

Networking and Career Development

  • Industry Connections

    • Performance analysis is highlighted as a rapidly evolving field. Pete emphasizes the importance of networking (e.g., student Mitch became a team manager after an internship when the previous manager tore an Achilles; Sam Start, a Year 4 teaching student, is an assistant coach).

    • UC Success Stories: Three UC players have played for New Zealand in 3x3 basketball (e.g., Aiden Tonj).

  • Professional Mindset

    • Students are encouraged to develop high Emotional Intelligence (EQ), adaptability, and relatability.

    • The goal is for students to "dream big," aiming for roles in national programs or Olympic-level competition (e.g., New Zealand’s 3x3 Basketball targeting Olympic and Commonwealth Games).

The Five Core Pillars of Performance Analysis

Performance analysis in sport is generally categorized into five fundamental dimensions:

  • 1. Technique Analysis

    • Focuses on the biomechanical execution of specific skills.

    • Example (Hockey): Analyzing the "hitting" technique. Evaluative questions include: Where is the stick positioned? Where is the head? Are the legs properly aligned? Is the player facing the target?

  • 2. Effectiveness Analysis

    • Measures the success rate of actions, often using binary or ordinal scales.

    • Binary Example: Shots on target vs. shots off target in football.

    • Ordinal Example (Rugby Tackles):

      • Dominant: Pushing the opponent backward.

      • Neutral: Bringing the player down on the spot.

      • Passive: Moving backward while making the tackle.

    • Calculation: Can be expressed as a simple success percentage (e.g., 50%50\% success rate).

  • 3. Tactical Analysis

    • Examines the execution of pre-determined strategies and decision-making frameworks.

    • Example (Hockey): The "press." Analyzing when it is used, where on the field it occurs (left vs. right), and whether the team is executing the predetermined plan.

  • 4. Movement Analysis

    • Focuses on the physiological and spatial demands on an athlete.

    • Technology: Primarily utilizes GPS units and heart rate monitors.

    • Metrics Captured: Meters gained, total speed, speed bands (e.g., number of sprints over 25km/h25\,km/h), and impacts.

  • 5. Decision-Making Analysis

    • Evaluates the choices made by athletes in real-time game situations.

    • Impact: Impacting a player’s decision-making is considered the pinnacle of high-level performance analysis.

Specialized Fields within Performance Analysis

  • Physiology

    • Analyzes physiological demands and workload.

    • Work Rate: The analyst tracks how much work athletes do to inform training and recovery.

    • Recovery Protocols (Crusaders Example): The Crusaders rugby team implemented a recovery points system where players must earn 1,5001,500 points before training again (e.g., eating a banana = 200200 points; hot/cold therapy = 400400 points).

  • Biomechanics

    • Uses technology to record and analyze movement angles and technical flaws, often comparing good shots vs. bad shots side-by-side.

  • Notational Analysis

    • The fundamental practice of recording events manually using pen and paper.

    • Frequency Tables: Tallies of events (e.g., lineouts won/lost/crooked). Useful for calculating ratios and percentages but lacks chronological detail.

    • Scatter/Field Diagrams: Visual plotting of events on a diagram of the field/court. Provides location data and is easy for coaches to digest.

    • Cricket Example: The "Wagon Wheel" tracks where a batsman hits the ball to identify strengths and weaknesses.

  • Video-Based Analysis and External Providers

    • Software: Hudl and SportsCode are the industry standards. SportsCode is notably Mac-exclusive.

    • External Providers: Teams may pay for 50-page reports from third-party firms to supplement their internal data.

Key Measurement Principles

To ensure data is useful for a coach or athlete, it must meet specific criteria:

  • Definitions: Analysts must explicitly define what constitutes a specific action (e.g., what exactly is a "shot on target"?) so everyone is on the same page.

  • Objective vs. Subjective:

    • Objective: Factual, such as "ball in vs. out" or "shot percentage."

    • Subjective: Involves judgment calls, such as "quality of a press" or "effectiveness of a tackle."

  • Consistency (Reliability): If the same event is measured on different days or by different people, the numbers should be identical.

  • Validity: The analyst must ask: Does measuring this actually help the team's performance?

Applied Case Study: Tennis Analysis

During the workshop, students practiced notational analysis on a professional tennis match (e.g., Alcaraz, Federer, Nadal) using the following metrics:

  • Service Data

    • First Serve Percentage: Successful First ServesTotal First Serves×100\frac{\text{Successful First Serves}}{\text{Total First Serves}} \times 100

    • Aces: Serves the opponent fails to touch.

    • Double Faults: Failing both serve attempts.

  • Outcome Data

    • Winners: Successful shots that the opponent cannot reach.

    • Errors: Categorized by "Forehand" vs. "Backhand."

  • Key Performance Indicators (KPIs)

    • KPIs must be realistic and researched. For example, a power player may have a KPI to win more than 83%83\% of rallies consisting of three or fewer shots.

    • Context matters: Success rates vary based on court surface (Grass, Clay, Hardcourt) and opponent ranking.

Questions & Discussion

Q: What jumped out to you as relevant from Aaron's lecture?A: One student noted how much "building" or preparation happens in a single week; Pete clarified that the analyst's job is to handle all the extra data gathering so the coach can focus on the sport.

Q: Why track both the home and away team in a frequency table?A: It provides context. For example, if it is raining, high error counts for the home team might be explained by the weather if the away team also has high error counts.

Q: Is position (possession) important in football?A: It depends on the team's strategy. Some teams play possession-based styles; others use a "punt it and get lucky" approach. The analyst must determine if the metric is valid for their specific team's goals.