Lesson Aim
Students watch a video about how big data and analytics have transformed professional basketball, especially the Houston Rockets, and discuss data-driven decision-making in sport and business.
Before watching
- How can data help a sports team win?
- Should coaches trust data or instinct more?
- What other industries use analytics to gain an edge?
Prep Part 1
Drag the correct sentence ending into each gap.
Sentence endings
analyse large amounts of informationthe best value or return for the effortvery small differencesit gets a small advantage over competitors.students should connect it to the lesson topic.Watch Part 1
Watch from 0:04 to about 3:39. Focus on the Houston Rockets, big data, three-point shots and why some shots are statistically better than others.
Open Part 1 on YouTube
Comprehension 1
Choose an answer to get instant green/red feedback.
1. What helped fuel the Houston Rockets’ dramatic rise?
2. According to the video, what balance is important?
3. What shots did the data show were especially valuable?
4. What happened to attempted three-point shots over the past decade?
Vocabulary from Part 1
Elite sport is decided by the finest of .
The Rockets rose from mid-table .
Analytics gave the team an .
The data revealed which shots gave the best bang for .
Options
retailersmarginsedgemediocritybuckPrep Part 2
Drag the correct sentence ending into each gap.
Sentence endings
happening immediately as events occursmall improvements that add upit is detailed enough to show small patterns and differences.very detailed informationstudents should connect it to the lesson topic.Watch Part 2
Watch from about 3:39 to the end. Focus on tracking systems, machine learning, player movement, recruitment and the future of real-time analytics.
Open Part 2 on YouTube
Comprehension 2
Choose an answer to get instant green/red feedback.
1. What does Second Spectrum collect for NBA teams?
2. How often do cameras track player and ball movement?
3. What can machine learning help teams estimate?
4. What edge has data given the Rockets in recruitment?
Vocabulary from Part 2
Second Spectrum gathers a vast range of .
Machine learning creates interactive .
Teams can analyse the minutiae of their .
Data can become functionally real-.
Options
timeperformancesdatavisualizationskeynoteVocabulary Review
| Expression | Meaning | Example |
|---|---|---|
| gain an edge | get a small advantage over competitors | Analytics gave the Rockets an edge. |
| crunch data | process and analyse data | The team started crunching game data. |
| best bang for buck | the best value or return | Three-pointers can provide better bang for buck. |
| marginal gains | small improvements that improve performance | Teams look for marginal gains on court. |
| real-time analytics | data analysis available immediately | Real-time analytics could help coaches during games. |
Phrasal Verbs and Expressions
You can break winning into two things.
The team went the data after games.
Analytics helped the Rockets figure better shot choices.
Successful teams look marginal gains.
Data has changed how teams set their strategy.
Options
downupoverouthomeforCollocations
big
winning
video tracking
machine learning
real-time
Options
formulaanalyticssystemapartmentdatatechnologyB2/C1 Grammar: Data, Comparison and Cause/Result
This section practises language for explaining how evidence changes decisions.
Grammar Section 1: Cause and Result
Choose an answer to get instant green/red feedback.
1. Complete: “The data revealed better shot choices; ___, teams attempted more three-pointers.”
2. Which sentence is best?
Grammar Section 2: Comparing Performance
Three-pointers can be more efficient long two-point shots.
Players today are leaner and more .
Data makes it easier to extract small .
Real-time analytics could help coaches as the game .
Options
symbolismthanagilepercentageshappensGrammar Section 3: Speaking Task
| Explaining data | Comparing options | Predicting impact |
|---|---|---|
| The data shows that... The evidence suggests... The analysis reveals... | Compared with... more efficient than... a better return than... | This could lead to... This may change... As a result... |
Thought-Provoking Questions
1. Should coaches trust data more than experience?
2. Does analytics make sport more interesting or less human?
3. Could too much data make players less creative?
4. What other sports have changed because of analytics?
5. Is a 5% advantage really massive in professional sport?
6. Should real-time data be allowed during games?
7. How could your workplace or studies use data better?
Role Play
| Data analyst | Traditional coach | Compromise |
|---|---|---|
| The data shows... This gives us an edge. We should change our shot selection. | Players need confidence. Instinct still matters. Data cannot see everything. | Let’s balance data and instinct. We can test the approach. We should use data to support decisions. |
Context
Student A
You are the data analyst. Explain why the team should take more three-pointers and use tracking data.
Student B
You are the coach. You respect data, but you worry about team chemistry, player instinct and over-reliance on numbers.
Role play task: Agree on a balanced strategy that uses data without ignoring human judgement.
Thank You
You have completed the ESL CONNECT video lesson.