We discussed pace of play in my last strategy session, and since that time, the games with the highest projected paces of the night have finished in 6-4 (CAR-MON) and 6-5 (WSH-CAR) finals. Hopefully this is something that makes you go “hmm…”.
Let’s look at how – if at all – a team playing back-to-back has their pace affected at all. I don’t know what the results will show, as I’m diving into this for the first time myself, but there are a handful of teams playing B2B tonight, so I thought it’d be a great time to find out!
B2B Going From Road to Home
Tonight’s teams playing road > home B2B: Washington, Colorado
I have started work on a database of team records and GF/GA in B2B appearances since the start of 2016. I have compiled about 95% of all B2B games played.
When a team plays on the road, and then travels home to play the next night – with the data I have compiled – teams have a record of 93-63-19…wow.
Teams in this spot actually have a better record than the average in this spot. All told, these team’s average 2.9 GF/game, which is exactly the same as the average in all games since the start of 2016-17.
Team’s playing in this situation are only allowing 2.7 GA/game though, 0.2 lower than the league average.
The team playing back-to-back in these situations seems to have a slight advantage – crazy. Let’s see how pace is affected – for this exercise, let’s use just the top-10 highest-paced teams.
These teams have played 11 games going road to home. The average sum of CF and CA in these games was 124.3 – which is a bit higher than the ten teams’ average sum of 119.2.
This likely needs a larger sample than 11 games, but early indications would suggest that the games in these scenarios are actually a bit faster, with the team playing back-to-back actually having a slight advantage.
B2B Going From Home to Road
Tonight’s teams playing home > road B2B: Detroit, New Jersey
Since the start of 2016-17 – using the data I have available – teams playing back-to-back, going from home to road, have a combined record of 94-89-34. We can see that these teams actually do have a losing record, as opposed to teams going road to home.
The B2B teams score an average of 2.7 goals per game, slightly lower than the league average, while allowing 2.9 goals against per game – which is right on par with the league average. Let’s see how pace has played out in these games thus far in 2018-19.
There have only been 6 games thus far for the top-10 highest paced teams in this scenario, and the average sum of CF + CA has been 117.3 in these games.
This is, obviously, an extremely small sample, but the pace has been just a tad slower in these games. All of the data seems to indicate that going from home to road is slightly harder for teams, and they have struggled a bit in this situation over the years.
B2B Road Games
Tonight’s teams playing B2B on the road: Ottawa
Since the start of 2016-17 – using the data I have compiled thus far – teams playing back-to-back on the road, having played an away game the night before as well, have a combined record of 156-161-48. The team playing B2B has only won 42.7% of games in these situations – but how is the score affected?
The teams playing B2B have only managed 2.4 goals per game in this situation – that is a half-goal less than the league average. Surprisingly, though, these teams have allowed 2.9 goals against per game – right on par with the league average.
This seems to suggest that team’s playing B2B may be at a disadvantage offensively, but they shouldn’t necessarily be targeted defensively, as they are allowing the same amount of goals against as any other situation. So how has pace been affected in road B2B’s?
The top-10 highest paced teams have played in 21 road B2B games, and their average pace has been 120.3 – which is just slightly higher than the 119.2 average pace of these teams.
Some more testing could go into this, for sure, but pace surely doesn’t seem to be affected by B2B games THAT much.
The biggest thing I am taking from this is the old myth about targeting teams playing on a road B2B. For at least three seasons, there has not been any statistical advantage to that approach.
Perhaps you should avoid rostering players from the teams on the B2B, but I will be eliminating the targeting of these teams moving forward.