Why preseason doesnt matter

I feel that Preseason games do not matter because the 4 games that are played they use back up players Maybe I'm wrong But I get more out of the regular season games due to them having the 1st string players on the field I'm a ravens fan and one of our players got injured for the whole season And why did that happen? He injured himself during the Ben Watson That's the player I was thinking of If we have to have Preseason games lets just have two games instead of 4.

Its good to see all the teams out on the field but there's always unnecessary risk of injuries before the official season starts.

The only positive aspect is each of the players are able to see what works and what doesn't against another formidable team.

Definitely not an indicator of how the season will turn out. The preseason is can matter at the beginning of the regular season but really it doesn't after the first few games or even at all. The preseason is great for tuning players to get ready for the regular season because anything can happen in the NFL but really it doesn't matter. No, the NFL preseason doesn't really matter. It's not a good snapshot of how teams are going to play all season long.

It's a chance for the team to work out, practice and get the kinks worked out of new plays, and new players, if there are any joining the team. The preseason is not an accurate picture of how the actual season is going to go. It is just a time for the teams to get ready and to figure out what is going to work for them. The preseason is more like a scrimmage than like real games. It should not be given too much consideration.

No I do not think that the NFL preseason matters. I do not think it shows how the team will do during the regular football season. The NFL preseason does not matter. The games are insignificant and are a waste of time. Save my name, email, and website in this browser for the next time I comment. Ben Elsner. Ben Kotwica. Paul Domowitch. Skip to content. Why Preseason Games Still Matter. But one game pair is really one observation, even though two teams are involved.

I'm not that fond of the way most standard statistical measures are used - they usually get taken well out of context. The majority of the variation you see is due to point quantization. It's not bias-free - it'll overpredict the small margins, and underpredict the large margins. The actual equation is less important than the fact that inasmuch as regular season games predict future regular season games, preseason games predict future regular season games.

If you do wager on games and I don't , this is just a guide. Say you're trying to guess how Dallas will do versus Philly in December. Well, you'd look at how they did the previous game they played in, right? In exactly the same way, if you're trying to see how Chicago will do against San Francisco in Week 8, look at how they did against them in the first half this Friday. RMS means Root-mean-square.

It's not called standard deviation because physicists like to sound better than statisticians. The correlation coefficient isn't that important.

The importance is whether or not preseason game scores are related to regular game rematches just like regular season rematches are. And they are. This tells you that preseason games are as predictive as regular season games are of performance in a rematch.

I transferred mid-grad school, after I had finished all of my classes at Penn State, but when I got here, I was told I needed to take at least one class because I couldn't graduate without a GPA. The math department should understand the limited statistical significance of only one class towards GPA.

Next thing you know they're making you class valedictorian Do you know if it makes a difference if you only look at the score at the end of the first quarter?

Only because, especially early in preseason, the starting units are only on the field about that long if that, and so it seems like that may possibly correlate better. I understand that doesn't give a team much time to build a significant point differential, but just a thought.

I tried doing that, and you're exactly right - I don't think it gives enough time. The correlation's significantly weaker which is wrong - it should be stronger, because one thing I didn't say in the article is that part of the increase is also due to the fact that I'm using only half a game - obviously with a full game a team has more time to build a much larger point differential. That's not the entire reason, though, the rest is what MDS pointed out.

Basically, the closer the RMS average point differential gets to zero, the more point quantization comes into play. Take last night, for instance - Philly was up at the end of the first quarter and completely dominated the first-team Raiders. But you could imagine a much harder-fought first quarter with the teams much closer, and still ending up with a score. Preseason VOA might be interesting to look at, though, since it's smoother.

You definitely would've been able to tell that Philly smothered the Raiders. In Aaron's infinite free time, of course. Incidentally, I also tried excluding the last week of the preseason. That reduces the significance.

That's fairly interesting to me. My personal guess on that, though, is that the performance of the second-string backups somewhat echoes the performance of the first string, which kinda makes sense. If your first string sucks, the second string is probably going to suck more. Teams usually don't keep better players on the second string. Most likely that tapers off for third and fourth string players. Okay guys. Let's not be ridiculous here. You are showing us a scatterplot with a correlation of.

What you do not tell your fine readers is that your plot is a scattershot, which indicates no correlation. Correlations read between -1 and 1. The closer you get to zero, the less of a correlation there is. Any statistition would tell you that this result is a meaningless one. That regression line is pretty worthless too. David - I don' think it's that bad. First, as Pat says, he is comparing preseason correlation to regular season correlation.

So the Q is, how do those correlations compare? Third, I've seen presentations in neuroscience although that's not my field with even worse correlations than that with actualy conclusions drawn. You mentioned home field advantage, and looked at points greater than 7 points; but that eliminates a lot of data points.

I recommend subracting the home field advantage from the second game when the field is switched, and doing nothing when it is not. But on average if both effects are real it should increase the correlation significantly. Patrick, are those plots done in ROOT? I was staring at them and thinking to myself I've seen a million like them, only with muons.

Great article, I guess I'll have to watch the preseason games now. Well, I was going to any way, but now I can argue with my wife that they are statistically correlated to the regular season and thus MUST watch them.

Any statistician would tell you that the important value for significance is p-value, not the correlation coefficient. If I take a set of numbers, X, and plot them versus 0. The p-value will be zero, which means there's no chance that it's random whatsoever. That means "these numbers are related.

The correlation coefficient itself doesn't really matter here. I know that the regression doesn't explain the majority of the spread. Of course not. It's a game. We wouldn't watch it if it did. But the important point is what James G pointed out: the preseason correlation is essentially identical to the regular season one.

Plus, as I've mentioned above, the correlation coefficient gets flattened by the points in the center. But this isn't important, because I do the same thing for both groups. You would think they would be related in some way, interesting article.

After the Colts went in the preseason and then started the season I started to wonder though ;o. Thing is, Indy's preseason slate in wasn't pretty - the easiest team they faced was Buffalo. Atlanta, Chicago, Denver, Cincinnati were the other teams. So that's 1 bad team, 1 average team, and 3 playoff teams.

Heck, Indy faced almost as many playoff teams 3 in the preseason as they did in the regular season 4! The only game that really was an outlier game was the Buffalo game, and anyone who actually saw the Buffalo-Indy preseason game realizes why. That's part of the bias I mentioned early on. Had Indy actually played Atlanta, Buffalo, Chicago, Denver, and Cincinnati early in the regular season in a row like that, I think there's probably a good chance they would've lost a few.

So when Indy went , that didn't mean they were going to be bad. It meant that the teams they played were going to be on par with them. And in 3 out of the 5 cases, that was true. Re 22 and misuse of statistical terms, to be fair, the poster claimed that the results don't have useful meaning, not that you'd somehow goofed statistical significance. Reading your response to my statement along the same lines 10 , I can buy that you have shown that the preseason correlation is on par with the regular season correlation.

The reason I brought up the double-observation issue is that the plots show each point twice. Glad that that's the only place they show up twice.

That will be an important game to watch, considering both teams could be in the playoff race. Nice article, Pat. It would be really interesting to see how well you can predict the results of the first few games of the regular season using preason stats like DVOA and the stats from the previous weeks of the season, and to see how long you had to go into the regular season until there was no added value to taking preseason stats into account like the week mark for regular season games.

The fact that the correlation coefficient is 0. Fahrenheit temperature and Celsius temperature, for instance, have a correlation of one, becaue they have a perfect linear relationship. It would be really interesting to see how well you can predict the results of the first few games of the regular season using preason stats like DVOA. I agree. It was fairly obvious to me that the limiting factor in this study was the granularity of the score.

You care about your favorite team and what kind of season they are going to have, right? Well the performances in the preseason go a long way towards determining not only who makes the bottom of the roster but who secures certain valuable roles for the season.

In two of my seven years, I was battling for a starting spot and the preseason games were a major determining factor in who won the job. There are usually at least one or two competitions for starting jobs unfolding during the preseason games. I have friends like that. They really just want to watch the Eagles and cheer them on in games that count during the regular season.

Two years ago in , the last time preseason games were played, the primary skill guys the Eagles used in those games were guys like wide receiver Greg Ward and running back Boston Scott, among others.