Project: Who's Heating Up? Season Trend Tracker

Introduction

Quarterbacks get hot. Receivers go on a run. Analysts track recent passing yards to spot who's heating up.

Today you will build a mini trend tracker that scans recent games and finds hot streaks.

What we're building

Store recent game stats in a list
Loop through the list to find big games
Track streaks to see how long the hot stretch lasts
Load a CSV game log and analyze real data

Part 1: Quick Start

Download the Starter Pack

Open the starter pack in Cursor by going to File > Open Folder and selecting the folder you downloaded from your computer.

You should see a file called trend_tracker.py. Open it, this is where we will be writing our code.

Download the Football Game Log

>button: Download Football Game Log CSV

Move the downloaded game_log.csv into the same folder as trend_tracker.py.

Writing the code

Type the code below into trend_tracker.py:

player_name = "Your QB"
recent_stats = [210, 275, 312, 198, 340]

print(f"Trend Tracker for {player_name}")
print("Recent games:", recent_stats)

Running the code

Save the file (Cmd + S or Ctrl + S)

Run the code by clicking the "play" icon in the top right of the screen. Or open the terminal (Cmd + ~ or Ctrl + ~) and type python trend_tracker.py.

If everything is working correctly, you should see:

Trend Tracker for Your QB
Recent games: [210, 275, 312, 198, 340]

Great! You just created your first list of game stats.

Here's what you need to know about lists:

List stores multiple items in a single variable (like a shopping list!)
Lists can hold numbers, text, or other data types
Items in a list stay in order and you can change them
Each item has a position number (called an index), starting at 0 for the first item

Part 2: Project Milestones

Milestone 1: Print every game in the list

A list is great, but we want to look at each game individually. That is where loops come in.

for stat in recent_stats:
    print(stat)

Expected output:

Here's what you need to know about loops:

A loop lets you go through each item in a list one by one
The for loop repeats the same code for every item
Think of it like checking each game on your list — you look at game 1, then game 2, then game 3...

Milestone 2: Flag hot games above a threshold

Now we will define what counts as a "hot" game. For passing yards, let us use 300 yards.

The if statement lets your program make decisions. Think of it like this: "If the stat is high enough, then print it!" The program checks each game — if it meets your threshold, it prints it. If not, it moves on to the next game.

hot_threshold = 300

for stat in recent_stats:
    if stat >= hot_threshold:
        print(f"Hot game: {stat}")

Expected output:

Hot game: 312
Hot game: 340

Milestone 3: Track the longest hot streak

Let us track how many hot games in a row the player had. This is a streak counter.

hot_threshold = 300
current_streak = 0
best_streak = 0

for stat in recent_stats:
    if stat >= hot_threshold:
        current_streak = current_streak + 1
        if current_streak > best_streak:
            best_streak = current_streak
    else:
        current_streak = 0

print(f"Best hot streak: {best_streak}")

Expected output:

Best hot streak: 1

Here's what's happening with if and else:

The if statement checks: "Is this stat hot enough?" If yes, add 1 to the streak.
The else statement handles what happens when the answer is no: reset the streak to 0.
Think of it like this: "If the game is hot, keep counting. Otherwise, start over!"

Try changing the list to include multiple hot games in a row and run it again.

Milestone 4: Load stats from a CSV file

Lists are useful, but real data is often stored in files. Use the game_log.csv you downloaded earlier.

A CSV (Comma Separated Values) file is a plain text file where each line represents a data record, and fields within each record are separated by commas.

The file looks like this:

date,stat
2025-01-03,210
2025-01-10,275
2025-01-17,312

Now load it in Python:

import csv

stats_from_file = []

with open("game_log.csv", "r") as file:
    reader = csv.DictReader(file)
    for row in reader:
        stats_from_file.append(int(row["stat"]))

print("Loaded stats:", stats_from_file)