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Inside The Data: What Does A Projection Model Forecast For The Eagles In 2026? · Inside the Birds: A Philadelphia Eagles Podcast

• 0:09
  Speaker 1: Hello, everyone. Welcome to Inside the Data on Inside the Birds.
• 0:13
  Speaker 1: I'm Jeff Mosher. And of course, we have Sam Finkel
• 0:16
  Speaker 1: with us.
• 0:16
  Speaker 2: And listen, we are just now a couple of days
• 0:20
  Speaker 2: away from the Eagles opening up their season against the
• 0:22
  Speaker 2: Washington Commanders at the link. And what Sam did was
• 0:27
  Speaker 2: he wanted to confuse everybody by throwing some strange model
• 0:30
  Speaker 2: at them.
• 0:30
  Speaker 1: No, just kidding, Sam. What we're going to get into.
• 0:33
  Speaker 2: Is statistical analytical data that projects the record for the
• 0:41
  Speaker 2: Eagles and also win probability against all their opponents, along
• 0:46
  Speaker 2: with some other things that we'll get into in the podcast.
• 0:49
  Speaker 2: And this is going to require, Sam, from you, a
• 0:52
  Speaker 2: little bit of an explanation on what is called the
• 0:55
  Speaker 2: Monte Carlo simulation model, the number of simulations, and then,
• 1:00
  Speaker 2: of course, why probability might change from one opponent to another,
• 1:05
  Speaker 2: even if it's the same opponent.
• 1:06
  Speaker 1: In a different week. So what was your impetus behind
• 1:09
  Speaker 1: doing this specific project?
• 1:12
  Speaker 3: I wanted to, that was, no, I, I went through
• 1:17
  Speaker 3: a couple, uh, you know, ideas and, uh, I, I
• 1:21
  Speaker 3: kind of settled on just, I've always wanted to, you know,
• 1:24
  Speaker 3: map out how like a simulated run through the season
• 1:27
  Speaker 3: a bunch of times based on certain wind probabilities and
• 1:29
  Speaker 3: kind of see how it does. Uh, this admittedly, this
• 1:32
  Speaker 3: is the first time I've ever built one of these models.
• 1:34
  Speaker 3: So this is going to be kind of fun to
• 1:36
  Speaker 3: talk about. Um, I do know about them obviously, but
• 1:39
  Speaker 3: I just, I think it's fun to actually build.
• 1:42
  Speaker 1: Yeah, sure.
• 1:43
  Speaker 3: Sure.
• 1:43
  Speaker 1: So explain your process.
• 1:44
  Speaker 2: First of all, explain itself, the Monte Carlo simulation model
• 1:49
  Speaker 2: and explain the process that you went through to come
• 1:52
  Speaker 2: up with win probability against all the opponents and for
• 1:55
  Speaker 2: the season.
• 1:56
  Speaker 3: Yeah. So essentially it's just like running through, um, some
• 2:00
  Speaker 3: sort of, it's getting the expected value out of, out
• 2:03
  Speaker 3: of a basically random samples. It takes a subset of
• 2:07
  Speaker 3: samples and it tries, it averages them to get the
• 2:09
  Speaker 3: expected value. That's essentially what it is. So this one, I,
• 2:13
  Speaker 3: I essentially, uh, use the Eagle season and I did,
• 2:17
  Speaker 3: did a thousand times, a random sample, a thousand times
• 2:20
  Speaker 3: an average amount. So first I gave the Eagles and
• 2:23
  Speaker 3: each of their opponents a strength rating based on the
• 2:26
  Speaker 3: betting market. projections, which all have the Eagles around 10
• 2:29
  Speaker 3: and a half wins. So I will disclaim that later.
• 2:33
  Speaker 3: It'll make sense. But this kind of gave an estimate
• 2:36
  Speaker 3: how good each team would be on a neutral field.
• 2:39
  Speaker 3: So that's kind of the baseline there. And then for
• 2:42
  Speaker 3: every game, I compared the Eagles rating with their opponent's
• 2:45
  Speaker 3: rating and adjusted for whether it was home, away, or
• 2:48
  Speaker 3: a neutral site. And that produced a projected point spread. Uh,
• 2:53
  Speaker 3: and then I converted that by multiplying it by a
• 2:55
  Speaker 3: multiplier to get a win probability. Instead of simply, uh,
• 3:01
  Speaker 3: saying that the Eagles will win a game. Uh, so
• 3:03
  Speaker 3: like when you'll see the model there's for the game
• 3:06
  Speaker 3: week one, uh, there's a 71.4% win probability against the commanders. Um,
• 3:11
  Speaker 3: it just means that like seven out of every 10 simulations,
• 3:14
  Speaker 3: that's kind of how it came up. Um, and then
• 3:17
  Speaker 3: I simulated the entire season, a thousand times using those
• 3:21
  Speaker 3: game by game probabilities. And that allows us to see
• 3:24
  Speaker 3: the Eagles average projected record, the records occur, which ones
• 3:28
  Speaker 3: occur most frequently and the probability that they reach each benchmark.
• 3:31
  Speaker 3: I have a couple on there like 10 plus 11
• 3:34
  Speaker 3: plus 12 plus et cetera. And right now the model
• 3:37
  Speaker 3: projects 10.5 wins.
• 3:40
  Speaker 2: Oh, you're getting, Oh, you're getting ahead here. I just
• 3:42
  Speaker 2: wanted to understand. I like you're saving the good stuff
• 3:45
  Speaker 2: for later.
• 3:46
  Speaker 3: Yes, but I think it's important to say it now
• 3:49
  Speaker 3: because for one reason, one reason I think it's important.
• 3:52
  Speaker 3: And again, I will get into that, but the reason
• 3:55
  Speaker 3: I think it's important is because that is what the
• 3:57
  Speaker 3: market says, right? So it's really important to caveat that it,
• 4:02
  Speaker 3: it agrees with the model and the only, and the
• 4:04
  Speaker 3: model is certainly influencing it, but based on the independent,
• 4:07
  Speaker 3: it can be somewhat circular is what I'm saying is
• 4:10
  Speaker 3: because I used as an input that 10.5 number and
• 4:14
  Speaker 3: then adjusted it for each matchup. So it kind of,
• 4:17
  Speaker 3: it's biased by that model. That's, that's the reason I
• 4:19
  Speaker 3: think it's really important to say now, um, the model
• 4:23
  Speaker 3: still supports that 10 and a half is a fair
• 4:25
  Speaker 3: starting point. So it's like a market calibrated baseline that,
• 4:28
  Speaker 3: that essentially started with.
• 4:30
  Speaker 1: Right.
• 4:30
  Speaker 3: And from that baseline, the math doing the season a
• 4:34
  Speaker 3: thousand times. And after converting each of their opponent scores,
• 4:37
  Speaker 3: it still ends up about where the market is, which
• 4:39
  Speaker 3: is the only reason I thought it was important to
• 4:41
  Speaker 3: kind of bring up now.
• 4:43
  Speaker 1: Okay. Makes sense. Where, where are, cause we like to
• 4:46
  Speaker 1: be objective with everything we do.
• 4:48
  Speaker 2: Where are the flaws in the model besides the obvious,
• 4:51
  Speaker 2: like if you lose your, Starting quarterback for 16 games
• 4:54
  Speaker 2: or a season, you know, that's going to impact your
• 4:57
  Speaker 2: win projection for sure.
• 4:58
  Speaker 1: But are there any other areas that the model has flawed?
• 5:01
  Speaker 3: Yeah, I mean, there's a there's a couple of ways.
• 5:03
  Speaker 3: That's a really big one. There's certain things like, you know,
• 5:07
  Speaker 3: especially later in the season, bench players, weather is not
• 5:10
  Speaker 3: affected in this at all. That's a big one. And
• 5:13
  Speaker 3: it's hard to project this far out. I would say, again,
• 5:17
  Speaker 3: the fact that I used, you know, the projected win
• 5:20
  Speaker 3: loss and strength of schedule from I really debated using
• 5:24
  Speaker 3: last year's win loss record. But again, it's just it's
• 5:28
  Speaker 3: too hard to attribute, especially when there's coaching changes. And
• 5:32
  Speaker 3: it's it's giving a lot of credit to the betting markets,
• 5:35
  Speaker 3: which I don't typically love to do.
• 5:38
  Speaker 1: Yeah, that's fair.
• 5:39
  Speaker 3: So I do want to, which is why I thought
• 5:41
  Speaker 3: that 10 and a half was really important to say
• 5:43
  Speaker 3: in the beginning, because that is a huge flaw with
• 5:45
  Speaker 3: this because it's, it's reliant on that assumption. Also, it
• 5:51
  Speaker 3: only has a certain number of assumptions, right? It has,
• 5:54
  Speaker 3: you know, I didn't use that many variables. I could
• 5:56
  Speaker 3: have used a bunch of variables, but it doesn't have
• 6:00
  Speaker 3: that many variables. So, and there are so many variables
• 6:03
  Speaker 3: in the game of football. So I think that that's
• 6:06
  Speaker 3: a really, you know, anything that you can think of
• 6:08
  Speaker 3: that affects a football game that day, that week. Yeah.
• 6:13
  Speaker 1: A breakout player, right?
• 6:14
  Speaker 2: I mean, you can't, a breakout player could have a huge,
• 6:17
  Speaker 2: like a Jackson Smith and Jigba last year for the Seahawks.
• 6:20
  Speaker 2: We knew he was a first round pick and was
• 6:21
  Speaker 2: a good player, but you know, he had almost 1700,
• 6:24
  Speaker 2: almost 1800 yards himself.
• 6:26
  Speaker 3: Right.
• 6:27
  Speaker 2: So those are some things that are probably difficult to
• 6:30
  Speaker 2: be predictive with, with some of the modeling when you're
• 6:32
  Speaker 2: just talking about overall, um, team success because individual breakouts
• 6:36
  Speaker 2: can influence hugely team success.
• 6:39
  Speaker 1: Quarterbacks, especially.
• 6:40
  Speaker 3: Or regression.
• 6:42
  Speaker 1: Or regression. Right. Same point. Same point. Yep. Okay. Good stuff.
• 6:46
  Speaker 1: We'll bring up the charts in a second. One other question. Oh, yeah.
• 6:50
  Speaker 2: So like when you run these models a thousand times,
• 6:54
  Speaker 2: you're obviously not using an abacus. We're in the world
• 6:56
  Speaker 2: of computers. How long does all that take?
• 6:58
  Speaker 3: It didn't take me that long because there's a computer program.
• 7:02
  Speaker 1: Random generator. Okay. Great stuff. Fantastic. All right.
• 7:07
  Speaker 2: I will bring up all the hard work that you
• 7:10
  Speaker 2: have done here. It's great for our friends on YouTube
• 7:15
  Speaker 2: can follow along.
• 7:16
  Speaker 1: Oh, that is not the one.
• 7:18
  Speaker 3: Okay. I will say, I apologize for, you know, saying
• 7:23
  Speaker 3: the conclusion this early, but for our listeners, but there's
• 7:26
  Speaker 3: more exciting stuff.
• 7:27
  Speaker 1: Oh, there's, yeah, there's way more.
• 7:29
  Speaker 3: Absolutely. Okay. I just think it's important to caveat model flaws,
• 7:34
  Speaker 3: et cetera. So for sure, for sure.
• 7:37
  Speaker 1: All right. So we're going to, I'll try to.
• 7:39
  Speaker 2: Shrink this to get to the whole schedule on one screen, right?
• 7:43
  Speaker 2: The Monte Carlo simulation model. Why is it called that.
• 7:46
  Speaker 1: By the way?
• 7:47
  Speaker 3: That I, I'm not a hundred percent sure. Uh, I remember,
• 7:53
  Speaker 3: it's actually so funny. My dad gave me his textbooks
• 7:57
  Speaker 3: from when he was in college. And I remember he
• 8:00
  Speaker 3: has a statistics textbook and that was one of the
• 8:02
  Speaker 3: first models I ever read about. So I've always wanted
• 8:04
  Speaker 3: to do one. And I'm really glad I got to
• 8:07
  Speaker 3: apply it here.
• 8:09
  Speaker 1: As well, as well as our week.
• 8:12
  Speaker 2: So you have each opponent by week where the game
• 8:16
  Speaker 2: is being played. And in the right column is the
• 8:20
  Speaker 2: win probability that you have color coded.
• 8:22
  Speaker 3: I do.
• 8:23
  Speaker 1: You have dark green, light green, red.
• 8:27
  Speaker 2: And do you want to go with like beige or yellow?
• 8:29
  Speaker 1: How do you see that?
• 8:31
  Speaker 3: Yeah, it's yellow. And then there's an orange one as well.
• 8:35
  Speaker 1: Oh, yeah. The orange one as well.
• 8:37
  Speaker 2: So how did you decide which colors were going to
• 8:41
  Speaker 2: signify what?
• 8:42
  Speaker 3: Yeah. I mean, anything under 50% was going to be red.
• 8:45
  Speaker 3: Anything in the 50%. to, you know, 59.9% is going
• 8:50
  Speaker 3: to be, you know, orange. Anything in the 60% is
• 8:54
  Speaker 3: going to be yellow. Anything over like 70% is green.
• 8:59
  Speaker 3: And then anything that was like close to 80 or higher,
• 9:01
  Speaker 3: I wanted to do darker green. I probably should have
• 9:05
  Speaker 3: kept the Cardinals game to lighter green, but I just,
• 9:07
  Speaker 3: I wanted to highlight it. So I kept it.
• 9:10
  Speaker 1: Gotcha.
• 9:10
  Speaker 2: So basically anything yellowish to green to dark green is
• 9:14
  Speaker 2: an assumed win.
• 9:15
  Speaker 1: For the Eagles, right?
• 9:17
  Speaker 3: Yeah. The probability for sure.
• 9:19
  Speaker 1: Right. According to the computers, we'll say.
• 9:20
  Speaker 3: According to the computer.
• 9:21
  Speaker 1: Four, five, six. And then, so that would be seven, eight.
• 9:24
  Speaker 1: Not like you said.
• 9:25
  Speaker 2: Well, I believe there's 11 of those games that in
• 9:28
  Speaker 2: general have that color, right?
• 9:30
  Speaker 3: Right.
• 9:31
  Speaker 2: And then there's the four reds that we'll get into
• 9:33
  Speaker 2: in a second. The one orange, that's five. That's a
• 9:37
  Speaker 2: 55 percenter, right?
• 9:39
  Speaker 1: Which is close. And am I missing one? One, two, three, four.
• 9:42
  Speaker 1: So it's also, I'm sorry. So there must be Well,
• 9:45
  Speaker 1: the Colts one is blue. No, that's a green.
• 9:48
  Speaker 3: It's green. Yeah.
• 9:49
  Speaker 1: Green, dark green. I guess there were 12 then between.
• 9:52
  Speaker 3: That would make sense. Yeah. Yeah. 12.
• 9:55
  Speaker 1: And then the, okay. And then the five were under 50%.
• 9:57
  Speaker 3: Okay. Or 55%.
• 9:57
  Speaker 1: And under, I should say.
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• 12:33
  Speaker 1: Interesting. Really interesting. I like how you did that there.
• 12:38
  Speaker 2: We can go through them really quickly, but my first
• 12:40
  Speaker 2: question would be, okay, why would the model say that
• 12:44
  Speaker 2: the Eagles are 71% chance to win on Sunday, week one,
• 12:49
  Speaker 2: against the Commanders? However, when they meet in week eight,
• 12:52
  Speaker 2: it's down to 60% chance. That's an 11% drop. I
• 12:55
  Speaker 2: understand that it's at Washington, right? And you did say
• 13:00
  Speaker 2: home road will factor in, but What else would lead
• 13:02
  Speaker 2: for that to be an 11% difference?
• 13:06
  Speaker 3: That is the largest factor in there. It certainly is. Because, again,
• 13:13
  Speaker 3: I didn't use that many variables. So it's pretty easy
• 13:16
  Speaker 3: to determine where the swings come from. And it really
• 13:19
  Speaker 3: just factored in that home away split. And that's a
• 13:23
  Speaker 3: big part of it.
• 13:24
  Speaker 1: Gotcha.
• 13:25
  Speaker 2: So week one, week two, Commanders, then at Titans. They
• 13:28
  Speaker 2: have a 71% win probability against the Commanders. only a
• 13:33
  Speaker 2: 66% win against the Titans. I would, I think that
• 13:37
  Speaker 2: I would even think that the market, the models would
• 13:40
  Speaker 2: think the commanders would be better than the Titans this year.
• 13:43
  Speaker 2: So I assume that that six point differential isn't bigger
• 13:48
  Speaker 2: because it's in Nashville.
• 13:50
  Speaker 1: Yeah.
• 13:50
  Speaker 3: That again, the home away split is probably over exaggerated
• 13:54
  Speaker 3: in this model, but again, it's only because I didn't
• 13:56
  Speaker 3: use that many variables. So it's, it's one of the,
• 13:59
  Speaker 3: there's a reason that the swing would be there. It
• 14:02
  Speaker 3: would be interesting if I flipped it. I wonder what
• 14:04
  Speaker 3: it would be. Probably almost 80% against the Titans, I'd imagine.
• 14:11
  Speaker 2: As we move on, it's not great. What the models
• 14:14
  Speaker 2: say about the Week 3 and Week 4 stretch at
• 14:17
  Speaker 2: Chicago followed by the Rams Week 4. I think Chicago
• 14:21
  Speaker 2: is the Monday night game?
• 14:22
  Speaker 1: I know it's a night game, right?
• 14:23
  Speaker 3: By the way, does the.
• 14:24
  Speaker 1: Shortened week.
• 14:29
  Speaker 2: Or days of rest, does that factor all into, is
• 14:34
  Speaker 2: that just all potentially factoring into the betting markets?
• 14:38
  Speaker 3: It's probably factored into the betting markets. One would implicit
• 14:42
  Speaker 3: in the model, but I really didn't use that many
• 14:45
  Speaker 3: variables just because I wanted to get something out that's
• 14:47
  Speaker 3: pretty easy and digestible. But yeah, I mean, it probably
• 14:50
  Speaker 3: will affect, I mean, it definitively will affect you know,
• 14:54
  Speaker 3: the performance of the players, but it's not, it's implicit
• 14:56
  Speaker 3: in the model because it's in the wind totals, but
• 14:59
  Speaker 3: it's not actually a variable in the model itself.
• 15:02
  Speaker 1: Right.
• 15:02
  Speaker 2: So interestingly, the models had the Eagles at two and oh,
• 15:05
  Speaker 2: but then two and two theoretically after four games with
• 15:08
  Speaker 2: losses to.
• 15:09
  Speaker 1: The bears and the Rams.
• 15:10
  Speaker 2: And then they don't have a predicted under 50% or
• 15:15
  Speaker 2: even under 55% until we get to week 12. So that's, that's,
• 15:19
  Speaker 2: it's like kind of a rough start, but then a
• 15:21
  Speaker 2: nice smooth sailing there in the middle.
• 15:23
  Speaker 3: Theoretically. I mean, if you ran this in the 1,000 times,
• 15:27
  Speaker 3: it happens in the attributed percentages times.
• 15:31
  Speaker 1: Right. I mean, you did run this 1,000 times.
• 15:33
  Speaker 3: I did. I did run this. I have the numbers
• 15:36
  Speaker 3: if we're ever curious about it. We just pull a
• 15:37
  Speaker 3: random sample.
• 15:39
  Speaker 2: Oh, like give me an example of what you mean.
• 15:41
  Speaker 2: Like the Rams, like how many of the 1,000?
• 15:43
  Speaker 3: Yeah. So if you want to like 972, they start off,
• 15:48
  Speaker 3: they win the first game, lose the second, win the third,
• 15:51
  Speaker 3: lose the fourth. lose the fifth when that's a pretty
• 15:56
  Speaker 3: bad model. They only had eight wins in that model,
• 15:58
  Speaker 3: but still, I mean, I have the actual numbers. So
• 16:02
  Speaker 3: if you want to pick a random number.
• 16:04
  Speaker 2: I wouldn't even know where to start. I almost say you,
• 16:06
  Speaker 2: you pick one that you found was interesting.
• 16:09
  Speaker 3: I mean, there, there was one model. I mean, when
• 16:12
  Speaker 3: we ran it the 13th time, the Eagles start out one, two, three, four, five,
• 16:17
  Speaker 3: six and oh, uh-huh. They lost the seventh game against
• 16:23
  Speaker 3: the Cowboys. They won the eighth and then they kept
• 16:27
  Speaker 3: going alternating and then they finished off the season. Five
• 16:34
  Speaker 3: and one. So, I mean, it finished 13 wins on
• 16:38
  Speaker 3: the season. It's one of the better model 13. I mean,
• 16:42
  Speaker 3: simulation 13 produced 13 total wins.
• 16:45
  Speaker 1: Go figure.
• 16:47
  Speaker 3: I don't know. There's a bunch. I mean, it ranges
• 16:50
  Speaker 3: pretty heavily. I mean, I think I have the, when
• 16:54
  Speaker 3: we go lower in the chart, it'll say, but I
• 16:57
  Speaker 3: think the most wins I had on there was 16.
• 17:00
  Speaker 1: Oh my God.
• 17:02
  Speaker 3: And it happened 0.1% of the time.
• 17:04
  Speaker 2: Okay.
• 17:05
  Speaker 3: And the lowest I think I had was four wins.
• 17:08
  Speaker 3: And that also happened 0.1% of the time.
• 17:11
  Speaker 1: Interesting. All right.
• 17:13
  Speaker 2: Then I'm really interested to get to that part where
• 17:15
  Speaker 2: we say what the models say about their likeliest number
• 17:19
  Speaker 2: of wins and losses.
• 17:21
  Speaker 1: We already kind of covered that a little bit.
• 17:22
  Speaker 3: Well, because that's what the Monte Carlo is good at, right?
• 17:24
  Speaker 3: It takes what your expected value is, right? I mean,
• 17:28
  Speaker 3: it models it a thousand times and then averages the outcomes.
• 17:32
  Speaker 3: That's really what the model does.
• 17:35
  Speaker 1: Right. All right.
• 17:36
  Speaker 2: As they get into the second part of their schedule,
• 17:38
  Speaker 2: weeks five, six, seven, eight, Jags in London, then the Panthers,
• 17:43
  Speaker 2: then the Cowboys at home, both of those at home,
• 17:45
  Speaker 2: and then at the Commanders again. Crazy how they finished
• 17:48
  Speaker 2: off the Commanders in the first eight weeks when they
• 17:50
  Speaker 2: didn't even play them until week, what, 16 last year.
• 17:54
  Speaker 2: But the models all look good in those. Now, the
• 17:58
  Speaker 2: Panthers one is a little more lopsided, over 70%. Jags, Cowboys, Commanders,
• 18:03
  Speaker 2: all around 60%, which is.
• 18:05
  Speaker 1: Why you have a little bit. You don't have that green.
• 18:07
  Speaker 2: You have that light yellow color because those are kind
• 18:11
  Speaker 2: of coin. 60% is not exactly like a commanding. convincing
• 18:14
  Speaker 2: percentage exactly it's all within that coin flip range they
• 18:17
  Speaker 2: have a lot of coin flips which is why you
• 18:19
  Speaker 2: know this the models.
• 18:21
  Speaker 3: Come out weird the simulations itself run that come out
• 18:23
  Speaker 3: a little bit weird sometimes.
• 18:25
  Speaker 4: Sure um all right that that home game by the
• 18:30
  Speaker 4: way just to as to go off our last conversation
• 18:33
  Speaker 4: they're a 61 win probability against the cowboys in philly
• 18:39
  Speaker 4: so you can imagine what it would be like as
• 18:41
  Speaker 4: we get a little lower when it's in Dallas, it's
• 18:43
  Speaker 4: going to change because we've seen already.
• 18:46
  Speaker 1: That's a big difference here in, in how the wind
• 18:48
  Speaker 1: probability comes out. All right.
• 18:51
  Speaker 2: Then, then it's kind of a weird, take your pick
• 18:54
  Speaker 2: right from nine, 10, 11, 12, and 13. You got
• 18:59
  Speaker 2: home versus the giants home versus Steelers at the Cowboys
• 19:02
  Speaker 2: at the Cardinals home versus Colts. And we have literally
• 19:06
  Speaker 2: every single color option here in there.
• 19:11
  Speaker 1: Yeah.
• 19:11
  Speaker 2: So that's like, that really becomes a, whereas week, weeks
• 19:15
  Speaker 2: one through four, you know, it looks a little bit
• 19:17
  Speaker 2: more cut and dried per percentages.
• 19:19
  Speaker 1: Weeks five, six, seven, eight, same thing.
• 19:21
  Speaker 2: You're feeling good about the, at least being favored in
• 19:24
  Speaker 2: every game based on the percentages.
• 19:27
  Speaker 1: Then nine, 10, 11, 12, 13. It's like, it could be,
• 19:30
  Speaker 1: it's a whole different world there.
• 19:32
  Speaker 3: Yeah, absolutely.
• 19:35
  Speaker 2: Any one of those percentages that really stick out or
• 19:38
  Speaker 2: jumped out to you?
• 19:39
  Speaker 3: Well, I think week 13 against the Cardinals is interesting
• 19:43
  Speaker 3: because it's an away game, and yet they're still the
• 19:46
  Speaker 3: highest projection. So it just shows. that the markets are
• 19:50
  Speaker 3: not very favorable to the Cardinals this year, which is
• 19:54
  Speaker 3: not particularly shocking.
• 19:57
  Speaker 1: Right.
• 19:57
  Speaker 2: If it were a home game, that game might be
• 20:00
  Speaker 2: closer to like 90%.
• 20:02
  Speaker 3: Easily could it be, for sure. I will say that
• 20:07
  Speaker 3: the Eagles strike the schedule, at least based on last
• 20:10
  Speaker 3: season is 16th. So I just, I think that's worth
• 20:14
  Speaker 3: saying just at this point, just because it's interesting to
• 20:18
  Speaker 3: see how this model would have affected other teams. You know,
• 20:20
  Speaker 3: I think the Cowboys have a tougher schedule. If I
• 20:23
  Speaker 3: remember correctly, when I was looking at it. So, I mean,
• 20:26
  Speaker 3: and I think the NFC East has around that range
• 20:30
  Speaker 3: around like, I think 12 to 20 something. So, yeah. Yeah.
• 20:36
  Speaker 2: Yeah. You know, the Cowboys kind of got hurt. In
• 20:39
  Speaker 2: a weird way because of their second-place schedule. Some would
• 20:42
  Speaker 2: argue that their second-place schedule is tougher than the Eagles'
• 20:45
  Speaker 2: first-place schedule because teams like the Ravens last year finished
• 20:48
  Speaker 2: in second place. I think the Bills finished in second
• 20:51
  Speaker 2: to the Patriots. Who finished second in the NFC North?
• 20:57
  Speaker 1: It was the Bears won it. Was it the Packers?
• 21:01
  Speaker 3: I think it was the Packers, yeah.
• 21:02
  Speaker 2: Yeah, I think it was the Packers, which is never
• 21:04
  Speaker 2: an easy opponent by any stretch. And the Rams finished second.
• 21:09
  Speaker 2: in the NFC West, if I'm not mistaken, to the Seahawks.
• 21:11
  Speaker 2: So you have a lot of second-place teams there that
• 21:14
  Speaker 2: it's like, oh, man, those are not easy teams right there.
• 21:17
  Speaker 3: At all. At all.
• 21:18
  Speaker 2: All right, as we go into the bottom part of
• 21:23
  Speaker 2: the schedule, Colts week 14, Seahawks week 15, Texans 16,
• 21:29
  Speaker 2: at Niners, at Giants 17, 18, it looks like the
• 21:33
  Speaker 2: models are saying– I'm surprised the models give them such
• 21:36
  Speaker 2: an edge over the Colts. At 71%, I thought that
• 21:39
  Speaker 2: would be something in the 60s, a little higher than
• 21:42
  Speaker 2: I thought, Sam.
• 21:43
  Speaker 3: Yeah, me too. I wonder what the win total is
• 21:45
  Speaker 3: projected for the Colts. I have the raw data somewhere. Sure.
• 21:53
  Speaker 3: Colts are around 7.5. Seven and a half wins.
• 21:57
  Speaker 1: Okay, so all right. I mean, that's fair.
• 22:00
  Speaker 2: So if the models say the Colts are only a
• 22:02
  Speaker 2: seven and a half win team and it's in Philly,
• 22:04
  Speaker 2: you could see why it would be a 71%.
• 22:06
  Speaker 1: Winning percentage. Niners at Niners under 50%. We know that's
• 22:12
  Speaker 1: always a, that's a tough road trip. It's a good team.
• 22:14
  Speaker 1: What is the Niners win projected total for the market?
• 22:18
  Speaker 3: Let's take a look.
• 22:19
  Speaker 1: I'm going to guess nine and a half.
• 22:24
  Speaker 3: You should be a betting man. It's exactly that. Nice.
• 22:29
  Speaker 1: Texans 60. Texans is well, it's at home.
• 22:33
  Speaker 2: So obviously if that game– these are one of the
• 22:35
  Speaker 2: beige games or the light yellow games where the home
• 22:38
  Speaker 2: road splits really matter because if it was in Houston,
• 22:41
  Speaker 2: it would probably be a red game for the Eagles.
• 22:44
  Speaker 3: 100% would be, yeah. What are the Texans winning total?
• 22:50
  Speaker 2: I would say– I'm going to say 11.5. 9.5.
• 22:55
  Speaker 1: Wow. Okay. I guess I'm not a betting man.
• 22:58
  Speaker 3: Well, I mean, stick with the NFC. You'll be all right.
• 23:01
  Speaker 1: Yeah, I guess so.
• 23:03
  Speaker 2: And then, of course, the season ends at the Giants.
• 23:06
  Speaker 2: That's going to be fascinating. I really do think it's
• 23:08
  Speaker 2: going to be an interesting game. I think the Giants
• 23:10
  Speaker 2: are going to hover around the 500 mark for a
• 23:15
  Speaker 2: lot of the year and just be decent enough so
• 23:18
  Speaker 2: that maybe week 18 for them could mean a wild
• 23:22
  Speaker 2: card berth.
• 23:25
  Speaker 3: Yeah.
• 23:25
  Speaker 2: You know, like they might be a game out or–
• 23:29
  Speaker 2: but they need two other teams to lose. Also, you know,
• 23:32
  Speaker 2: I could see that the race for the seventh seed
• 23:34
  Speaker 2: has been pretty interesting for the last few years.
• 23:37
  Speaker 3: Yeah. I mean, their win total projection is also is
• 23:40
  Speaker 3: seven and a half.
• 23:42
  Speaker 2: Right.
• 23:42
  Speaker 3: So, I mean, it's not terribly far off, but I
• 23:45
  Speaker 3: don't know. I think the thing is, I think if
• 23:47
  Speaker 3: it's going to be a team from the NFC East,
• 23:49
  Speaker 3: that's not the Eagles like in that spot. I don't
• 23:52
  Speaker 3: think it's the giants. I, I, I, feel more comfortable
• 23:56
  Speaker 3: saying it's the Cowboys.
• 23:57
  Speaker 1: I would agree. I would agree. It's more likely the Cowboys.
• 24:00
  Speaker 3: All right.
• 24:01
  Speaker 2: So who among the Eagles opponents does have the highest
• 24:05
  Speaker 2: projected win total?
• 24:06
  Speaker 1: And why is it the Rams?
• 24:09
  Speaker 2: Well, I mean, maybe I should ask who has the
• 24:12
  Speaker 2: second highest behind the Rams.
• 24:14
  Speaker 3: Well, the Rams are at 11 and a half. And
• 24:17
  Speaker 3: you think about it. I mean, they have made some huge, huge,
• 24:22
  Speaker 3: acquisitions and unretirements on that defensive line. And they're, they're
• 24:29
  Speaker 3: a pretty exciting team. So I think that's a big
• 24:32
  Speaker 3: part of it. Who is the second highest? That's a
• 24:34
  Speaker 3: good question.
• 24:35
  Speaker 1: On the Eagle schedule.
• 24:36
  Speaker 2: I would think by this chart, it would be the
• 24:40
  Speaker 2: bears or the, well, maybe the, maybe the Niners.
• 24:43
  Speaker 3: So the bears, Cowboys, Niners, and Texans are all tied.
• 24:48
  Speaker 3: I wonder if it's the former Superbowl champions. It is. Oh, yeah.
• 24:54
  Speaker 1: That makes sense.
• 24:55
  Speaker 3: Yeah. Okay. Yeah.
• 24:56
  Speaker 2: Makes a lot of sense.
• 25:01
  Speaker 1: All right. Good stuff.
• 25:03
  Speaker 2: Let us go on to some of the other things
• 25:06
  Speaker 2: that you put together that are really fascinating. We've got
• 25:08
  Speaker 2: the model summary, right? Which tells us expected wins and losses,
• 25:12
  Speaker 2: which we covered a little bit. And then also probability
• 25:16
  Speaker 2: of each number of wins.
• 25:18
  Speaker 1: I love this. This is great. Let's go with the
• 25:21
  Speaker 1: left side. Explain the left side here.
• 25:23
  Speaker 3: Yeah, I mean, the expected wins is that expected value
• 25:27
  Speaker 3: that the model projected, right? And then the expected losses
• 25:30
  Speaker 3: is just, you know, the subtraction from the actual games.
• 25:34
  Speaker 3: It's pretty easy. But basically what it's saying is that
• 25:37
  Speaker 3: it averaged all the outcomes of the 1,000 and the
• 25:40
  Speaker 3: average expected wins is 10.5, which again is what was
• 25:45
  Speaker 3: projected by most of the betting platforms anyway. And then
• 25:50
  Speaker 3: what's interesting is the most common record for them was
• 25:53
  Speaker 3: 11 and six. So out of all of them, like
• 25:57
  Speaker 3: that's the most frequent, the mode, it's what comes out.
• 26:01
  Speaker 3: The expected value is lower than that, but the most
• 26:05
  Speaker 3: frequent one was 11 and six.
• 26:07
  Speaker 1: Hey, it makes sense.
• 26:07
  Speaker 2: Adam and I, you know, we did our projections the
• 26:11
  Speaker 2: other day and we try to, you know, give our guesses.
• 26:14
  Speaker 1: And I think he, I came at, I kept saying
• 26:17
  Speaker 1: I'm stuck between.
• 26:17
  Speaker 2: 11 and 12 wins and, you know, so 11 and
• 26:19
  Speaker 2: six and, and 12 and five.
• 26:22
  Speaker 1: And that's kind of where I see it.
• 26:24
  Speaker 3: And again, there are some biases in the model that
• 26:26
  Speaker 3: we already talked about that are definitely impact this number,
• 26:29
  Speaker 3: but I do think it's a reasonable, you know, model
• 26:34
  Speaker 3: modeling of this. What I think is interesting though, is
• 26:36
  Speaker 3: there's these benchmarks that I created, which are like the
• 26:39
  Speaker 3: chance of 10 plus wins, the chance of 11 plus wins,
• 26:42
  Speaker 3: chance of 12 wins. And so when you look at
• 26:45
  Speaker 3: 10 plus, it gives it almost a 70% probability based
• 26:48
  Speaker 3: on those probabilities that we had above and based on
• 26:51
  Speaker 3: when it ran it the 1,000 times. The 11 plus,
• 26:56
  Speaker 3: it goes down to about 51%. Right. And it drops
• 26:57
  Speaker 3: even more. Then it goes to 30% and then it
• 26:59
  Speaker 3: goes to 15%. Yeah. 13. But if you were to
• 27:01
  Speaker 3: look at it differently, you would say.
• 27:11
  Speaker 2: The models say they have a 45% chance of winning
• 27:14
  Speaker 2: at least 12 games, right?
• 27:18
  Speaker 3: A 45% chance.
• 27:20
  Speaker 1: Well, no, I can't do it that way.
• 27:22
  Speaker 2: So I was sort of combining the percentage of winning
• 27:25
  Speaker 2: 12 or more games at 31% and the percentage of
• 27:29
  Speaker 2: winning 13 or more at 15% and adding them together,
• 27:32
  Speaker 2: thinking that you could then say you got a 45,
• 27:35
  Speaker 2: but I.
• 27:35
  Speaker 1: Don't know if it works that way.
• 27:36
  Speaker 3: No, it doesn't.
• 27:37
  Speaker 1: No, unfortunately it doesn't.
• 27:39
  Speaker 2: But I do think this, I mean, you might have the,
• 27:41
  Speaker 2: the information in front of you, I don't know how
• 27:43
  Speaker 2: many teams have a 15.7% chance of winning 13 or
• 27:47
  Speaker 2: more games.
• 27:49
  Speaker 3: That's very fair. Yeah.
• 27:51
  Speaker 1: I would say that they're on.
• 27:52
  Speaker 3: This model for a bunch of teams. Sorry to interrupt you.
• 27:55
  Speaker 1: Yeah, no, that's okay.
• 27:57
  Speaker 3: I was just saying, I didn't run this model for
• 27:59
  Speaker 3: other teams, but I can't imagine it would be that many.
• 28:02
  Speaker 1: Agreed.
• 28:04
  Speaker 2: I think obviously it goes without saying it's obvious, but
• 28:07
  Speaker 2: it is good to know if you're worried about doom
• 28:09
  Speaker 2: and gloom, according to your model's projections, the.
• 28:13
  Speaker 1: Eagles winning three or fewer games is at.
• 28:20
  Speaker 2: 0.0%, four or fewer at 0.1%, and five or fewer
• 28:24
  Speaker 2: at 0.8%.
• 28:25
  Speaker 1: So if you're worried about the Eagles having a year
• 28:27
  Speaker 1: like the Commanders.
• 28:28
  Speaker 2: Had last year, it would be one of the most
• 28:31
  Speaker 2: unpredictable phenomenons ever.
• 28:34
  Speaker 3: Yes. Yeah. Based on this model itself and based on
• 28:38
  Speaker 3: all the markets and everything, it's... almost it would be
• 28:43
  Speaker 3: a crazy scenario it just would it's unlikely very very
• 28:46
  Speaker 3: unlikely right catastrophe must have to happen so sure.
• 28:50
  Speaker 2: And so what do you see as their biggest win
• 28:52
  Speaker 2: probability here yeah.
• 28:54
  Speaker 3: I think it's between 10 and 11 right so i
• 28:57
  Speaker 3: mean 11 was the was the mode so that's at
• 29:00
  Speaker 3: a 20.2 percent but i think as you can see
• 29:03
  Speaker 3: between 10 and 11 seems to be kind of the
• 29:06
  Speaker 3: big split i could see it Honestly, anywhere from 9
• 29:10
  Speaker 3: to 12 is reasonable. I do think 10 or 11
• 29:13
  Speaker 3: makes the most sense to me.
• 29:15
  Speaker 1: Got it. Awesome.
• 29:16
  Speaker 2: And for those who really have big, big expectations of
• 29:19
  Speaker 2: an undefeated season, 0.0% chance the Eagles are doing that
• 29:23
  Speaker 2: and just a 0.1% chance of winning 16 or more. Hey, though,
• 29:28
  Speaker 2: there is a 4.2% chance of 14 or more wins.
• 29:32
  Speaker 3: That's true. That's true. I think.
• 29:33
  Speaker 2: The way I know Eagles fans and the way I've
• 29:35
  Speaker 2: seen some predictions, I think they there would be more
• 29:38
  Speaker 2: if you pulled like a thousand eagles fans and ask
• 29:41
  Speaker 2: them what the record is you'd get more than 4.2
• 29:43
  Speaker 2: percent saying 14 or more wins i just.
• 29:46
  Speaker 3: Suspect that i suspect that too but again models don't
• 29:49
  Speaker 3: play football right they're just a good approximation but they
• 29:52
  Speaker 3: don't play football like that has to be said too.
• 29:55
  Speaker 1: Right So this is now in bar graph form.
• 29:58
  Speaker 3: Same thing.
• 30:00
  Speaker 1: Yeah. Same thing.
• 30:01
  Speaker 2: And it just shows you that the 11 win mark
• 30:03
  Speaker 2: is the highest at close to 20%. 10 win mark
• 30:06
  Speaker 2: is right around there at 19%. And you know, the
• 30:10
  Speaker 2: zero win mark, you don't even see any bar because
• 30:12
  Speaker 2: it's 0%.
• 30:12
  Speaker 1: Yeah.
• 30:14
  Speaker 3: Awesome.
• 30:15
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• 31:14
  Speaker 1: So this is really interesting. Good stuff. I will wonder.
• 31:20
  Speaker 2: If people feel validated, feel good, feel bad about a
• 31:25
  Speaker 2: projection of somewhere around 11 wins, you know, 10 to
• 31:27
  Speaker 2: 11 wins. I mean, I think expectations are a little
• 31:31
  Speaker 2: higher winning the Superbowl two years ago, but I also
• 31:34
  Speaker 2: think people realistically understand that there's some newness here, especially
• 31:38
  Speaker 2: with the offense. There's some offensive line health questions and
• 31:42
  Speaker 2: that you don't have to win 13 or more games
• 31:45
  Speaker 2: to be in the Superbowl.
• 31:47
  Speaker 1: Right. It sure helps, but.
• 31:51
  Speaker 3: No one was complaining about that.
• 31:53
  Speaker 1: What about, what was your thought after you finished doing
• 31:56
  Speaker 1: the data here?
• 31:58
  Speaker 3: Yeah. I mean, I just, I thought it was reasonable.
• 32:02
  Speaker 1: Like what did you, what was your project prediction for
• 32:05
  Speaker 1: the Eagles in 2026? I, I would.
• 32:08
  Speaker 3: Have thought 12 wins. I would have felt pretty good
• 32:11
  Speaker 3: about that. But I I'm comfortable with this model and
• 32:15
  Speaker 3: the projections. But also understanding that, again, it is a
• 32:19
  Speaker 3: circular model, right? It's relying on that ten and a
• 32:21
  Speaker 3: half win total to some extent. So I do understand
• 32:26
  Speaker 3: Vegas doesn't know everything, but they do know a lot.
• 32:29
  Speaker 3: And that's why they take a lot of money from
• 32:31
  Speaker 3: people either way. But I would have probably if I
• 32:36
  Speaker 3: had to guess, I would have guessed it would be
• 32:37
  Speaker 3: a little bit on the higher side. In this model,
• 32:40
  Speaker 3: my personal prediction probably will be a little bit higher
• 32:44
  Speaker 3: than the model, but I'm very comfortable with where this
• 32:46
  Speaker 3: model put.
• 32:48
  Speaker 2: Are you uncomfortable with your own self-projection of 13 or
• 32:52
  Speaker 2: more wins?
• 32:54
  Speaker 3: I would be uncomfortable with more than 13. I think
• 32:58
  Speaker 3: 13 is doable. I think the Eagles could easily, I mean,
• 33:03
  Speaker 3: not easily, they could do that. I think anything over
• 33:06
  Speaker 3: that is unlikely. yeah possible but unlike possible it.
• 33:11
  Speaker 2: Just it's a big difference because you know 11 to
• 33:13
  Speaker 2: 12 feels like a team that will be in the
• 33:16
  Speaker 2: divisional round if not the conference championship 13 and more
• 33:20
  Speaker 2: wins feels like a team that should be in the
• 33:22
  Speaker 2: super bowl right like definitely in the conference championship and
• 33:26
  Speaker 2: good shot to be in the super bowl so.
• 33:28
  Speaker 3: A hundred percent and the thing is they just they
• 33:31
  Speaker 3: have some tough stretches right like that that's to me
• 33:34
  Speaker 3: like I think their coin flips, they could stack, right?
• 33:37
  Speaker 3: Like if they lose both week three and week four,
• 33:40
  Speaker 3: that doesn't feel great. And then you can lose momentum.
• 33:43
  Speaker 3: Like there are other factors in there. But if they
• 33:45
  Speaker 3: split the coin, like there's just a couple of really,
• 33:48
  Speaker 3: really tough stretches on the schedule that I just don't
• 33:52
  Speaker 3: see them coming out unscathed. I just don't think there's
• 33:55
  Speaker 3: a world where they win all the games in the
• 33:57
  Speaker 3: tough stretches. And it wouldn't be the Eagles without losing
• 34:01
  Speaker 3: a game that they seemingly should win.
• 34:04
  Speaker 2: I think i think to your point weeks five six
• 34:07
  Speaker 2: seven and eight where they have three coin flip games
• 34:10
  Speaker 2: and then um i guess a gimme with the panthers
• 34:13
  Speaker 2: at 71 but jag 60 percent cowboys 61 and at
• 34:19
  Speaker 2: commanders at 60 uh is it going to be very
• 34:22
  Speaker 2: telltale for this yeah i think we'll know a lot
• 34:25
  Speaker 2: and like you said you win more than you lose
• 34:27
  Speaker 2: and if you can if you can quote unquote uh
• 34:30
  Speaker 2: win one of those projected losses against either the Rams
• 34:33
  Speaker 2: or the bears, but you win, like you said, you
• 34:34
  Speaker 2: stack some, some quite flip games.
• 34:37
  Speaker 1: You're good. If it's the reverse, you're not, you're, you're
• 34:40
  Speaker 1: really hoping that things pick up.
• 34:41
  Speaker 3: In the second half. Absolutely. And I just think a
• 34:44
  Speaker 3: lot of this depends on how this new offense operates.
• 34:48
  Speaker 3: If the defense can perform where they were last year.
• 34:50
  Speaker 3: I mean, there's a lot of things that there, there
• 34:53
  Speaker 3: are things that need to be worked out and, you know,
• 34:56
  Speaker 3: they really didn't, play any, obviously any starters in the preseason.
• 34:59
  Speaker 3: So there's going to be a little bit of a
• 35:02
  Speaker 3: slower start potentially. I think that that's a fair, we
• 35:04
  Speaker 3: talked about it in another episode. You've talked about it,
• 35:07
  Speaker 3: you know, in separate podcasts. It's just, it's, it'll be interesting.
• 35:11
  Speaker 3: There's a lot of unknowns.
• 35:14
  Speaker 1: For sure. All right. This is exciting.
• 35:16
  Speaker 2: This, this announcement, because next week, when you hear from
• 35:20
  Speaker 2: Sam and I, you're going to have actual real live
• 35:24
  Speaker 2: game data from, and game data coverage and analytics to
• 35:27
  Speaker 2: go through because we'll be not only will there be one,
• 35:30
  Speaker 2: but there'll be two inside the days next week. One
• 35:33
  Speaker 2: is going to recap the season opener against the commanders.
• 35:36
  Speaker 1: And the next one will preview their week two game
• 35:40
  Speaker 1: against the Titans. So this is it.
• 35:42
  Speaker 2: This is the last of the conjecture analytics pods. We
• 35:45
  Speaker 2: will have real tangible football to go.
• 35:49
  Speaker 1: Over with from an analytics level. And I'm really excited
• 35:51
  Speaker 1: for it.
• 35:52
  Speaker 3: Me too.
• 35:53
  Speaker 1: All right, great for Sam Finkel. I'm Jeff Mosher. You've
• 35:57
  Speaker 1: been watching Inside the Data on Inside the Birds, and
• 35:59
  Speaker 1: we will catch you on the next one.