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Analysis of the Top Teams

Posted at 2:09 pm on February 20, 2013

Jennifer Jones Rachel Homan and Heather Nedohin
There are three teams in a dead heat at the Scotties. At the mid-point in the tournament, Ontario, Team Canada, and Manitoba all boast a perfect record in this year’s Canadian championship. With each team posting such great results, it’s hard to tell if anyone has an edge as the playoffs approach. So, we dug a little deeper to explore underlying trends that may reveal this year’s most likely champion.

At this point, Manitoba is leading the way in shooting percentage. With a team average of 85%, Jennifer Jones and company have been the most impressive squad on the ice so far. Ontario and Team Canada aren’t far behind, with team averages of 82% and 83%, respectively. So does this mean Jones has the best shot heading in to the playoffs?

Not necessarily. We dove into the Percent Trends for these top teams and saw some teams rise to the top.

Q: What in the world is Percent Trends?

A: Whenever we look at averages, we’re seeing a single overall number that describes how a team is playing. But it doesn’t reveal whether a team is heating up or cooling down. A player who starts the tournament strong (90%+) may settle back into a weaker rhythm, but because of the high numbers at the beginning of the week, their overall average stays high. The reverse is also true. A player with a poor start to an event may build momentum throughout the week and post higher numbers that aren’t revealed in their overall average.

Team Manitoba’s front-end (Dawn Askin and Jill Officer) are cooling down. With incredibly high numbers at the beginning of the week (just under 90%), Askin and Officer had nowhere to go but down. As down on the graph below, the Manitoba front-end was dominating their competition early in the week and posted number much higher than Ontario or Team Canada’s front end. As the week chugged along, Manitoba’s numbers slipped back and, as of right now, sit roughly equal to their top competitors.

Ontario and Canada’s front-ends, however, are moving up. They’re making more shots now than they were at the beginning of the week.

Since front ends set up the game for their skips, this means that Jennifer Jones is likely going to be facing tougher shots than Rachel Homan or Heather Nedohin will, heading in to the playoffs. While Jones is known to make spectacular shots, as a general rule, you want to leave your skipper with the easiest shot possible. Over time, attempting tougher shots will yield more errors, putting Jones at a disadvantage over Nedohin and Homan.

Scotties Curling stats

Click for larger graph

When looking at the back-end (thirds and skips) for these three big dog teams, again a pattern emerges.

Jennifer Jones and Kaitlyn Lawes, forming the back-end of the Manitoba team, are on a steady decline. As mentioned before, when the front-end goes down, the back-end needs to clean up the mess. And the mess appears to be taking its toll on Jones and Lawes. Barring a change in this trend, we’re predicting the Manitoba girls to run out of steam during the playoffs and fail to make the finals.

Rachel Homan and Emma Miskew are showing a similar trend. While their decline isn’t as pronounced as the one by Manitoba, they are pointed in the wrong direction. The big advantage for Team Ontario, however, is that their front-end is bearing the load. They can afford for Homan to post some weaker numbers, because they’re keeping the ends clean so she’ll be more likely to be facing easier shots.

The team with the biggest statistical edge, however, is Heather Nedohin’s Team Canada. These girls started strong and are getting stronger. The back-end of this team started the week curling 76%, and have kicked in to high gear, climbing all the way up to 90%. Combine that trend with a front-end that’s moving in an upward direction, and Team Canada is one tough team to beat.

Based on these stats, we’re predicting a Homan and Nedohin final, with Nedohin having the best chance to win the 2013 Scotties.

back-end

Click for larger graph

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