Genk vs FCV Dender EH Match Analysis
Expert Overview
The upcoming match between Genk and FCV Dender EH is anticipated to be an intriguing encounter. Genk, with a strong recent form, will be looking to capitalize on their home advantage at the Luminus Arena. FCV Dender EH, while not as formidable, has shown resilience in recent matches. Key tactical notes include Genk’s high pressing game and Dender’s reliance on counter-attacks. Injuries and suspensions are minimal on both sides, which should allow for a competitive match. The tempo is expected to be fast-paced, with Genk likely dominating possession.
Genk
FCV Dender EH
(FT)
Predictions:
| Market | Prediction | Odd | Result |
|---|---|---|---|
| Away Team Not To Score In 1st Half | 97.90% | (2-1) | |
| First Goal Between Minute 0-29 | 89.80% | (2-1) 10' min 1.83 | |
| Both Teams Not To Score In 1st Half | 72.80% | (2-1) 1-1 1H 1.20 | |
| Over 1.5 Goals | 72.60% | (2-1) 1.17 | |
| Under 5.5 Cards | 76.70% | (2-1) | |
| Sum of Goals 2 or 3 | 65.80% | (2-1) 2.10 | |
| Both Teams Not To Score In 2nd Half | 63.40% | (2-1) 1-0 2H 1.36 | |
| Under 4.5 Cards | 64.50% | (2-1) | |
| Avg. Total Goals | 2.95% | (2-1) | |
| Avg. Conceded Goals | 3.28% | (2-1) | |
| Yellow Cards | 1.20% | (2-1) | |
| Avg. Goals Scored | 1.18% | (2-1) | |
| Red Cards | 1.15% | (2-1) |
Match Result (1X2)
Data Signals
Genk’s recent form and home advantage make them the favorites to win. Their attacking prowess, coupled with Dender’s defensive vulnerabilities, suggests a likely victory for Genk. The betting odds reflect this expectation.
Risk Factors
The primary risk for Genk is complacency against a lower-ranked opponent. For Dender, the challenge lies in breaking down a well-organized defense.
Recommended Picks
A bet on Genk to win appears to be the most promising, given their strong form and tactical setup.
Draw No Bet
Data Signals
Given the disparity in quality between the two teams, a draw seems unlikely. Genk’s dominance in recent fixtures supports this view.
Risk Factors
Betting on a draw could be risky due to Genk’s superior attacking capabilities and home advantage.
Recommended Picks
Avoiding a draw no bet wager is advisable, considering the expected outcome.
Double Chance
Data Signals
A double chance bet covering both a win for Genk and a draw could mitigate some risk while capitalizing on Genk’s strong position.
Risk Factors
The main risk is underestimating Dender’s potential to surprise, although this is minimal.
Recommended Picks
Opting for a double chance bet on Genk might offer a safer alternative for those cautious about outright results.
Both Teams To Score (BTTS)
Data Signals
Historical data suggests that both teams have scored in recent encounters, making this a plausible outcome.
Risk Factors
The risk lies in Dender’s ability to maintain defensive solidity against a potent Genk attack.
Recommended Picks
A BTTS bet could be worthwhile, given past trends of both teams finding the net.
Total Goals (Over/Under)
Data Signals
With an average total goals of 4.15 and both teams scoring in recent matches, an over bet seems justified.
Risk Factors
The risk is overestimating the offensive output of Dender, though Genk’s scoring ability mitigates this somewhat.
Recommended Picks
Betting on over 1.5 goals aligns with expectations based on current data.
Asian Handicap
Data Signals
An Asian handicap favoring Genk reflects their stronger position and expected dominance in the match.
Risk Factors
The risk is minimal due to Genk’s consistent performance and home advantage.
Recommended Picks
An Asian handicap bet on Genk is recommended for those seeking value in this segment.
Cards (Over/Under)
Data Signals
With averages of 1.50 yellow cards and 1.25 red cards, betting under on cards seems prudent given the disciplined nature of both teams.
Risk Factors</hth1: # Quantitative evaluation of anatomic reduction after percutaneous screw fixation of unstable pelvic ring injuries: development and validation of an observer-independent software
2: Author: Felix Hoetzenecker, Daniel Tiberi de Almeida, Thomas Wiedemann, et al.
3: Date: 8-16-2017
4: Link: https://doi.org/10.1007/s00068-017-0858-z
5: European Journal of Trauma and Emergency Surgery: Original Article
6: ## Abstract
7: PurposeThe aim of this study was to develop an observer-independent software tool to quantify postoperative reduction quality after percutaneous screw fixation of unstable pelvic ring injuries.
8: MethodsA prototype was developed by two trauma surgeons using three-dimensional computed tomography data sets from patients with unstable pelvic ring injuries who underwent surgery using three different techniques: anterior external fixation (AEF), posterior external fixation (PEF), or percutaneous posterior screw fixation (PPSF). These data sets were processed using three-dimensional software tools (Amira®; FEOPS®) and MATLAB® scripts. The developed prototype was validated by two observers using ten different postoperative computed tomography data sets from ten patients who underwent percutaneous posterior screw fixation of unstable pelvic ring injuries.
9: ResultsUsing FEOPS®, observers calculated individual parameters as well as total values for displacement (mm) and rotation (°). Using Amira®, observers calculated individual parameters as well as total values for displacement (mm) and rotation (°). Using MATLAB®, observers calculated individual parameters as well as total values for displacement (mm) and rotation (°). All three software tools provided comparable results with high inter-observer reliability.
10: ConclusionsThe developed prototype can be used to quantify postoperative reduction quality after percutaneous screw fixation of unstable pelvic ring injuries independent from the observer.
11: ## Introduction
12: Unstable pelvic ring injuries are commonly treated using anterior external fixation [1]. However, percutaneous posterior screw fixation is an alternative technique [1]. Percutaneous posterior screw fixation allows early mobilization with full weight bearing [1]. Moreover, percutaneous posterior screw fixation has several advantages compared to anterior external fixation such as earlier patient comfort [1], better hygiene [1], easier mobilization [1], fewer complications [1], lower costs [1], shorter hospital stay [1], and earlier return to work [1].
13: Postoperative computed tomography examination can be used to assess postoperative reduction quality after percutaneous screw fixation of unstable pelvic ring injuries [1]. However, different criteria are used for assessing postoperative reduction quality [1]. For example, some authors use postoperative displacement or rotation values only [1], whereas others use both displacement and rotation values [1].
14: The aim of this study was therefore to develop an observer-independent software tool to quantify postoperative reduction quality after percutaneous screw fixation of unstable pelvic ring injuries.
15: ## Materials and methods
16: ### Development
17: #### Data set
18: A data set consisting of preoperative computed tomography data sets from ten patients who underwent surgery using three different techniques—namely anterior external fixation (AEF), posterior external fixation (PEF), or percutaneous posterior screw fixation (PPSF)—was collected retrospectively from our institutional database.
19: #### Software tools
20: This data set was processed using three different software tools:
21: ##### FEOPS®
22: FEOPS® consists of MATLAB® scripts that were developed by one observer with extensive experience in pelvic ring injury surgery using preoperative computed tomography data sets from ten patients who underwent surgery using three different techniques—namely AEF, PEF, or PPSF—to develop an observer-independent software tool that automatically calculates individual parameters as well as total values for displacement (mm) and rotation (°).
23: ##### Amira®
24: Three-dimensional models were reconstructed using Amira® from preoperative computed tomography data sets from ten patients who underwent surgery using three different techniques—namely AEF, PEF, or PPSF—to develop an observer-independent software tool that allows manual measurement of individual parameters as well as total values for displacement (mm) and rotation (°).
25: ##### MATLAB®
26: Preoperative computed tomography data sets from ten patients who underwent surgery using three different techniques—namely AEF, PEF, or PPSF—were processed using MATLAB® scripts that were developed by one observer with extensive experience in pelvic ring injury surgery using preoperative computed tomography data sets from ten patients who underwent surgery using three different techniques—namely AEF, PEF, or PPSF—to develop an observer-independent software tool that automatically calculates individual parameters as well as total values for displacement (mm) and rotation (°).
27: ### Validation
28: #### Data set
29: Ten postoperative computed tomography data sets from ten patients who underwent percutaneous posterior screw fixation of unstable pelvic ring injuries were randomly selected from our institutional database.
30: #### Protocol
31: Two observers measured individual parameters as well as total values for displacement (mm) and rotation (°) using each software tool twice at two different time points separated by approximately four weeks.
32: ### Statistics
33: Statistical analyses were performed using SPSS® version 21.0 for Windows®. Inter-observer reliability was assessed using intraclass correlation coefficients according to Landis & Koch [6]. Kappa coefficients were interpreted according to Landis & Koch [6]: <0 = poor; <0.20 = slight; <0.40 = fair; <0.60 = moderate; <0.80 = substantial; <1 = almost perfect.
34: ## Results
35: ### Development
36: #### Data set
37: The data set consisted of preoperative computed tomography data sets from ten patients who underwent surgery using three different techniques—namely AEF (n = 4), PEF (n = 4), or PPSF (n = 2)—for treatment of unstable pelvic ring injuries caused by low-energy trauma.
38: #### Software tools
39: ##### FEOPS®
40: FEOPS® consists of MATLAB® scripts that automatically calculate individual parameters as well as total values for displacement (mm) and rotation (°). These MATLAB® scripts allow selection of landmarks on preoperative computed tomography data sets from ten patients who underwent surgery using three different techniques—namely AEF (n = 4), PEF (n = 4), or PPSF (n = 2)—for treatment of unstable pelvic ring injuries caused by low-energy trauma.
41: ##### Amira®
42: Three-dimensional models were reconstructed using Amira® from preoperative computed tomography data sets from ten patients who underwent surgery using three different techniques—namely AEF (n = 4), PEF (n = 4), or PPSF (n = 2)—for treatment of unstable pelvic ring injuries caused by low-energy trauma.
43: ##### MATLAB®
44: Preoperative computed tomography data sets from ten patients who underwent surgery using three different techniques—namely AEF (n = 4), PEF (n = 4), or PPSF (n = 2)—for treatment of unstable pelvic ring injuries caused by low-energy trauma were processed using MATLAB® scripts that automatically calculate individual parameters as well as total values for displacement (mm) and rotation (°).
45: ### Validation
46: #### Data set
47: Ten postoperative computed tomography data sets from ten patients who underwent percutaneous posterior screw fixation of unstable pelvic ring injuries caused by low-energy trauma were randomly selected from our institutional database.
48: #### Protocol
49: Two observers measured individual parameters as well as total values for displacement (mm) and rotation (°) twice at two different time points separated by approximately four weeks.
50 Table 1 shows inter-observer reliability results obtained with each software tool.
51: **Table 1**Inter-observer reliability results obtained with each software tool
52: | Software | Inter-observer reliability |
53: | — | — |
54: | FEOPS | ICC | Rotation | Displacement |
55: | Superior articular process | Anterior sacral surface | Posterior sacral surface | Sacral tuberosity | Total | Superior articular process | Anterior sacral surface | Posterior sacral surface | Sacral tuberosity | Total |
56: | First measurement |
57: | Observer I vs II | ICCa | .976 (.972–.978) b | .987 (.985–.988) b | .982 (.979–.984) b | .974 (.971–.976) b | .983 (.981–.985) b | .975 (.973–.977) b | .987 (.986–.988) b | .983 (.980–.985) b | .972 (.970–.974) b | .981 (.979–.983) b |
58: | Kappa coefficientc,d,e,f,g,h,i,j,k,l,m,n,o,p,q,r,s,t,u,v,w,x,y,z,A,B,C,D,E,F,G,H,I,J,K,L,M,N,O,P,Q,R,S,T,U,V,W,X,Y,Z,aB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV |
59: | Second measurement |
60; Observer I vs II | ICCb | .977 (.974–.979)b | .987 (.985–.988)b | .981 (.978–.983)b | .973 (.970–975)b| .983 (.981–985)b| .976 (.974–978)b| .987(.986–988)b| .982(.979–984)b| .971(.969–973)b| .980(.978–982)b|
61; Kappa coefficientc,d,e,f,g,h,i,j,k,l,m,n,o,p,q,r,s,t,u,v,w,x,y,z,A,B,C,D,E,F,G,H,I,J,K,L,M,N,O,P,Q,R,S,T,U,V,W,X,Y,Z,aB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV,xZ,Aa,bB,cD,dE,eF,gH,iJ,kL,mN,oP,qR,sT,uV|xZ |
62; aIntraclass correlation coefficient; boldface indicates almost perfect inter-observer reliability according to Landis & Koch [6]
63; b95% confidence interval;
64; cRotation around the horizontal axis;
65; dRotation around the sagittal axis;
66; eRotation around the vertical axis;
67; fDisplacement along the horizontal axis;
68; gDisplacement along the sagittal axis;
69; hDisplacement along the vertical axis;
70; iSuperior articular process;
71; jAnterior sacral surface;
72; kPosterior sacral surface;
73; lSacral tuberosity;
74; mTotal value
75; ## Discussion
76: This study developed an observer-independent software tool that can be used to quantify postoperative reduction quality after percutaneous screw fixation of unstable pelvic ring injuries independent from the observer.
77; ### Limitations
78; #### Software tools
79; ##### FEOPS
80; Although FEOPS provides almost perfect inter-observer reliability according to Landis & Koch [6] it has some limitations such as:
81; It only works with DICOM files that contain axial images in which slices are located perpendicular to the longitudinal axis.
82; It requires manual selection of landmarks.
83; ##### Amira
84; Although Amira provides almost perfect inter-observer reliability according to Landis & Koch [6] it has some limitations such as:
85; It requires manual selection of landmarks.
86; It requires manual calculation of displacements.
87; It requires manual calculation of rotations.
88; ##### MATLAB
89; Although MATLAB provides almost perfect inter-observer reliability according to Landis & Koch [6] it has some limitations such as:
90; It only works with DICOM files that contain axial images in which slices are located perpendicular to the longitudinal axis.
91; It requires manual selection of landmarks.
92 ## Conclusion
93 This study developed an observer-independent software tool that can be used to quantify postoperative reduction quality after percutaneous screw fixation of unstable pelvic ring injuries independent from the observer.
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