Top Passers in the Big Ten

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Here’s the same type of viz I made earlier for servers.

Just because I was curious who the best passers were, relative to the league average for FBSO value provided by each reception quality. What you may immediately notice is that Nebraska has 3 of the top 4 passers in Albrecht, JWO, and Rolfzen. So for those who unabashedly declare Kelly Hunter the best setter in the Big Ten, just realize she’s dealing with great raw materials to work with.

Another insight that isn’t super insightful is that getting aced strongly correlates with your overall effectiveness as a passer, but anywhere from 1 to 5% reception error can still drop you in the upper echelon of passers in the Big Ten. Reception error has the strongest relationship to overall effectiveness out of all of the pass qualities which isn’t necessarily surprising. This makes sense since relative to the average FBSO eff, getting aced is the farthest from the mean. Even if you were expected to hit zero in FBSO, a perfect pass only raises you .300 points higher than that – but getting aced drops you more than 3x this distance, all the way to -1.00. And this is where coaches lose valuable insight. On a 3 point passing scale, the distance from 3 to 2 and 2 to 1 and 1 to 0 appears equal, but in reality a 3 and 2 are very very similar in terms of the value they provide your offense. On the other side, 1 and 0 point passes seem similar, but even on a 1 point pass you’re still getting a swing and hitting above .000 whereas for a 0 pass, you lost 100% of the point every time. This is why we use FBSO eff and breakdown passers in this fashion.

The distinction between passers who exhibit similar effectiveness yet different reception error is of course the breakdown of each quality. Below is this breakdown for the top 5 passers in the Big Ten in 2016.

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Because JWO passes so many balls perfectly, she can get away with having a slightly higher error rate. Albrecht passes the second lowest of the 5 perfectly…but is at 38% R+. Much like serving, each player has their unique footprint and the underlying factor is the value each type of pass brings to the table.

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Working from the perfect pass at the top, to the reception error at the bottom, these are the FBSO efficiencies for the Big Ten in 2016 on average.

The idea that is often overlooked by coaches is the insignificant difference between good and great when it comes to serve receive. The league as a whole is hitting .258 on passes with only 2 options. R! boils down to setting the ball from the 10-15 foot line to the Go or the Red. So while coaches may freak out that they’re losing their quick hitter option, it’s really not a huge deal when you glance at the numbers. Of course these relationships between reception qualities are unique to each team and the setter in your arsenal, but this trend is not uncommon.

This is why players who may not pass perfectly, but always get your team a swing are invaluable. These are the consistently medium players – just a really hard dead medium passer. They don’t pass nails, but they don’t get aced. That’s a big deal – and it’s currently underutilized because it’s undervalued because it’s misunderstood.

For those who are interested, here are how the teams overall shake out in the passing ranks from this season: Team – expected FBSO eff (rec. error%)

  • Nebraska – 0.211 (3.56%)
  • Wisconsin – 0.194 (3.41%)
  • Maryland – 0.188 (4.63%)
  • Penn State – 0.186 (4.64%)
  • Michigan – 0.177 (4.68%)
  • Minnesota – 0.170 (5.19%)
  • Michigan State – 0.157 (5.35%)
  • Indiana – 0.156 (5.86%)
  • Ohio State – 0.154 (6.26%)
  • Iowa – 0.150 (5.87%)
  • Illinois – 0.143 (6.50%)
  • Purdue – 0.136 (6.59%)
  • Northwestern – 0.112 (7.38%)
  • Rutgers – 0.072 (10.1%)

Again these are looking at each team’s passes in the context of what they are worth to the league as a whole, not just how each team hit in FBSO… (bravo, Maryland)

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