Hey everyone! Yesterday, I put out a statistical analysis that went over how correct people were at making predictions about Season 26 and Season 27, based on the difference between their predictions and the actual standings of the league. But those seasons are already over, and we are now at the doorstep of Season 28, discussing what the league is going to be like over these next few weeks and making our own guesses. And I feel like it doesn’t matter if you are a relatively new player, someone who’s already familiarized with the ISFL or a true veteran, many are kind of shooting in the dark in this Point Task. And I don’t blame them, it’s obviously hard predicting the future.
In this post, I want to follow on the footsteps of my analysis and give you who is reading this tips on what teams you should and shouldn’t be betting on during this next Season (S28) from a purely mathematical point of view (although my suggestions will be supported by previous media articles that go into further detail about each team). As well, I will also comment on a topic that couldn’t get out of my mind when making my original analysis.
Like my last media entry, I went through what users submitted, compared them to actual results and made my point. Here, instead of going over 50 entries, I managed to compile 159 entries. As I will discuss later however, little changed. Obviously, I couldn’t have the actual standings, since the season hasn’t started, so I managed to obtain a table containing the results of S28 simulations. In respect to the author of the simulations, I will not publish here their results nor my own table, and only the data I gathered from them.
If you haven’t seen my previous work, I created what I call “AD”, which is short for Average Deviation. It indicates, on a scale of 0 to 6, how much the average prediction deviated (was different from) the actual standings of teams at the end of a season. I will now divide teams and discuss their situation based on teams you should “bet on”, which are most likely going to live up to people expectations, be it positive or negative, and those you should “stay away from”, which are the most likely to be volatile and cause surprises throughout S28.
Teams You Should Bet on:
• (Baltimore). Sorry Baltimore, but you know why. After an 0-14 season, it might get a little better for you. But still pretty bad. Both users and simulation results agree that they’re going last in the ultracompetitive NSFC. Again.
With an AD of 0.27, they’re almost twice as predictable as the next team on this list.
Prediction: Baltimore goes 7th in the NSFC.
• (Philadelphia). I thought a lot about including teams that had a slightly lower AD instead of Philly. After going through some expert opinions however, most of all ztarwarz’s “Quick Look at Season 28”, I would argue several teams have the chance to make a push or actually get into the playoffs in the NSFC, which might change their placement, even if slightly. This team is not one of them. They have several flaws in their roster, which might eventually get fixed, since they are filled with young players. But as of S28, it’s going to be a similar season.
With an AD of 0.52, they are tied with Yellowknife to be the 3rd most predictable team in the ISFL this season and 2nd in the NSFC.
Prediction: Philadelphia goes 6th in the NSFC
• (Arizona). It would be easy to just say that the easiest teams to predict are the worst. Arizona is one massive exception to this. They are even more highly seen in both simulations and predictions than reigning Ultimus champions Sarasota. They are as sure as sure can be. Even if they have certain weaknesses, such as DLine, QB, and Kicker, the rest of this team overcompensates it. By a lot.
With an AD of 0.58, they are by far the most predictable Top 3 team in both NSFC and ASFC. Statistically, they are the 5th most predictable of them all and the 2nd most in the NSFC.
• Prediction: Arizona goes 1st in the ASFC
Teams you should stay away from:
• (New Orleans). A team that was one game away from the ultimate glory is the least predictable team of all ISFL? I believe it is exactly because of last season’s ASFC championship run that they are so controversial. They showed to have great sim luck and a championship window. As ztarwarz would argue, however “It's hard not to look at this team and consider its window closed.”. Aging players and disappointing draft classes can set this team back, but sim luck, recent successes, and being part of the ASFC can make this team get to the top again.
With an AD of 2.75, they are 0.36 points ahead of the 2nd most volatile team in the league and are the absolute question mark of this season.
Prediction: Stay away from betting on NOLA.
• and (New York and San Jose). I want to show you all at least one team from each conference, so I put in NY and San Jose together to fit space for a NSFC team. Also because they have very similar stories. In New York, users expect for their offense to help them get over the obstacles their own defense may impose them and make it, or at least fight for, the playoffs. Simulations, however, say otherwise, putting NY in 6th on average.
For San Jose, it’s the exact opposite. There is a consensus that San Jose’s roster, that serious lacks on-field cohesion, will battle it out to be the worst team of the ASFC. Simulations, however, say otherwise. They say the SaberCats are very much still in playoff contention, and are more likely to end up in the top half than the top bottom.
As far as AD is concerned, San Jose takes a slight advantage with 2.39, slightly over New York’s 2.29. They are, together with NOLA and the next team in this list, the only teams to reach an AD over 2.
Prediction: One will go to the playoffs, the other will finish 6th. Who is going to do what is a literal coin toss.
• ( Chicago). The only NSFC team to have an AD above 2, this comes as a surprise for many. Some would argue that Chicago’s recent success and attempts to build a great roster should still carry them over to the playoffs in a team firmly dominated by a few teams, who should easily secure the first 3 spots. Others also wonder if Chicago’s regression and lack of depth may finally show up this season. Simulations, however, confirm these fears. They are expected to finish as many as 2 wins below the playoffs. If you believe simulations, that is.
Prediction: If anyone in the NSFC is going to raise some eyebrows this season, it’s Chicago.
I said I would also reflect on a specific point of my previous statistical analysis, so if you only wanted my tips and predictions, you can skip this part. But I feel obligated to point this out.
One of my major fears was that a sample of only 50 predictions would be way too little to make an accurate representation of the general public’s opinion, especially when there were more than 300 entries available per season. When expanding my analysis to triple the entries, with 150, I expected to confirm this. I did not. Only two teams changed standings, which were NOLA (who fell from 4th to 5th) and Orange County, who took NOLA’s place, and not much changed after.
I would add that further research can certainly be done using a more concrete data value, such as predicted wins and actual wins, and the same or similar method can be used to reflect on regular season and playoff predictions. I do not expect to be doing them until a couple of weeks into the regular season, if at all, so I would certainly encourage those who are just as nerdy as I am to conduct similar experiments and analyses as I have over these past few days.
I also received several positive messages on my last post, so I would like to thank all of you who have read both that and this post, and I hope to help you out to crush those regular season predictions!
In this post, I want to follow on the footsteps of my analysis and give you who is reading this tips on what teams you should and shouldn’t be betting on during this next Season (S28) from a purely mathematical point of view (although my suggestions will be supported by previous media articles that go into further detail about each team). As well, I will also comment on a topic that couldn’t get out of my mind when making my original analysis.
Like my last media entry, I went through what users submitted, compared them to actual results and made my point. Here, instead of going over 50 entries, I managed to compile 159 entries. As I will discuss later however, little changed. Obviously, I couldn’t have the actual standings, since the season hasn’t started, so I managed to obtain a table containing the results of S28 simulations. In respect to the author of the simulations, I will not publish here their results nor my own table, and only the data I gathered from them.
If you haven’t seen my previous work, I created what I call “AD”, which is short for Average Deviation. It indicates, on a scale of 0 to 6, how much the average prediction deviated (was different from) the actual standings of teams at the end of a season. I will now divide teams and discuss their situation based on teams you should “bet on”, which are most likely going to live up to people expectations, be it positive or negative, and those you should “stay away from”, which are the most likely to be volatile and cause surprises throughout S28.
Teams You Should Bet on:
• (Baltimore). Sorry Baltimore, but you know why. After an 0-14 season, it might get a little better for you. But still pretty bad. Both users and simulation results agree that they’re going last in the ultracompetitive NSFC. Again.
With an AD of 0.27, they’re almost twice as predictable as the next team on this list.
Prediction: Baltimore goes 7th in the NSFC.
• (Philadelphia). I thought a lot about including teams that had a slightly lower AD instead of Philly. After going through some expert opinions however, most of all ztarwarz’s “Quick Look at Season 28”, I would argue several teams have the chance to make a push or actually get into the playoffs in the NSFC, which might change their placement, even if slightly. This team is not one of them. They have several flaws in their roster, which might eventually get fixed, since they are filled with young players. But as of S28, it’s going to be a similar season.
With an AD of 0.52, they are tied with Yellowknife to be the 3rd most predictable team in the ISFL this season and 2nd in the NSFC.
Prediction: Philadelphia goes 6th in the NSFC
• (Arizona). It would be easy to just say that the easiest teams to predict are the worst. Arizona is one massive exception to this. They are even more highly seen in both simulations and predictions than reigning Ultimus champions Sarasota. They are as sure as sure can be. Even if they have certain weaknesses, such as DLine, QB, and Kicker, the rest of this team overcompensates it. By a lot.
With an AD of 0.58, they are by far the most predictable Top 3 team in both NSFC and ASFC. Statistically, they are the 5th most predictable of them all and the 2nd most in the NSFC.
• Prediction: Arizona goes 1st in the ASFC
Teams you should stay away from:
• (New Orleans). A team that was one game away from the ultimate glory is the least predictable team of all ISFL? I believe it is exactly because of last season’s ASFC championship run that they are so controversial. They showed to have great sim luck and a championship window. As ztarwarz would argue, however “It's hard not to look at this team and consider its window closed.”. Aging players and disappointing draft classes can set this team back, but sim luck, recent successes, and being part of the ASFC can make this team get to the top again.
With an AD of 2.75, they are 0.36 points ahead of the 2nd most volatile team in the league and are the absolute question mark of this season.
Prediction: Stay away from betting on NOLA.
• and (New York and San Jose). I want to show you all at least one team from each conference, so I put in NY and San Jose together to fit space for a NSFC team. Also because they have very similar stories. In New York, users expect for their offense to help them get over the obstacles their own defense may impose them and make it, or at least fight for, the playoffs. Simulations, however, say otherwise, putting NY in 6th on average.
For San Jose, it’s the exact opposite. There is a consensus that San Jose’s roster, that serious lacks on-field cohesion, will battle it out to be the worst team of the ASFC. Simulations, however, say otherwise. They say the SaberCats are very much still in playoff contention, and are more likely to end up in the top half than the top bottom.
As far as AD is concerned, San Jose takes a slight advantage with 2.39, slightly over New York’s 2.29. They are, together with NOLA and the next team in this list, the only teams to reach an AD over 2.
Prediction: One will go to the playoffs, the other will finish 6th. Who is going to do what is a literal coin toss.
• ( Chicago). The only NSFC team to have an AD above 2, this comes as a surprise for many. Some would argue that Chicago’s recent success and attempts to build a great roster should still carry them over to the playoffs in a team firmly dominated by a few teams, who should easily secure the first 3 spots. Others also wonder if Chicago’s regression and lack of depth may finally show up this season. Simulations, however, confirm these fears. They are expected to finish as many as 2 wins below the playoffs. If you believe simulations, that is.
Prediction: If anyone in the NSFC is going to raise some eyebrows this season, it’s Chicago.
I said I would also reflect on a specific point of my previous statistical analysis, so if you only wanted my tips and predictions, you can skip this part. But I feel obligated to point this out.
One of my major fears was that a sample of only 50 predictions would be way too little to make an accurate representation of the general public’s opinion, especially when there were more than 300 entries available per season. When expanding my analysis to triple the entries, with 150, I expected to confirm this. I did not. Only two teams changed standings, which were NOLA (who fell from 4th to 5th) and Orange County, who took NOLA’s place, and not much changed after.
I would add that further research can certainly be done using a more concrete data value, such as predicted wins and actual wins, and the same or similar method can be used to reflect on regular season and playoff predictions. I do not expect to be doing them until a couple of weeks into the regular season, if at all, so I would certainly encourage those who are just as nerdy as I am to conduct similar experiments and analyses as I have over these past few days.
I also received several positive messages on my last post, so I would like to thank all of you who have read both that and this post, and I hope to help you out to crush those regular season predictions!