Advanced Stats Matchup Analysis
- 2017 Michigan at Indiana
Behold, the latest installment of the new and improved Advanced Stats (S&P+) Matchup, this time featuring Michigan at Indiana.
This matchup analysis draws upon the Advanced Stats Profiles published weekly by Bill Connelly on Football Study Hall. The profiles feature Connelly’s well-known Five Factors, and also include the more detailed groups of S&P+ metrics that break down elements of the game such as Rushing and Passing, as well as the down-and-distance scenarios known as Standard Downs and Passing Downs. As you may recall from last season, this matchup analysis was presented in the form a somewhat lengthy table listing the 26 metrics (this season it’s only 20), with a column of metrics for the offense and defense for each team. Derived from these two pairs of metrics were two more columns of matchup metrics, which when compared would indicate which team held a net advantage in that metric. It was a lot to digest, and in the end, it failed to really provide a qualitative characteristic of how great (or negligible) an advantage was that a team held in any metric relative to the other metrics. To that end, this new approach seeks to display the matchups graphically, in a way that more clearly distinguishes and gauges the significance of any net advantages. For more details regarding the definition of and concepts behind each of the metrics, the Advanced Stats Glossary is a handy reference to bookmark.
Beginning next week, I’ll just have a link back to this boilerplate section. If you’ve read previous installments of this diary, the only new thing is in the Turnover Margin section. Otherwise, you can skip ahead to the Matchup Analysis below.
This section describes the approach to analyzing Bill Connelly’s base metrics, the formulation for deriving the matchup metrics and the format for the charts. None of this is etched in stone, and certainly suggestions for improving any of the aspects of the methodology are welcome and appreciated!
The analysis evaluates metrics that are applicable to both offensive and defensive units of two competing teams, such that a set for a given metric consists of five values: Team A Offense, Team A Defense, Team B Offense and Team B Defense, and the National Average. From this set, two matchup values are derived. The first matchup value is “Team A Offense vs. Team B Defense," which as it states gauges the competitive performance of the Team A offense against the Team B defense. The resulting matchup value is then normalized to a matchup between two average teams, so a relative comparison can be made with the opposing team’s result, as well as with matchups for other metrics.
The first matchup value is determined by simply taking the product of the Team A offense and Team B defense metrics, divided by the national average for the given metric. The second matchup value is in turn computed in the same way for the Team B Offense versus the Team A Defense. Once the two matchup metrics are determined, the team with the higher value when on offense will have a net advantage for that metric, with the exception of three categories: "Stuff Rate", "Standard Down Sack Rate" and "Passing Down Sack Rate". These are termed contra-metrics for the purposes of this diary. A contra-metric gauges the offense's ability to avoid the given categorical description. Akin to a contra-asset in the accounting vernacular, with these metrics, a lower value is better.
The one factor or metric that does not conform to this principle of geometric scalability described above - because it is predominantly a random variable with a zero mean - is Turnover Margin. The Expected Turnover Margin can be positive or negative, and depends on measureable statistics like fumbles and passes defended. The difference between the Expected and Actual values is the measure of a team’s luck. The matchup metric for Turnover Margin is just the difference between the two teams Expected Turnover Margins.
The charts are arranged according to the groupings in the table above. All of the base metric numerical data, as well as matchup values, are embedded in the individual metric charts in the small table at the bottom. Metrics for each team’s Offense, Defense, and its Offense versus the opponent’s Defense are read across the designated row in the table. The same data is also depicted visually in chart graphic. Along each side is a vertical line plotted between two color-coded and shape-coded markers. The vertical line on the left side is for “Team A Off. vs. Team B Def.”, where the circle (or “O”) marker designates the value for the offense. Likewise, the diamond marker designates the value for the defense. The markers are in turn color coded according to the particular team’s colors. So you will notice that the color-coding is consistently reversed between the left and right sides across the charts. A third, horizontal dash marker designates the value for the composite matchup between the given offensive and defensive values, as determined by the formulation noted above.
Next is the block in the center of the graphic. The block simply gives emphasis to the vertical difference between the matchup values (the horizontal dash markers) on the left and right vertical lines. The blocks are in turn color coded according to the team whose offense corresponding to the greater matchup value.
Also included in each chart is a horizontal dashed line showing the FBS National Average value for each metric. This is the value to which the matchup values have been normalized.
Last - and this is where the rubber meets the road in setting up this visualization approach – is the Y-axis scaling across the charts (ignoring Turnover Margin, for which this does not apply). You may notice that a logarithmic scale has been applied, and this is because its better suited to reflect the geometric normalization that’s in play here (e.g. 2 times the average will have the same vertical offset as 1/2 of the average, just in the opposite direction). So what’s going on here is that the bounds of the vertical scale for each chart are set to the same multiple of the FBS National Average of each particular metric. For example, the maximum values for the first four charts are set to 6 times the FBS Average values. Likewise, the minimum values are pegged to 1/6 of the FBS Average values, so in the end, the plus or minus percentage range is the same for each chart relative to the FBS average for that chart.
From there, you can just eyeball the blocks, and easily observe which team has the advantage in which matchups, and evaluate whether the matchups are relatively close, as well as where there is potential for a mismatch.
Michigan at Indiana Matchup Analysis
So, on with the matchup analysis!
The Five Factors Matchups
Here are the matchups for the core Five Factors metrics that compose the actual S&P+ ratings from which the game scoring margin is derived. As of the beginning of this week, that margin stands in favor of Michigan, at 6.6 points. Keep in mind a couple of things: the weightings of the factors into the predicted scoring margin are not uniform and, a team has control of only the first four. Of those first four, UM has an advantage in only two. UM also holds an edge in fifth and and least predictive factor. You can guess which one that is.
In Efficiency, the UM Offense is well below average, while the Indiana Defense is about average, which pulls down the UM Offense a bit more. On the other side, the Indiana Offense is below average, however, the UM Defense remains elite. In fact, it is Ranked #1 in this category! The net matchup gives a significant advantage to Michigan in Efficiency.
In Explosiveness, the UM Offense is about average, but the Indiana Defense is well above average, which pulls the UM Offense down to well below average. On the other side, the Indiana Offense is well below average, while the UM Defense is about average, which leaves the Indiana Offense about the same. The net matchup gives sizeable advantage for Indiana in Explosiveness.
As for Field Position, the UM Offense is below average, while the Indiana Defense is above average, pulling the UM Offense down to well below average. On the other side, the Indiana Offense is slightly below average, but the UM Defense is slightly above average, which pushes the Indiana Offense downward as well. The net matchup, however, is a slight Field Position edge for Indiana.
In Finishing Drives, the UM Offense is well below average, but the Indiana Defense is also below average, giving a slight boost to the UM Offenses. The key difference is UM’s Defense, however, which is well above average, matched against the Indiana Offense which is about average. The net matchup is a sizeable advantage for Michigan in Finishing Drives.
Both teams have a recent history of having poor Turnover Luck. The story of the season at this point is that both Indiana and Michigan’s TO Luck has lagged expectation based on measurables (e.g. Fumbles and Passes Defended). Most most pale in comparison to Michigan’s sorry luck. Setting luck aside however and just comparing the statistically-based expected turnover margins, Michigan is well above average (#9), while Indiana is well below average (#123). The net difference amounts to about 9.5 PPG. Thus, the net matchup is a significant advantage for Michigan in TO Luck.
Not to belabor each matchup as much as above, but here – in start contrast to the clean sweep Sparty had in this category last week - Michigan appears to have a net advantage in 4 out of 5 of the Rushing matchups, and most by a sizeable amount. The issues that the Wolverines are having with its Offensive Line should not be so glaring in this game. The only disadvantage for UM is in Explosiveness, which has to do with the RB’s ability, and not the OL’s.
Rushing Success Rate
In Rushing Success, both offenses are below average, as well as the Indiana Defense. The major difference is that UM’s Defense is elite (#3). The net matchup balance is a considerable advantage in Rushing Success for Michigan.
In Explosiveness, the UM Offense is about average, however the Indiana Defense is actually elite (#5) – a testament to their salty linebackers - which pulls the UM Offense down significantly. On the other side, the Indiana Offense is below average, while the UM Defense is just average. In the end, Rushing IsoPPP (Explosiveness) favors Indiana by a sizeable margin.
In Opportunity Rate, the UM Offense is well below average, while the Indiana Defense is slightly better, knocking the UM Offense down another notch. On the other side, the IU Offense is well below average and the UM Defense is well above average, which takes the IU Offense down even further. The net is a sizeable advantage for Michigan in Opportunity Rate.
Power Success Rate
In Power Success Rate, the UM Offense is actually well above above. Think “the Hammering Panda”, and that is what exemplifies Power Success. The IU defense is still above average, which takes the UM Offense down a peg. On the other side, IU Offense is also above average, however, the UM Defense is the elitist - ranked #1 in this metric – which takes the IU Offense down significantly. In the end, the matchup balance is a significant advantage for Michigan in Power Success Rate.
Last is Stuff Rate (a contra-metric). In this case, both offenses are close to average. The difference is in the defenses: the IU Defense is below average, while UM Defense is top ten. Think “space hogs” like Moe Hurst, with some Brian Mone sprinkled in. So, in the end, the matchup result is a considerable advantage for Michigan in Stuff Rate.
The Passing matchups are technically, split, but basically the net advantage here is well in Michigan’s favor.
Passing Success Rate
In Passing Success Rate, the UM Offense is below average, OK? Also, the IU Defense is above average, OK? OK, so that takes the UM Offense down a notch further. No worries. Not a big deal. The reason is because, even though the IU Offense is about average, the UM Defense is, once again, the elitist (ranked #1 in this metric). The scuttlebutt is that the IU Offense is obliterated into nothingness, Simmie Cobbs or no Simmie Cobbs. Lavert Hill promises to pull a Jourdan Lewis on that action, and you’ll see Hill’s name all over PFF next week. The net is a significant advantage for Michigan in Passing Success Rate.
Just a quick reminder on the Explosiveness metric: it only applies to successful plays. So, if a team has 10 successful plays, 3 of which happen to be explosive, then that’s your 30% Explosiveness. The Dudes Abide.
In Passing IsoPPP (Explosiveness), the above average UM Offense is brought down by the slightly more above average IU Defense. On the other side, the well below average IU Offense is boosted by the well below average UM Defense. The net matchup result is a negligible advantage for Indiana in Passing IsoPPP.
Standard Down Matchups
Michigan captures 3 of the 4 Standard Down matchups with Indiana, with UM’s only disadvantage coming in Explosiveness. It was noted above but is worth repeating that UM’s defensive scheme under Harbaugh, and under Don Brown in particular, is typically weak in the Explosiveness metric, and it’s not a bad thing. What’s important is that it is usually offset by a strong Success Rate metric, which means that although the explosive plays given up may tend to be large, they are a very infrequent. Think of it as the “good cholesterol” symptomatic of an aggressive defense.
SD Success Rate
In SD Success Rate, the UM Offense is well below average. Do you always have the sense that this offense is always “behind the chains”? Well, there you go. The IU Defense is perfectly average, so the status of the UM Offense is preserved. On the other side, the IU Offense is below average, while the UM Defense is elite (#2), which brings the IU Offense down significantly. The net matchup result is a considerable advantage for Michigan in SD Success Rate.
In SD Explosiveness, the UM Offense is below average, while the IU Defense is above average, which pushes the UM Offense further down. On the other side, the IU Offense is well below average, but the UM Defense is also below average, making the IU Offense look slightly better. The net matchup result is a sizeable advantage for Indiana in SD Explosiveness.
SD Line Yards per Carry
In SD LYPC, the UM Offense is below average, and the IU Defense is about average, leaving the UM Offense about the same. On the other side, the IU Offense is well below average, while the UM Defense is elite (ranked #3) and pushes the IU Offense down significantly. The net matchup result is a significant advantage for Michigan in SD Line Yards per Carry.
SD Sack Rate
In SD Sack Rate (a contra-metric), the UM Offense is significantly below average, while the IU Defense is even worse, which lowers the UM Offense effective Sack Rate. On the other side, the IU Offense is well below average, but the UM Defense is elite (ranked #3), which pushes the IU Offense up as well. In the end, the net matchup result is an overwhelming advantage for Michigan in SD Sack Rate.
Passing Down Matchups
Last, but certainly not least, are the Passing Down matchups, which are split between Michigan and Indiana, with some indications that UM may need to be concerned about its pass protection in Bloomington.
PD Success Rate
In PD Success Rate, the UM Offense is above average while the IU Defense is top ten, which pulls the UM Offense down considerably. On the other side, the above average IU Offense is still obliterated by the elitist UM Defense (ranked #1). The net matchup result is a sizeable advantage for Michigan in PD Success Rate.
In PD Explosiveness (IsoPPP), here again the UM Offense is above average, but the IU Defense is well above average and pulls the UM Offense down considerably. On the other side, the IU Offense is about average, as is the UM Defense, which leaves the IU Offense about the same. The net matchup result is a negligible advantage for Michigan in PD Explosiveness.
PD Line Yards per Carry
In PD Line Yards per Carry (LYPC), the UM Offense is above average, while the IU Defense is about average, which boosts the UM Offense up a smidge. On the other side, the IU Offense is above average, but the UM Defense is well above average, which takes the IU Offense down a notch. The net matchup result is a slight advantage for Michigan in PD LYPC.
PD Sack Rate
In PD Sack Rate (a contra-metric), as everyone should know by now, the UM Offense is well below average, while the IU Defense is top ten, which pushes the UM Offense up even higher. On the other side, the IU Offense is above average, but is negated by the UM Defense, which is well above average. Still, the net matchup result is a significant advantage for Indiana in PD Sack Rate.
So at this point you may still have some mixed feelings about this, another mixed bag of metrics matchups. Overall, UM has the advantage in all the categories of metrics, if not each metric. Yet, the margin for this game is roughly 6 points narrower than last week’ matchup with Sparty. How can that be? Well, the difference is essentially attributable to the change in home field advantage. Beyond that, UM has, in the aggregate, the same statistical advantage as was thought it had over Sparty.
So how does UM beat the same caliber of team on the road that it failed to beat at home? Simple: don’t turn the ball over. One of the most significant characteristics of this time is in its expected turnover margin. These are turnovers that one would expect the average team to gain based on UM proficiency in defending passes, and inducing the other team to to put the ball on the ground. Alas, the variance of this metric is quite wide, with Michigan being on the negative end of that distribution so far this season.
The matchups also suggest that Michigan’s rushing game is not a complete dumpster fire, at least, not in going up against Indiana. The matchups suggest that UM’s OL should be able to provide nominal gains to the second level for UM ball carriers. Beyond that, however, all bets may be off. The matchups also suggest that UM is good at getting short yardage when it matters, so playing with four downs in mind instead of three could be a key strategy is some situations, and may accentuate other avenues for success such as leveraging PD LYPC, which would entail running the ball on a passing down. At the same time, this would simultaneous mitigate UM’s disadvantage in PD Sack Rate, which entails passing the ball on a passing down.
Conversely, UM has one of its biggest advantages in SD Sack Rate, which suggests that it would be safer for UM to pass the ball on a standard down, since the risk of being sacked would be much lower. These metrics bear out that the OL is better at blocking and keeping the quarterback clean on standard downs than it is on passing downs. So a key element to that end will be to feature more play action, and more use of the blocky-catchy types in the form of mobile protection, if not screens and swing passes.
So, that concludes this week’s Five Factors Matchup Analysis!
Yours in football, and Go Blue!