100 Sports Research Topics for High School Students

Updated October 2026

TL;DR

This guide lists 100 sports research topics for high school students across ten areas: performance analytics, exercise physiology, sports psychology, biomechanics, nutrition and recovery, coaching and tactics, sports technology, sports economics, sociology and equity, and environment and sustainability. Each topic has a one-line description and a difficulty level (beginner, intermediate, or advanced), and most name a free data source or tool you can use. A comparison table helps you find the area that fits your interests and skills. If you want to turn one of these ideas into a college-level research paper with one-on-one guidance from a PhD mentor, you can apply to the Horizon Academic Research Program.

Many high school students applying to college play a sport. Far fewer have researched one. If you’re planning to study kinesiology, sports management, or data science, a sports research project shows colleges that your interest goes beyond the field or court. It also gives you something specific to discuss in applications and interviews.

With thousands of directions to choose from, picking a topic can feel overwhelming, so we’ve narrowed it down to 100 sports research topics for high school students across ten disciplines. If you want ideas beyond sports, browse our list of STEM research topics for high school students.

What does sports research look like in high school?

Sports research means answering a focused question about athletes, teams, or the sports industry using evidence. You might analyze game statistics, compare training methods, study injury risk, survey athletes about motivation, or examine the economics of ticket prices and stadiums.

Most high school projects use one of three approaches:

• Data analysis: You work with public statistics from league databases, weather records, or open datasets, using a spreadsheet or Python.
• Literature review: You compare published studies from databases like PubMed and Google Scholar to explain what the evidence shows.
• Small original studies: You collect your own data through anonymous surveys, video analysis, or simple supervised tests.

If you enjoy the data side, these sports analytics summer programs show how teams use statistics.

How do you choose a sports research topic?

Start with a sport or question you already care about, then narrow it until you can answer it with data you can reach. “Sports injuries” is a field, not a topic. “Why do female soccer players tear their ACL more often than male players?” is a question you can dig into.

A strong topic has three things: sources or data you can access, a question with a measurable answer, and a scope that fits your timeline. Match the difficulty level to your skills, too. Beginner topics need a spreadsheet, while advanced topics often need coding or modeling experience. For more help narrowing your idea, read our guide on picking a broad vs. niche research topic.

Which area of sports research fits you?

Best sports research topics for high school students by area

Sports performance analytics

These topics use game statistics to explain why some players, teams, or strategies win more.

1. Three-point shooting, turnovers, and NBA wins (Beginner): Test how well these two team stats predict regular-season wins using Basketball Reference data.
2. Ball possession and Premier League results (Beginner): Check whether teams with more possession win more often, using public match datasets on Kaggle.
3. Home advantage across four leagues (Beginner): Compare home and away win rates in the NBA, MLB, NFL, and Premier League over two decades.
4. Starting-pitcher stats and MLB outcomes (Intermediate): Test whether ERA, WHIP, or strikeout rate best predicts wins, using FanGraphs data and a classification model.
5. Free throw percentage in close NBA games (Beginner): Measure whether better free throw shooting helps teams win games decided by a few points.
6. Serve and return stats in ATP matches (Intermediate): Use Jeff Sackmann’s open tennis datasets to find which stats best predict match winners.
7. NBA scoring efficiency by court zone (Intermediate): Compare points per shot at the rim, from mid-range, and from three using NBA shot-location data.
8. Predicting marathon times from shorter races (Intermediate): Build a regression model that predicts marathon finish times from 5K, 10K, and half-marathon results.
9. Turnover rate and NCAA Division I wins (Beginner): Test whether college basketball teams that protect the ball win more, using Sports Reference data.
10. Expected goals vs. actual goals (Intermediate): Use Understat’s xG data to see which Premier League teams consistently beat or miss their expected scoring.

Exercise physiology and human performance

These topics look at how your body responds to training, effort, and recovery.

11. Exercise intensity and heart rate recovery (Beginner): Track how quickly heart rate drops after light, moderate, and hard exercise using a fitness tracker.
12. Warm-up length and shuttle run times (Beginner): Compare timed shuttle run results after short and longer warm-ups in a supervised setting.
13. Resting heart rate and aerobic fitness (Beginner): Check whether students with lower resting heart rates score higher on a standard fitness test.
14. Exercise duration and perceived exertion (Beginner): Use the Borg RPE scale to see how effort ratings change as moderate exercise continues.
15. Air temperature and endurance performance (Intermediate): Review published studies on how heat and cold affect endurance, without testing people in unsafe conditions.
16. Weekly training frequency and 5K times (Intermediate): Survey recreational runners to see whether training more days per week links to faster 5K times.
17. Heart rate variability as a recovery marker (Advanced): Analyze public wearable datasets to test whether HRV changes reflect recovery after exercise.
18. Recovery in trained vs. recreational exercisers (Intermediate): Compare how quickly heart rate returns to normal in regularly trained and casually active people.
19. Sleep duration and fitness test scores (Beginner): Compare self-reported sleep with performance on a simple, age-appropriate fitness test.
20. Endurance benchmarks across three sports (Intermediate): Compare published performance data to see how endurance differs among runners, swimmers, and cyclists.

Sports psychology and mental performance

These topics explore how confidence, motivation, and pressure shape performance.

21. Pre-competition anxiety and performance (Intermediate): Pair the Sport Competition Anxiety Test with game results to see whether nerves link to performance.
22. Music and motivation during exercise (Beginner): Compare motivation and effort ratings for workouts done with and without music.
23. Mental imagery and shooting accuracy (Intermediate): Test whether a short guided visualization changes free-throw or target-shooting accuracy.
24. Athletic confidence and skill test results (Beginner): Check whether self-reported confidence matches performance on a standard skill test.
25. Goal setting and training motivation (Beginner): Compare motivation in athletes who set specific, measurable goals with those who simply log workouts.
26. Time pressure and decision-making (Intermediate): Build a simple computer task and measure how decision accuracy changes under time pressure.
27. Social support and sport motivation (Beginner): Survey student-athletes on support from coaches, teammates, and family, and compare it with motivation.
28. Sleep quality and motivation to train (Beginner): Use anonymous questionnaires to see whether better sleepers report stronger motivation to practice.
29. Positive vs. corrective feedback (Intermediate): Test how different feedback styles affect motivation during repeated skill practice.
30. Competitive vs. cooperative drills (Intermediate): Compare how motivated players feel after drills built around competition versus teamwork.

Biomechanics and injury prevention

These topics study how the body moves and how forces affect injury risk.

31. Stride length, cadence, and knee loading (Advanced): Use published biomechanics data and OpenSim to estimate how running form changes the load on the knee.
32. Landing technique in vertical jumps (Intermediate): Compare soft and stiff landings using Kinovea video analysis and published force-plate data.
33. Running shoe type and stride mechanics (Intermediate): Film runners in different shoes and measure stride length and foot strike in Kinovea.
34. Injury history and single-leg balance (Beginner): Compare supervised balance test scores in athletes with and without past lower-limb injuries.
35. Fatigue and jump-landing mechanics (Advanced): Use existing motion-capture data to see how knee and hip movement changes when athletes are tired.
36. Running surfaces and stride (Intermediate): Compare stride characteristics on track, treadmill, grass, and road using published studies and video.
37. Pedaling cadence and cycling power (Intermediate): Analyze cycling power data to see how cadence affects power output at a fixed workload.
38. Stroke rate and swimming race times (Beginner): Count stroke rates from race footage and compare them with finishing times.
39. What drives tennis serve speed (Intermediate): Use frame-by-frame video to link toss position, body rotation, and contact height to serve speed.
40. Movement symmetry in trained vs. recreational athletes (Advanced): Compare left-right movement patterns using public gait or motion-capture datasets.

Sports nutrition, hydration, and recovery

These topics examine how food, fluids, and rest affect performance.

41. Hydration and endurance performance (Intermediate): Review published studies on fluid loss and endurance rather than dehydrating participants.
42. Breakfast and morning performance (Beginner): Survey students about breakfast habits and compare them with results on a supervised morning fitness task.
43. Carbohydrate availability and endurance (Intermediate): Summarize research on how carbohydrate intake affects performance in long events.
44. Protein intake and muscle recovery (Intermediate): Review studies comparing protein intake with recovery markers after resistance training.
45. Sleep and perceived recovery (Beginner): Use sleep diaries and short surveys to see whether athletes who sleep more feel more recovered.
46. Active recovery, stretching, and rest (Intermediate): Compare published evidence on how each strategy affects muscle soreness.
47. What shapes athletes’ fluid intake (Beginner): Survey athletes about training length, weather, and water access to find patterns in hydration habits.
48. Energy drinks and sports participation (Beginner): Use an anonymous survey to compare energy drink use among teens with different training schedules.
49. Recovery habits of high school athletes (Beginner): Survey athletes on sleep, stretching, nutrition, and rest days to map common recovery practices.
50. Nutrition knowledge and food choices (Intermediate): Compare scores on a nutrition knowledge questionnaire with athletes’ reported food choices.

Coaching, tactics, and team strategy

These topics test the decisions coaches and teams make during games.

51. Substitution timing in soccer (Intermediate): Test whether substitutions made at certain points in a match link to goals or better results.
52. Zone vs. man-to-man defense (Intermediate): Compare opponent scoring efficiency against each defense using game film and team stats.
53. Pace of play and NBA scoring (Beginner): Check whether teams with more possessions per game also score more efficiently, or just more often.
54. Fourth-down decisions in the NFL (Intermediate): Use free NFL-verse play-by-play data to see whether going for it on fourth down raises win probability.
55. Soccer formations and attacking output (Intermediate): Compare shots and goals across formations using StatsBomb Open Data, which records team lineups and formations.
56. Home vs. away playing style in soccer (Intermediate): Compare possession, shots, and passing in home and away matches for the same teams.
57. Passing accuracy and soccer results (Beginner): Test whether teams that complete more passes win more often, using StatsBomb Open Data.
58. Coach timeouts and NBA scoring (Advanced): Use play-by-play data to see whether scoring efficiency changes in the possessions after a timeout.
59. Defensive pressure and pass completion (Intermediate): Use StatsBomb Open Data, which flags passes made under pressure, to measure how pressure affects accuracy.
60. Playing style after rule changes (Intermediate): Compare league stats before and after a major rule change, such as MLB’s pitch clock introduced in 2023.

Sports technology and wearable devices

These topics explore how sensors, cameras, and AI measure athletic performance.

61. Fitness trackers vs. chest-strap monitors (Intermediate): Review validation studies comparing wrist-based heart rate readings with chest-strap measurements.
62. GPS data and training load (Intermediate): Explore how distance and acceleration data from GPS trackers are used to estimate workload in team sports.
63. Computer vision player tracking (Advanced): Use OpenCV and MediaPipe to track player movement in publicly available sports video.
64. Smartwatch exercise intensity readings (Beginner): Compare smartwatch intensity classifications with manually recorded workouts or published validation data.
65. Machine learning to predict performance (Advanced): Train a model on historical stats and test how well it predicts an athlete’s next-season performance.
66. Classifying movements from accelerometer data (Intermediate): Use UCI’s Daily and Sports Activities dataset to classify activities such as walking, running, and jumping.
67. VR training and decision-making (Intermediate): Review experiments on whether virtual reality practice improves decisions in game situations.
68. Running speed from smartphone video (Intermediate): Estimate sprint speed from phone footage in Kinovea and check it against stopwatch times over a set distance.
69. Wearable data and self-reported recovery (Intermediate): Test whether resting heart rate, sleep, or HRV best matches how recovered athletes say they feel.
70. Computer vision for officiating (Advanced): Explore how accurately vision models detect events such as out-of-bounds balls or offside positions.

Sports economics, business, and management

These topics examine the money behind sports, from salaries to ticket sales.

71. Social media following and team value (Beginner): Compare team follower counts across platforms with Forbes franchise valuations.
72. Ticket prices and attendance (Beginner): Test whether higher average ticket prices link to lower attendance across teams or seasons.
73. Payroll and winning in MLB and the NBA (Intermediate): Compare team payrolls from Spotrac with winning percentage to see how much spending buys.
74. Major events and hotel occupancy (Intermediate): Use city tourism reports to see how hotel demand shifts around events like the Super Bowl.
75. Team success and merchandise interest (Intermediate): Use Google Trends to see whether winning streaks and playoff runs boost searches for team gear.
76. Economic outcomes for Olympic host cities (Intermediate): Compare tourism, employment, and public spending before and after the Games using World Bank and OECD data.
77. Broadcasting deals and league revenue (Intermediate): Track how major TV and streaming contracts line up with league revenue growth.
78. Resale ticket prices before game day (Intermediate): Record resale prices for similar games over several weeks to see how they change as the date nears.
79. Men’s and women’s league salary gaps (Intermediate): Compare salaries alongside revenue, attendance, and media exposure in comparable leagues.
80. Winning percentage and home attendance (Beginner): Check whether teams draw bigger crowds in seasons when they win more.

Sports sociology, equity, and participation

These topics study who gets to play and how sports are represented.

81. Household income and youth sports (Intermediate): Use National Survey of Children’s Health data and Aspen Institute Project Play reports to compare participation by income.
82. Boys’ and girls’ high school participation trends (Beginner): Chart decades of data from the NFHS High School Athletics Participation Survey.
83. Sports facilities by neighborhood income (Intermediate): Map parks and fields against Census income data using OpenStreetMap and QGIS.
84. Coverage of women’s vs. men’s sports (Beginner): Code a sample of sports news articles to measure how much coverage each receives.
85. Paralympic vs. Olympic media coverage (Intermediate): Compare how often and how Paralympic athletes appear in major news outlets.
86. Organized sports and sense of community (Beginner): Survey students to see whether team members report stronger community connection.
87. School athletic spending and participation (Intermediate): Compare district athletic budgets with sports participation rates using public financial records.
88. School sports and academic performance (Beginner): Review education research and public data on how athletes and non-athletes compare academically.
89. Cost of youth sports in one region (Beginner): Compare registration, equipment, and travel costs across popular sports using club websites.
90. Facility access for girls’ and boys’ sports (Intermediate): Map local facilities to see whether spaces for girls’ and boys’ sports are equally available.

Sports environment, facilities, and sustainability

These topics connect sports with weather, climate, and infrastructure.

91. Heat, humidity, and endurance race results (Intermediate): Match race results with NOAA weather records to see how conditions affect finish times.
92. Wildfire smoke and outdoor sports (Intermediate): Compare EPA AirNow air quality data with game cancellations and schedule changes.
93. Stadium electricity use (Intermediate): Use stadium sustainability reports to see how attendance, weather, and event type relate to energy use.
94. Weather and sports field irrigation (Intermediate): Compare parks department water records with rainfall and temperature data.
95. Artificial turf vs. natural grass temperature (Beginner): Measure surface temperatures with an infrared thermometer on sunny days and compare them with published findings.
96. Rain and soccer passing and scoring (Intermediate): Match soccer passing and scoring stats with historical weather records for each game.
97. Extreme heat and scheduled outdoor events (Beginner): Compare event schedules with NOAA temperature records to count how often games fall on very hot days.
98. Carbon emissions from team travel (Intermediate): Estimate a team’s flight emissions using Great Circle Mapper distances and EPA emission factors.
99. Public transit access to stadiums (Intermediate): Map stadiums against GTFS transit stop data in QGIS to compare how reachable they are without a car.
100. Comfortable outdoor sports days under warming (Advanced): Use NOAA Climate Data Online to estimate how the number of comfortable playing days in U.S. cities has changed.

How can you take a sports topic further?

Once you’ve picked a topic, write a one-sentence research question, find your data source, and run a small test analysis before committing. That quick check tells you early whether the data can actually answer your question.

When your paper is finished, you can submit it to one of these research journals for high school students.

If you’d like hands-on experience alongside your project, look into these sports internships for high school students or compare high school research programs across subjects.

If you want expert support from start to finish, the Horizon Academic Research Program is an online program where you work with a professor or PhD mentor to write a college-level, 20-page research paper. To strengthen your application, read these tips from the Horizon admissions committee.

What students often ask about these sports research topics

Image source: Horizon Academic Research Program