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Schedule Analysis – Juniata
This will be my third schedule analysis and this time the focus is on defending champion, Juniata. My Latvians were able to find their schedule and it should be interesting to see what they are planning as they replace most of their team while at the same time trying to extend their unbeaten win streak. As I did last time, here is a little reminder of what I’m doing here.
This series attempts to look at schedules through an NCAA Power Index (NPI) viewfinder and evaluate them on an NPI basis. Ned has gifted me an Excel sheet that allows me to plug in the 2025 schedule of a team and see how it would do if they were playing the 2024 versions of their opponent. From this, I can see what their max NPI would theoretically be (with an undefeated season) and how their spread of opponents look when examining their NPIs. I can even play some what-if games with wins and losses. Remember, when looking at 2024 NPIs, that a win gives you a match NPI that is about 10 points higher while a loss will give you 80% less. If we assume the at-large bid cut-line will be around 59.5 NPI then this means any team above 50 NPI will be beneficial with a win. The Quality Win Bonus (QWB) is set to 55.5 in women’s volleyball so most of the opponents between 55 and 60 will also give you a QWB. In doing these simulations, just know that I do not feed in the results and alter team’s NPIs. Most importantly, 2024 NPIs will not equal that team’s NPI in 2025. If you want that information, someone will have to learn to look into the future.
I’m still not 100% sure what information from this series will be important so I’m starting with the table below. Calvin was the first team I analyzed followed by ETBU and here is their summary. My hope is to draw some conclusions after doing a number of these.
(Loss n = Simulated losses against NCAA Tournament teams above the at-large cut-line.) (Loss a = Simulated losses that causes the team to use all of their 50+ NPI results.) (Max L = Maximum number of losses to their best opponents and stay above the at-large cut-line.)
Juniata had another undefeated season and finished with the best NPI number (that we’ll ever see?) at 77.77. They won the Automatic Qualifier (AQ) from their conference but, as I said, were the top team when it came to NPI. The Juniata schedule has 29 matches over 21 play dates (out of an allowed 22 dates).
Here is their spread of opponents across the NPI range:
60+…8 opponents
55-60…9 opponents
50-55…8 opponents
Less than 50…4 opponents
My first impression of this schedule is pretty darn impressive. This is basically the ETBU schedule except they replaced 4 low NPI matches with 5 elite teams. Again, impressive. We know that Juniata will not be the same team as they’ve had in the last few years. I mean they are graduating almost everyone. I think we can also say, with some confidence, that they will still be pretty good because they can recruit and, well, it’s Juniata. With the Calvin and ETBU schedules, I was concerned with the number of low NPI matches but this one, I’m probably concerned with the number of elite teams scheduled. There is a lot of risk for a team that will need to get their feet under them. With that said, has Juniata ever not won the AQ in their conference? Teams that dominate their conference can take more risks with scheduling.
With this schedule, Juniata has 25 matches that will be useful in the NPI game. That’s 5 more than ETBU and 9 more than Calvin. Remember, no team wants to start using the wins against the low NPI teams because it will drag their NPI towards or below the at-large cut-line.
Alright, let’s get to the numbers and the maximum NPI with this schedule is 75.92. That’s below their 2024 number but, by far, the best maximum we’ve seen with the first three schedules. That number would be good enough for second last year…behind Juniata.
The next NPI number we want to calculate is what would happen if Juniata lost to all of the NCAA Tournament teams they will play that were above the 2024 at-large cut-line. Those teams would be Cortland, Ithaca, Marietta, Transylvania, Chris Newport, Johns Hopkins, Franklin & Marshall, Millikin, UW-Oshkosh and Carnegie Mellon. Yikes! That’s 10 losses. With those simulated losses, the Juniata NPI would be around 58.82 (Loss n), which is slightly below the anticipated cut-line. This is the worst “Loss n” number of the three teams but also the most losses that are absorbed. To compensate for the 10 losses, all of the other 15 good opponents (results) are used.
The last simulation is using all of the matches against teams that are 50 NPI or higher. With Calvin, they had 16 so I had them get 6 losses. With Juniata and their 25 good NPI matches, it would mean 15 losses against 10 wins. I’m to the point on these really good schedules that this is just pointless to figure out. I mentioned above that I wasn’t sure what is useful or not and I’m thinking this isn’t too useful in this case.
What is useful, I think, is trying to figure out how many losses can be absorbed while still making the cut-line. Their “Loss n” was 58.82 so I think we just need to switch one of those wins. Sure enough, if I reverse their worst-best loss (in this case, Transylvania), it takes Juniata to 59.70 and above the cut-line. That is nearly double the losses (9) what ETBU can absorb and over double for Calvin. That’s a lot of wiggle room but for this young team, they will probably need it.
Let’s look at the table from the top and include Juniata.
The first two schools had very similar schedules with ETBU’s being slightly more difficult. Junita ramps the difficulty up to an 11 (Spinal Tap reference) and they are rewarded with a higher maximum NPI and more losses that can be absorbed (“Max L”). They also have a lower “Loss n” if they just flat out struggle against the top teams. What this probably means is that the Calvin and ETBU schedules are more NPI friendly in that their floor still gets them into the tournament. The big caveat, however, is that none of these simulations consider a big upset or unexpected loss. That changes the NPI game. If that happens to Calvin, they don’t have a lot of wiggle room to make it up. If it happens to Juniata, it can be absorbed with an elite win or two. Another important Latvian supplied tidbit is that last year teams that finished with a 60+ NPI only lost to a team with an NPI less than 55 ten times. That was out of 496 matches for a percentage of only 2%.
Now time for some more in-depth thoughts on the Juniata schedule before we get some comments from Juniata Head Coach Heather Pavlik.
My only concern, which I alluded to above, is whether this schedule overloads this young team. It’s not an NPI schedule and is pretty much what Juniata played last year. Their Opponent NPI Average is 0.561 compared to their 2024 average of 0.566. So, slightly easier but still much tougher than both Calvin’s and ETBU’s. When I’ve discussed scheduling in the past with respect to NPI, I’ve wondered if the elite teams would back off what they’ve done in the past (with the previous selection criteria) or keep it business as usual. Juniata chose the latter. I don’t see a universe where Juniata doesn’t win their AQ so some pressure is off and the tougher schedule will ensure the team is ready for the NCAA Tournament. I think this is an important consideration when comparing schedules. Teams that are virtually locked into an AQ can ignore NPI and do what they think is best to get their team ready. Neither Calvin or ETBU or locked into their AQ so NPI has to be considered more. Other than those points, I really can’t complain about the Juniata schedule. The only low NPI teams are from conference. To be safer, I might have taken two elite teams and swapped them out for two 50+ NPI team but, again, that’s not really required for Juniata who should get their AQ.
Since I have you here, let’s do some Juniata housekeeping. The Eagles have won a DIII record 97-straight matches without a loss. The all-time NCAA record is held Penn State at 109. To get to the record, they have to beat some impressive teams; Cortland, Ithaca, Marietta, Transylvania, Chris Newport and Johns Hopkins. In fact, that Johns Hopkins match would be needed for their 109th win. Franklin & Marshall away would be for their 110th. One final note before I turn you over to the coach is that Juniata will be having their ring ceremony tonight. I just want to add my congratulations to this amazing team and thank them for the wonderful volleyball memories. I have had the great pleasure of watching the team in person the last two Elite 8s and championship matches. It will not surprise me to see this new Juniata team in Bloomington come December.
Here is Coach Pavlik on their schedule this year:
Question: Did you factor in NPI when constructing your schedule? Or did you just try to schedule the best teams possible?
Answer: “I did think a little about NPI mostly from the standpoint of making sure that we could have 10-12 good wins on our schedule but more importantly, I wanted to make sure that we have strong enough matches to force this very young team to get better so that we can control our own destiny by winning the automatic bid. So, in the end, some of both!”
Q: Did you have any trouble finding opponents to play you?
A: “Yes, this was the worst year ever for scheduling. There were numerous sites where we could go play another top team but nobody wanted to play two perceived top teams so I had to schedule the same weekend three different times. It took until this spring to finish our home schedule as well. Not sure why some people did not want to play us considering we are going to be so young.”
Q: Your only low NPI matches (teams less than 50 NPI) are conference matches. Did you try to avoid scheduling teams below 50 NPI?
A: “I don’t think that we avoided teams below 50 but tried to schedule good teams but not make the schedule so strong that our young group would be overwhelmed but, in the end, they need to learn to how to compete with and beat good opponents.”
Thanks to Heather for the responses. We’ve got our 3rd baseline in the system as we search for the perfect NPI schedule. This one was quite different and provides a new insight on how teams that may have a lock on their AQ will go about their business of scheduling.
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