Matt Rhea, PhD
@MattRheaPhD · United States · joined 25 Jan 2012
Athlete Engineer. Strength and Conditioning Coach. Sport Scientist.
33 726Followers
74Following
3 597Posts total
49.7KViews on collected posts
Latest posts
Looking for new posts…
Two men that I got to watch do it the right way every day! @Mathieu_Era @taeetaylor
Are you looking for a reason to not play or are you doing everything in your power to get out there with your teammates?
3.6K views · 4 likes
· 0 reposts · 0 replies
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Three seasons, zero missed games 😳
Alontae Taylor and Tyrann Mathieu explain the mindset behind showing up every Sunday 👇
“I heard Tyrann come out of the training room one day and say, ‘Are you hurt or are you injured?’ Two totally different things… I was telling the guys http
6K views · 66 likes
· 3 reposts · 2 replies
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5:26
@MattRheaPhD Why not? Many student interns take internships at other institutions. It allows for developing other relationships and pipelines
131 views · 0 likes
· 0 reposts · 1 replies
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@MattRheaPhD This is an interesting take. I interned for my own university, but was also encouraged to intern at another. It seems like a great way to broaden your horizons and learn from more than one master strength coach.
373 views · 2 likes
· 0 reposts · 0 replies
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College S&C/Sport Sci depts “hiring”interns that aren’t part of your university student body is absurd. You realize the only reason you have college athletics is because of academics, right?There shouldn’t be an intern in your operation that isn’t a student at your institution.
9.7K views · 30 likes
· 2 reposts · 4 replies
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Grandkids, fireworks, BBQ, and Baseball! Have a day America! 🇺🇸 https://t.co/0113MXiE10
2.3K views · 35 likes
· 0 reposts · 0 replies
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You don’t have to rely on the “experts” to make sense of research literature or just trust that someone is giving you accurate info. Anyone can find research-backed answers through AI tools. So if you want to know if the weight room improves speed in athletes, for example, ⬇️ htt
3.1K views · 13 likes
· 3 reposts · 1 replies
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@MattRheaPhD How has the injury rate changed to, let’s say, pre-2000? More? Less? Different?
248 views · 1 likes
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I don’t care if we call it injury prevention, injury risk mitigation, or something else but instead of arguing semantics, we need to focus more time and effort on identifying the things that actually make sports participation safer and keep athletes healthier.
1.6K views · 17 likes
· 2 reposts · 2 replies
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If we then implement a program or system that addresses those risk factors and then see an injury rate below what would be predicted, we can say we had a positive impact.
1.7K views · 5 likes
· 0 reposts · 1 replies
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Can we predict injuries in sports? YES. Based on published research over past 15 years, we can predict how many injuries will occur per 1,000 hours of athlete exposure. ~30 in soccer, 75 rugby, 20 American Football, 9 basketball, 2 baseball and softball, and 35 in hockey.
19.6K views · 47 likes
· 11 reposts · 4 replies
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Can we prevent injuries in sports? YES. By examining trends in those athletes that get injured compared to those that do not, we find characteristics that suggest an athlete might be at greater risk. Strength, hydration status, motor coordination, acute:chronic workload, etc.
1.5K views · 9 likes
· 0 reposts · 1 replies
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Against accounts of the same size
12 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.
Median views2 012this account961median for 10K–100K
Reach, %5.97%this account3.53%median for 10K–100K
Engagement, %0.55%this account1.59%median for 10K–100K
| Metric | This account | Median for 10K–100K | Ratio |
|---|---|---|---|
| Median views per post | 2 012 | 961 | 2.09× |
| Reach (views ÷ followers) | 5.97% | 3.53% | 1.69× |
| Engagement rate | 0.55% | 1.59% | 0.34× |
Others in this range → Compare with another account → How these benchmarks are built →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
1.5K25 Jun
19.6K
1.7K
1.6K
24826 Jun
3.1K27 Jun
2.3K4 Jul
9.7K6 Jul
3737 Jul
1318 Jul
6K24 Jul
3.6K
Last 12 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.69%25 Jun
0.32%
0.35%
1.35%
0.40%26 Jun
0.55%27 Jun
1.51%4 Jul
0.37%6 Jul
0.54%7 Jul
0.76%8 Jul
1.20%24 Jul
0.11%
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.59%.
What the audience does
Likes68.0%229 in total
Reposts6.2%21 in total
Replies4.7%16 in total
Quotes0.3%1 in total
Bookmarks20.8%70 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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